Saimm 201512 dec

VOLUME 115

NO. 12

DECEMBER 2015

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The Southern African Institute of Mining and Metallurgy ) ) ) ) ) ) ! !

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H. Simon (1957–1958) M. Barcza (1958–1959) R.J. Adamson (1959–1960) W.S. Findlay (1960–1961) D.G. Maxwell (1961–1962) J. de V. Lambrechts (1962–1963) J.F. Reid (1963–1964) D.M. Jamieson (1964–1965) H.E. Cross (1965–1966) D. Gordon Jones (1966–1967) P. Lambooy (1967–1968) R.C.J. Goode (1968–1969) J.K.E. Douglas (1969–1970) V.C. Robinson (1970–1971) D.D. Howat (1971–1972) J.P. Hugo (1972–1973) P.W.J. van Rensburg (1973– 1974) R.P. Plewman (1974–1975) R.E. Robinson (1975–1976) M.D.G. Salamon (1976–1977) P.A. Von Wielligh (1977–1978) M.G. Atmore (1978–1979) D.A. Viljoen (1979–1980) P.R. Jochens (1980–1981) G.Y. Nisbet (1981–1982) A.N. Brown (1982–1983) R.P. King (1983–1984) J.D. Austin (1984–1985) H.E. James (1985–1986) H. Wagner (1986–1987) B.C. Alberts (1987–1988) C.E. Fivaz (1988–1989) O.K.H. Steffen (1989–1990) H.G. Mosenthal (1990–1991) R.D. Beck (1991–1992) J.P. Hoffman (1992–1993) H. Scott-Russell (1993–1994) J.A. Cruise (1994–1995) D.A.J. Ross-Watt (1995–1996) N.A. Barcza (1996–1997) R.P. Mohring (1997–1998) J.R. Dixon (1998–1999) M.H. Rogers (1999–2000) L.A. Cramer (2000–2001) A.A.B. Douglas (2001–2002) S.J. Ramokgopa (2002-2003) T.R. Stacey (2003–2004) F.M.G. Egerton (2004–2005) W.H. van Niekerk (2005–2006) R.P.H. Willis (2006–2007) R.G.B. Pickering (2007–2008) A.M. Garbers-Craig (2008–2009) J.C. Ngoma (2009–2010) G.V.R. Landman (2010–2011) J.N. van der Merwe (2011–2012) G.L. Smith (2012–2013) M. Dworzanowski (2013–2014) J.L. Porter (2014–2015)

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VOLUME 115 NO. 12 DECEMBER 2015

Contents Journal Comment—21 years of Chemical Engineering & Metallurgy at Wits

by J.H. Potgieter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

iv-v

President’s Corner

by R.T. Jones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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PAPERS – CHEMICAL ENGINEERING & METALLURGY AT WITS Removal of heavy metals using cassava peel waste biomass in a multi-stage countercurrent batch operation

by G.S. Simate, S. Ndlovu, and L. Seepe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Optimization of complex integrated water and membrane network systems

by M. Abass, E. Buabeng-Baidoo, D, Nezungai, N. Mafukidze, and T. Majozi . . . . . . . . . . . .

The impact of coal quality on the efficiency of a spreader stoker boiler

by R.L. Taole, R.M.S. Falcon, and S.O. Bada. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Coal quality and uranium distribution in Springbok Flats Coalfield samples

by M. Ndhlalose, N. Malumbazo, and N. Wagner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Synthesis of sodium silicate from South African coal fly ash and its use as an extender in oil well cement applications

by T. Kaduku, M.O. Daramola, F.O. Obazu, and S.E. Iyuke. . . . . . . . . . . . . . . . . . . . . . . . . . .

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel

by D.E.P. Klenam, C. Polese, L.H. Chown, S. Kwofie, and L.A. Cornish. . . . . . . . . . . . . . . . . .

Making sense of our mining wastes: removal of heavy metals from AMD using sulphidation media derived from waste gypsum

by J. Mulopo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Enhancing study practices: are first-year students ‘resistant to change’?

by L. Woollacott, S. Booth, and A. Cameron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Recycling of cemented tungsten carbide mining tool scrap

by C.S. Freemantle and N. Sacks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Titanium carbide–silicon nitride reactions at high temperature

by N. Can and R. Hurman Eric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes: prospects for acid mine drainage (AMD) treatment

by M.O. Daramola, B. Silinda, S. Masondo, and O.O. Oluwasina. . . . . . . . . . . . . . . . . . . . . . .

1137 1143 1159 1167

1175 1183

1193 1199 1207 1215

1221

PAPERS OF GENERAL INTEREST The accuracy of calcium-carbonate-based saturation indices in predicting the corrosivity of hot brackish water towards mild steel

by A. Palazzo, J. van der Merwe, and G. Combrink . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The effect of sodium carbonate on the dispersion behaviour and froth flotation of a nickel ore

by B. Feng, Q.M. Feng, Y.P. Lu, and H.H. Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The influence of water quality on the flotation performance of complex sulphide ores: case study at Hajar Mine, Morocco

by K. Boujounoui, A. Abidi, A. Bacaoui, K.El Amari, and A. Yaacoubi . . . . . . . . . . . . . . . . . .

Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi

by F.X. Paquot and C. Ngulube . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1229

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%'( $%&! $ ) # &"!( ) !$(# VOLUME 115

R. Dimitrakopoulos, McGill University, Canada D. Dreisinger, University of British Columbia, Canada E. Esterhuizen, NIOSH Research Organization, USA H. Mitri, McGill University, Canada M.J. Nicol, Murdoch University, Australia E. Topal, Curtin University, Australia

NO. 12

DECEMBER 20 15

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R.D. Beck J. Beukes P. den Hoed M. Dworzanowski B. Genc M.F. Handley R.T. Jones W.C. Joughin J.A. Luckmann C. Musingwini J.H. Potgieter R.E. Robinson T.R. Stacey

Journal Comment The School of Chemical and Metallurgical Engineering at the University of the Witwatersrand

C

elebrating one’s 21 year of existence is indeed a most joyous occasion, and another milestone in the history of Chemical and Metallurgical Engineering at the University of the Witwatersrand. Since its formation in 1995 through the merger of the departments of Chemical Engineering and Metallurgy and Materials Engineering as the School of Process and Materials Engineering, the School has gone from strength to strength. In 2005 ‘Chemical and Metallurgical Engineering’ became the official designation of the School after ratification of the name change by the University Council. The School has been at the forefront of education and research in engineering and has contributed greatly to the demand for skilled manpower by the process, beneficiation, and metallurgical industries in South Africa. The School prides itself on its contribution in terms of human resources training and development, knowledge generation, and community involvement and contributions. A significant number of industry and academic leaders locally and worldwide are Wits Chemical and Metallurgical Engineering graduates and alumni.

Chemical Engineering at Wits can trace its origins back to the immediate predecessors of the University, i.e. the University College Johannesburg (Transvaal) and prior to that the South African School of Mines, both of which offered courses in Chemical Technology. When Wits was established, Chemical Technology courses continued and the first Bachelor of Science in Engineering (Chemical Technology) degrees were awarded in March 1922. After 1926 the courses were revised and the degree awarded from 1928 onwards was Bachelor of Science in Engineering (Chemical Engineering). Although the Chemical Engineering degrees have always been awarded in the Faculty of Engineering, responsibility for the courses lay with the Department of Chemistry and Chemical Technology from 1922–1927 and thereafter the Department of Chemistry and Chemical Engineering from 1928–1960.

The first independent Department of Chemical Engineering at Wits was established in 1961 with Professor O.B. Volckman as its first Head. Thereafter Professor David Glasser, Associate Professor Donald Williams and Professor Tony Bryson acted as heads of department until 1995, when the School of Process and Materials Engineering was formed. Professor Bryson was also the first Head of the newly established school from 1995–1998. For a more complete history on Chemical Engineering at Wits, please consult Murray’s book ‘Wits: the Early Years’ (Murray, 1982) and Harris’s ‘Chemical Engineering at the University of the Witwatersrand, Johannesburg’ (Harris, 1983).

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Metallurgy at Wits has an even longer history than Chemical Engineering and can trace its roots to one of the three founding departments of firstly the Kimberley School of Mines and, after the second Anglo-Boer War, the South African School of Mines, together with the departments of Mining Engineering and Geology. Both the latter are still independent Schools at Wits, and all three will celebrate their 120th birthdays in 2016. The Department of Metallurgy has grown substantially over the years since the appointment of Professor G.H. Stanley as the first Chair of Metallurgy and Head in 1904. He held this position for 35 years until his retirement in 1939 and was succeeded by Professor L. Taverner from 1940 until 1959. The establishment of the Minerals Research Laboratory in 1934, a joint venture between the State, the University, and the forerunner of the present-day Council for Mineral Technology (Mintek), gave research a strong boost. Both the departments of Metallurgy and Chemical Engineering benefitted from the research focus on the recovery of metals and minerals from ores, and both presented specialized courses in minerals processing and extractive metallurgy for third- and fourth-year students. While some courses were jointly presented, each department awarded its own degree and it was only with the formation of the School in 1995 that the full strength and synergy between the two departments in the field of minerals beneficiation could be fully exploited.

Between 1959 and 1962 Professor C.E. Mavrocordatos led the Metallurgy Department, followed by Professor D.D. Howat who took over from the beginning of 1963 until 1975. From then on the headship of the department became more of a rotating than a permanent position, with Professors G.G. Garrett, R.P King, P. Robinson, and R.H. Eric all acting as heads of department for selected periods of time. Professor Hßrman Eric was the last Head of the Department of Metallurgy before its merger with Chemical Engineering to form the current School. He was subsequently also the second Head of the School of Process and Materials Engineering from 1999–2002. For more detail on the history of Metallurgy at Wits, consult Eric’s descriptions (Eric, 2004, 2006).

In 2002 Professor Wolter te Riele took over the headship of the School until the end of 2003. Following a short period of four months during which Professor Eric was acting Head of School, Professor Herman Potgieter became the Head of the School and led the efforts to change the name of the School to reflect the traditional disciplines from which it originated. Following his departure in 2008, Mr Bob Tait acted as Head of School until June 2009 when Professor Sunny Iyuke took over the

Journal Comment (continued)

the Centre of Excellence in Strong Materials – CoE SM), welding, coal (Clean Coal Technologies Group), sustainable energy and environmental research (SEERU), water treatment, specifically acid mine drainage (AMD) (Industrial and Mine Water Treatment Research Unit – IMWaRU), nanotechnology, tribology, and process optimization.

We are proud of our history and our significant contribution to South Africa in terms of human resources development and delivering competent graduates for industry, as well as supplying fundamental and applied research to solve industrial problems and contribute to relevant technology. The School of Chemical and Metallurgical Engineering at Wits is well placed to continue at the forefront of teaching and research with a group of enthusiastic, efficient and dynamic staff consisting of a mixture of well-established and experienced academics and a group of young, developing academics. Despite difficult financial times and turmoil in the mining industry, we look confidently to the future in the knowledge that we shall continue to provide a home for future engineering leaders and inspiring innovation to give our graduates the edge!

References 1. MURRAY, B.K. 1982. Wits: The Early Years.

Witwatersrand University Press, Johannesburg.

2. HARRIS, W.F. 1983. Chemical Engineering at the University of the Witwatersrand. ChemSA, March 1983.

3. ERIC, R.H. 2004. A brief history of time in Wits Metallurgy. Journal of the South African Institute of Mining and Metallurgy, November 2004.

4. ERIC, R.H. 2006. A glimpse of Pyrometallurgy at Wits University. Proceedings of Southern African Pyrometallurgy 2006. Jones, R.T. (ed.). South African Institute of Mining and Metallurgy, Johannesburg. pp. 101–104.

J.H. Potgieter Professor and Head of School

v

reins. Professor Iyuke headed the School until 2014, when the process commenced again to find a new Head.

Professor Thoko Majozi steered the ship as acting Head of School in the last six months of 2014 until Professor Herman Potgieter returned in January 2015 as Head of School again.

The School currently has a total staff complement of 54, made up of 14 Chemical Engineers, 14 Metallurgists, 5 visiting temporary lecturers, 4 workshop personnel members, a team of 9 administrative staff, and 8 technicians and laboratory assistants. There are 755 undergraduate students, 240 registered postgraduate students (part-time and full-time) and 5 postdoctoral fellows currently studying and working in the School.

The School hosts no less than three South African Research Chair Initiative candidates in the persons of Professor Thoko Majozi (Sustainable Process Engineering), Professor Selo Ndlovu (Hydrometallurgy and Sustainable Development), and Professor Rosemary Falcon (Clean Coal Technology) out of a total of 25 such chairs in the whole of the University of the Witwatersrand. In addition, Professor Jack Sigalas (Chair in Ceramic Science) and Professor Tony Paterson (Welding and Fabrication Engineering) hold endowed chairs from Element 6 and the South African Institute of Welding, respectively.

The School presents fully ECSA-accredited undergraduate programmes in Chemical and Metallurgical Engineering, as well as postgraduate MSc degrees on a 50% taught/50% research, or research-only basis in the specialization areas of Coal Studies, Pyrometallurgy, Minerals Processing and Extractive Metallurgy, and Advanced Chemical Engineering. The postgraduate programme in Oil and Gas Engineering (Petroleum) is unique in South Africa and cannot be followed at any other local university, while the postgraduate program in Welding Engineering is internationally accredited and offers a route to full registration as a Welding Engineer.

PhD opportunities in all these areas are also available. The School has excellent ties with industry and in addition it offers consultation services over a wide spectrum for industry. The School prides itself on always being sensitive to the needs of industry and society in general, and updates its curricula and research accordingly in order to stay relevant and provide the latest knowledge to graduates. Current areas of research strength include pyrometallurgy, hydrometallurgy (Metals and Minerals Extraction and Recovery Group – MMERG), physical metallurgy of steels, stainless steels, Wo-Co hard metals, ceramics, and thermodynamic modelling in the research focus areas of Hard Metals and Stainless Steels as part of

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A right to knowledge

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elson Mandela said that ‘Education is the most powerful weapon which you can use to change the world’. Southern Africa suffers greatly from a shortage of well-educated people. However, it is a massive challenge to increase literacy, let alone to provide education for all people in the region, starting with early childhood education, through primary and secondary schooling, and culminating with university studies. But this is a challenge to which we must rise, as educated people are employable and have the capacity to build a better society, to create employment, and to reduce poverty.

The Universal Declaration of Human Rights (1948) says, in Article 26, ‘Everyone has the right to education. Education shall be free, at least in the elementary and fundamental stages. Elementary education shall be compulsory. Technical and professional education shall be made generally available and higher education shall be equally accessible to all on the basis of merit.’ Some countries seem to have got this right, with examples of free education (even at university level) seen in countries including Cuba in the developing world (which spends 10 to 11% of its GDP on education), and Norway in the developed world. Annual spending on education around the world exceeds five trillion US dollars, yet there are still around 800 million people who are unable to read or write. There is clearly a pressing need for more professional, dedicated, welltrained teachers, and for society at large to confer a high social status on these important people (as is the case in the Nordic countries).

In South Africa, the Freedom Charter of 1955 declared that ‘Education shall be free, compulsory, universal and equal for all children. Higher education and technical training shall be opened to all by means of state allowances and scholarships awarded on the basis of merit.’ More recently, Section 29 of the Bill of Rights in the Constitution of South Africa says that ‘Everyone has the right to a basic education, including adult basic education; and to further education, which the state, through reasonable measures, must make progressively available and accessible’.

A report commissioned by the Department of Higher Education last year found that South Africa spends only 0.75% of its GDP on tertiary education, which is less than the average in Africa, let alone the world average. Universities say that government funding has not kept up with inflation and the huge increase in student numbers in recent years. Rising fees at universities have made studying unaffordable for many potential students. There is no doubt that many students are effectively excluded from a university education because of poverty.

Students at the University of the Witwatersrand started protesting around 14 October 2015, in response to an announcement by the university that fees would be raised by 10.5% in the New Year. The ‘Fees Must Fall’ student protests quickly spread to other universities across South Africa. University activities were significantly disrupted and access to campuses was effectively blocked. By 17 October, Wits University agreed to suspend the fee increase, and declined to take disciplinary action against participating students or staff members. Exams were postponed by a week. After a week of nationwide protests, a mass rally of many thousands of protesting students was held outside the Union Buildings in Pretoria. This resulted in the President of South Africa declaring that there will be a zero increase of university fees in 2016.

A small group of demonstrators turned violent, setting fire to a portable toilet, and breaking down fences. The police responded with tear gas, stun grenades, and rubber bullets. The students themselves called for discipline, stressing that it was a peaceful protest.

There seems to be a general consensus view that the protesting students managed to achieve a great deal in a relatively short space of time. Overall, the protests were disruptive but relatively peaceful (with a few exceptions). Many commentators hold the view that these protests are historically significant for our country. Of course, it remains to be seen whether the zero increase in fees is altogether a good thing -- presumably good for students' finances, but not necessarily so for providing the funds needed for quality education (unless the funds can be made up from somewhere else). The universities have argued that they need a greater income to keep up their standards.

The SAIMM’s Young Professionals Council responded promptly to the protests by presenting a very constructive option (by means of contributions to the SAIMM Scholarship Trust Fund) for people to contribute towards solving some of the very real problems faced by many students in South Africa. This fund makes a big difference to the lives of many students, and enables them to stay at university when they would otherwise have to drop out because of insufficient money for books or even food. This is a very good example of the way in which the SAIMM shows that it cares.

There is a further dimension to the story of the mining and metallurgy students of 2015. Perhaps half of the students who have recently graduated will not find employment in the year ahead. The universities have done a great job in response to the call to double the number of graduates in the past few years. However, in the current downturn, there are very few jobs available. This is a tragedy for the individual student who might have come from a rural village where the community has raised funds for him or her to get an education, with the expectation of a well-paying job, and the student has to return home dejected and empty-handed. Has a proper survey been carried out to determine how many engineers the mining industry actually needs in good times and in bad times?

As we approach the end of 2015, the mining industry is feeling rather battered and bruised after an exceptionally tough year. Many observers have indicated that 2016 is likely to be tough too, but we know that the commodity business is a cyclical one and the world we live in requires a variety of metals in order to function, so there is some optimism for the medium term. Best wishes to all for a good rest during the coming holiday season.

R.T. Jones President, SAIMM

vi

PAPERS IN THIS EDITION These papers have been refereed and edited according to internationally accepted standards and are accredited for rating purposes by the South African Department of Higher Education and Training

Papers — Chemical Engineering & Metallurgy at Wits Removal of heavy metals using cassava peel waste biomass in a multi-stage countercurrent batch operation

by G.S. Simate, S. Ndlovu, and L. Seepe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137 A study is presented of the removal of cobalt (Co2+), chromium (Cr3+) and vanadium (V3+) from synthetic effluent solution using cassava waste biomass in a multi-stage counter current batch system. The target metal concentrations in the final outlet stream were measured against the South African Department of Water and Forestry standards.

Optimization of complex integrated water and membrane network systems

by M. Abass, E. Buabeng-Baidoo, D, Nezungai, N. Mafukidze, and T. Majozi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1143 This work considers the synthesis and optimization of water networks through partial treatment of water (regeneration) before recycle/re-use. Four different compositions were studied and the developed models applied to a pulp and paper and petroleum case study to demonstrate their applicability.

The impact of coal quality on the efficiency of a spreader stoker boiler

by R.L. Taole, R.M.S. Falcon, and S.O. Bada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1159 This research established the combustion characteristics and efficiencies of South African coals of different qualities and their impact on the performance of a specific travelling grate spreader stoker boiler. The thermographic results led to the conclusion that South African low-grade Gondwana coals undergo delayed ignition and burn at unusually high temperatures.

Coal quality and uranium distribution in Springbok Flats Coalfield samples

by M. Ndhlalose, N. Malumbazo, and N. Wagner. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1167 This investigation examines the deportment of uranium in the coal zones intersected by five boreholes that were drilled in the Springbok Flats Coalfield.

Synthesis of sodium silicate from South African coal fly ash and its use as an extender in oil well cement applications

by T. Kaduku, M.O. Daramola, F.O. Obazu, and S.E. Iyuke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1175 The use of sodium silicate derived from South African coal fly ash (CFA) as an oil well cement slurry extender was investigated. The physico-chemical properties of the material were found to be consistent with those of commercial sodium silicate, and a comparative study indicated that the slurries extended with CFA have slightly lower densities, lower viscosities, and higher compressive strength than those extended with commercial sodium silicate.

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel

by D.E.P. Klenam, C. Polese, L.H. Chown, S. Kwofie, and L.A. Cornish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1183 The effect of surface hardening by pack carburizing on the mechanical properties of AISI 316L steel was studied.

The results show that the process significantly reduces the ductility, ultimate tensile strength, and impact toughness.

Making sense of our mining wastes: removal of heavy metals from AMD using sulphidation media derived from waste gypsum

by J. Mulopo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1193 The recovery of water and the selective removal of valuable metals from acid mine drainage (AMD) was investigated using calcium sulphide produced by the carbothermal reduction of waste gypsum. It was found that although selective metal removal and recovery as metal sulphides can be achieved, the purity of the CaS and mass transfer limitations associated with the AMD-CaS system may be critical for process development.

Enhancing study practices: are first-year students ‘resistant to change’?

by L. Woollacott, S. Booth, and A. Cameron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1199 The claim that students are resistant to changing their study practices was investigated by interviewing chemical and metallurgical engineering students in a South African university at the beginning and end of their first year.

‘Resistance to change’ appeared to be implicit in nature and to be more a consequence of overconfidence and the ‘momentum’ resulting from habit rather than an explicit attitudinal resistance.

These papers will be available on the SAIMM website

http://www.saimm.co.za

Papers — Chemical Engineering & Metallurgy at Wits (continued) Recycling of cemented tungsten carbide mining tool scrap

by C.S. Freemantle and N. Sacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1207 Two different techniques and processes – the zinc recycling process (PRZ) and acetic acid leaching – were used to recover and recycle cemented tungsten carbide mining tool scrap metal. It was found that the two processes could be used as complementary processes on an industrial scale.

Titanium carbide–silicon nitride reactions at high temperature

by N. Can and R. Hurman Eric. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1215 The kinetics and mechanism of the chemical interaction between silicon nitride and titanium carbide under nitrogen and argon atmospheres were investigated using thermogravimetric analysis. The relevant activation energies, as well as rate constants and diffusion coefficients, were determined, and the mechanisms of reactions modelled.

Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes: prospects for acid mine drainage (AMD) treatment

by M.O. Daramola, B. Silinda, S. Masondo, and O.O. Oluwasina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1221 Polyether sulfone (PES)-sodalite (SOD) mixed matrix membranes loaded with different amounts of SOD particles were fabricated and evaluated for the treatment of acid mine drainage. The results showed that the mechanical strength of the membrane, as well as the selectivity towards Mn2+, Pb2+, Cu2+, Al3+, and Mg2+, was enhanced by increasing the SOD loading. Optimization of the synthesis protocol and operational conditions is needed to improve the performance of the membrane.

Papers of General Interest The accuracy of calcium-carbonate-based saturation indices in predicting the corrosivity of hot brackish water towards mild steel

by A. Palazzo, J. van der Merwe, and G. Combrink . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1229 An empirically derived nonlinear regression model was developed and compared with the existing indices for predicting the corrosivity of mild steel in contact with brackish water at 45ºC. The accuracy of the broader application and relevance of the indices are also discussed.

The effect of sodium carbonate on the dispersion behaviour and froth flotation of a nickel ore

by B. Feng, Q.M. Feng, Y.P. Lu, and H.H. Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1239 The effect of sodium carbonate on the flotation performance of a nickel ore was studied. The flotation resultS show that the presence of lizardite minerals in the ore interferes with the flotation OF pentlandite. The addition of sodium carbonate improves pentlandite flotation recovery by changing the interparticle forces from attraction to repulsion, resulting in the removal of adhering slimes from pentlandite surfaces.

The influence of water quality on the flotation performance of complex sulphide ores: case study at Hajar Mine, Morocco

by K. Boujounoui, A. Abidi, A. Bacaoui, K.El Amari, and A. Yaacoubi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1243 A preliminary study on the effect of water quality on the flotation of galena, sphalerite, chalcopyrite, and pyrrhotite was carried out using asymmetrical fractional factorial design. The results showed that the influence of process water on lead flotation depends on its composition and concentrations of constituents.

Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi

by F.X. Paquot and C. Ngulube . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253 The previously stockpiled mixed sulphide/oxide ores at Kansanshi are now treated by flotation using controlled potential sulphidization. This paper describes the development of the process and its optimization. The effect of the complex mineralogy on the flotation performance is discussed.

http://dx.doi.org/10.17159/2411-9717/2015/v115n12a1

Removal of heavy metals using cassava peel waste biomass in a multi-stage countercurrent batch operation

by G.S. Simate*, S. Ndlovu*, and L. Seepe*

This paper presents a study of the removal of cobalt (Co2+), chromium (Cr3+), and vanadium (V3+) from synthetic effluent solution using cassava waste biomass. Test work was carried out in a multi-stage countercurrent batch system. Single and ternary metal ion systems were studied. A feed inlet concentration of 100 mg/L for each metal ion system was contacted with 0.5 g of cassava waste biomass. The target concentration in the final outlet stream was set against the South African Department of Water and Forestry (DWAF) standards. The results showed that the adsorption capacity was slightly lower for ternary metal ion systems than for single metal ion systems. This was attributed to the greater competition among the metal ions for the occupancy of the binding surfaces on the cassava waste in the ternary systems. Eight adsorption stages were required to meet the targeted limit of 0.5 mg/L for Co2+ set by the DWAF. The Cr3+ system needed six stages to obtain the targeted limit of 0.1 mg/L, while the V3+ system required four stages to attain the target limit of 0.2 mg/L. In general, cassava waste biomass adsorbed the metal ions in the following order: V3+ > Cr3+ > Co2+.

heavy metals, wastewater, biosorption, cassava waste, biomass, multistage, countercurrent, batch.

Wastewaters from many sources, such as the metallurgical, tannery, chemical manufacturing, mining, and battery manufacturing industries, contain toxic heavy metals. The concentrations of some of the toxic metals in these effluents are sometimes higher than permissible discharge levels. Discharge of the contaminated wastewater into the environment would, therefore, create a significant environmental hazard, including impacts on human, animal, and plant health (Matouq et al., 2005). According to the South African Department of Water Affairs and Forestry (DWAF) (2005), the permissible discharge limits for chromium, cobalt, and vanadium are 0.1, 0.5, and 0.2 mg/L, respectively. Therefore, it becomes necessary to remove these heavy metals from wastewaters by an appropriate treatment process before releasing them into the environment (Meena et al., 2005).

Several conventional chemical and physical methods have been developed and used to remove high concentrations of heavy metals from wastewater effluents, including (but not

* School of Chemical and Metallurgical Engineering, University of the Witwatersrand, Johannesburg. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015 and revised paper received Nov. 2015.

1137

â–˛

limited to) precipitation, solvent extraction, ion exchange, reverse osmosis, oxidation/reduction, sedimentation, filtration, and electrochemical techniques (Volesky, 2001; Feng et al., 2010; Nassar, 2010; Shen et al., 2009; Song et al., 2011; Ahmadi et al., 2014). However, most of these methods have high capital and operational costs, low metal removal efficiency at low concentrations, and generate toxic sludge that requires additional treatment (Ahmadi et al., 2014; Motouq et al., 2015). Therefore, a lot of effort has been directed at the development of economical methods for the removal of toxic heavy metals from wastewater effluents.

The use of biological-based technologies such as biosorption for removal of heavy metals from wastewater effluents has recently become the subject of considerable interest because of the low cost and high efficiency associated with the process (Arminia et al., 2015). Previous studies by the authors have shown that cassava peel waste is a potentially useful biosorbent for treating wastewater contaminated with Co2+, V3+, and Cr3+ ions (Ndlovu et al., 2013; Simate and Ndlovu, 2014; Seepe, 2014). Cassava is a perennial woody shrub, grown as an annual crop, and serves as a major source of low-cost carbohydrates for populations in the humid tropics (O’Hair, 1995; Simate et al., 2013; Adetunji et al., 2015). In the past, the largest producer of cassava was Brazil, followed by Thailand, Nigeria, the DRC, and Indonesia (O’Hair, 1995; Adetunji et al., 2015), but today Nigeria is the largest producer (Adetunji et al., 2015). So far, not much effort has been made to control or manage the enormous quantities of wastes arising from processing cassava tuber into its

Removal of heavy metals using cassava peel waste biomass various products, which are abundant and available in all seasons (Seepe, 2014). Since cassava waste has no economic value, its conversion into biosorbents would ultimately economically benefit the millions of cassava producers.

Indeed, the economic utilization of cassava waste would not only provide a solution to the environmental nuisance that it poses, but would create employment and improve local economies (Ndlovu et al., 2013).

Since the manner in which the biomass contacts with the solution to be treated is of particular significance for large-scale treatment of water, initial studies by the authors involved, firstly, batch equilibrium relating to adsorbate, adsorbent, and operating conditions (Ndlovu et al., 2013). This was followed by heavy metal removal studies in a column packed with immobilized cassava waste pellets (Simate and Ndlovu, 2014).

Column-type continuous flow operations have an advantage over batch-type operations because the rates of adsorption depend on the concentration of solute in the solution being treated. For column operation, the biomass is continuously in contact with a fresh solution. Consequently, the concentration in the solution in contact with a given layer of biomass in a column changes very slowly. In batch treatment, the concentration of solute in contact with a specific quantity of biomass decreases much more rapidly as adsorption proceeds, thereby decreasing the effectiveness of the adsorbent for removing the solute (Zhou, 2013).

However, the main limitations of the two studies are: (1) batch systems are usually limited to the treatment of small quantities of wastewater (Bharathi and Ramesh, 2013), and data obtained from such systems may not be applicable directly to most treatment systems (such as column operations) where the contact time is not sufficient for the attainment of equilibrium (Zulfadhly et al., 2001; Vinodhini and Das, 2010; Vimala et al., 2011; Bharathi and Ramesh, 2013); and (2) fixed-bed column studies are characterized by clogging and subsequent release of adsorbent into the treated wastewater (Amirnia et al., 2015), and immobilization of biomass also causes mass transfer limitations by hindering the access of the metals to the biosorbent sites compared to suspended biosorbents (Tsezos, 1990; Cassidy et al., 1996).

Furthermore, the regeneration capacity of immobilized biomass is limited, thus there is need for biomass to be replaced frequently, which is a costly process (Amirnia et al., 2015). However, continuous operation is the only viable way of treating large volumes of wastewater in a reasonable time, and this is where bench-scale batch biosorption studies are limited in their scope (Amirnia et al., 2015).

Based on the authors’ earlier work on the removal of Co2+, V3+, and Cr3+ ions using cassava waste biomass in a batch system (Ndlovu et al., 2013), metal adsorption using a multi-stage countercurrent batch system was investigated in this study. Multi-stage countercurrent adsorption operations

are superior to both batch and fixed bed operations because countercurrent flow maximizes the average driving force for mass transfer between the fluid and the adsorbent (Seepe, 2014). This technique involved contacting the metal ion solution with the cassava waste biomass in a series of gently agitated tanks for a sufficient retention time. The cassava and metal ion solution were transferred in a countecurrent flow arrangement. The schematic diagram for multi-stage batch adsorption is shown in Figure 1. In multi-stage countercurrent batch adsorption, the solution to be treated contains L dm3 solution and the concentration of heavy metals is reduced in each stage from Cn-1 to Cn mg/dm3. The amount of biomass added is B g and the heavy metal concentration on the biomass is increased from qn+1 to qn mg/g of biomass.

234.-2*/520'5,43 1'/

The cassava tubers were obtained from local wholesalers in South Africa and were prepared as described by Ndlovu et al.

(2013). In summary, cassava tubers were carefully peeled and the dried cassava peel waste was ground to 100 Îźm using a blender. Subsequently, the ground cassava peel waste was treated with nitric acid. Finally, sulphhydryl groups (or thiol groups) were introduced onto the cassava biomass using thioglycolic acid solution in the presence of hydroxylamine.

As illustrated in Figure 1, the multi-stage countercurrent biosorption was operated batchwise. About 0.5 g of cassava waste biomass was contacted with 100 mL of the influent solution in each reactor. The concentration of each metal ion in the inlet solution stream was 100 mg/L. Tests were conducted for single and ternary metal ion systems. Mixing was provided by agitation at 150 r/min. After 30 minutes, agitation was stopped and the biosorbent separated from metal ion solution by filtration. The biosorbent and effluent solutions were then transferred to the next respective reactors in a countercurrent manner. This procedure was followed until the final effluent was transferred to the discharge tank from reactor n. The saturated spent biomass emerging from the first reactor was transferred to the regenerator, in which the adsorbed metals were removed, and the biomass was subsequently reactivated and then returned to the adsorption circuit. The main advantage of this process is that the adsorbent can be regenerated as soon as its role in the adsorption step has been completed. Thus, in theory at least, the inventory of the adsorbent can be kept to a minimum.

The quantity of adsorbent required for a given separation can also be reduced by increasing the number of stages.

However, the possibility of regeneration and re-use of the

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Removal of heavy metals using cassava peel waste biomass cassava biomass was beyond the scope of this study. In practice, the heavy metals eluted from the cassava biomass could be further concentrated and/or used as an input in other hydrometallurgical processes.

4/(*3/520'5'-/+(//-105 Fourier transform infrared (FTIR) spectroscopy was used to identify the presence or absence of functional groups on the surface of cassava peel waste biomass before and after thiolation. Figure 2 shows the obtained FTIR spectra. As can be seen from Figure 2(a) and (b), the major difference between the two biomasses is the presence of the sulphhydryl group (-SH), which proves that thiolation process adds sulphhydryl functional groups on the cassava peel biomass (Ndlovu et al., 2013; Simate and Ndlovu, 2015). Other differences between treated and untreated cassava biomass were reported by Ndlovu et al. (2013). For example, the BET surface areas obtained were in the following order: untreated < 0.5 M acid treated < 1 M treated, and both the pore volume and pore size were in the following order: untreated > 0.5 M acid treated > 1 M treated. The point of zero charge (pzc) for the untreated and treated cassava peel biomass was determined as 4.9 and 3.1, respectively.

This shows that the functional groups on untreated cassava

peel biomass are weakly acidic (or more basic) than the functional groups on treated cassava peel biomass. Therefore, the pzc results confirm that more acidic functional groups were incorporated into the cassava peel biomass during thiolation. These results concurr well with the results shown in Figure 2(b), which shows the introduction of an acidic sulphhydryl group after thiolation.

Tables Iâ&#x20AC;&#x201C;VI show the results of a series of adsorption tests, and the number of stages required to reduce the heavy metals in this study to acceptable drinking water standards as set by the DWAF. Tables I and II show the adsorption of Co2+ in single and ternary systems, respectively. Eight stages of Co2+ removal were needed to meet the targeted limit of 0.5 mg/L in the effluent discharge. The effluent solution obtained after the 8th stage contained 0.04 and 0.05 mg/L Co2+ for single and ternary systems, respectively. Tables III and IV show that the adsorption of Cr3+ needed six stages to obtain the targeted limit of 0.1 mg/L. For single system and ternary system, 0.04 and 0.05 mg/L were obtained, respectively. For V3+, the effluent solution at the end of the 4th stage contained 0.01 and 0.02 mg/L for single and ternary systems, respectively (see Tables V and VI), with a target limit of 0.2 mg/L. In all cases, the adsorption capacity was slightly lower for the ternary metal ion system as compared to the single metal ion system. This may be attributed to the greater competition between the metal ions for the occupancy of the binding surfaces on the cassava waste biomass (Ndlovu et al., 2013). Generally, the biosorption efficiency increased in the order Co2+ < Cr3+ < V3+. These results are in agreement with our previous batch studies (Ndlovu et al., 2013) and column studies (Simate and Ndlovu, 2014). The differences (or variations) are attributed to the metal ionsâ&#x20AC;&#x2122; affinity towards the biosorbent (Mohan and Sreelakshmi, 2008), and this depends on the ionic radius and electropositive charges on the ions (Reddad et al., 2002).

This study showed that the adsorption efficiency obtained in the multi-stage countercurrent system is higher than that obtained in our study of the batch system, implying that there is a limited number of active binding sites on the

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adsorbent for metal adsorption in a batch system. However, in the multi-stage system, a somewhat weak solution is in contact with a biomass that has more active binding sites as it moves up the train from last stage to the first stage, hence higher recoveries were obtained.

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The required discharge limits were obtained for all metals using multi-stage countercurrent batch adsorption system with cassava peel waste biomass as biosorbent. The minimal accepted limits for Co2+, Cr3+ and V3+ discharge were reached in 8, 6, and 4 stages, respectively. Thus, in general, cassava waste biomass adsorbed the metal ions in the following order: V3+> Cr3+ > Co2+. The adsorption efficiency obtained in the multi-stage countercurrent system was higher than that achieved previously in a batch process.

+ 01 *4')4,403/ 59.84 19.81 33.10 39.02 53.78 99.35

5 55

The authors are thankful to all those who provided financial [NRF Scholarship (South Africa) and Friedel Sellschop award (University of the Witwatersrand, South Africa)] or technical support in the course of this research work. The work is part of the MSc (Eng) dissertation submitted by Ms Lizzy Seepe in 2014 to the University of the Witwatersrand, Johannesburg.

Removal of heavy metals using cassava peel waste biomass -/+*2-,4.

The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the data presented herein and do not necessarily reflect the official views or policies of any agency or institute. This paper does not constitute a standard or specification, nor is it intended for design, construction, bidding, or permit purposes. Trade names were used solely for information and not for product endorsement.

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Oâ&#x20AC;&#x2122;HAIR, S.K., 1995. Cassava. https://hort.purdue.edu/newcrop/CropFactSheets/cassava .html [Accessed November 2015].

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BHARATHI, K.S. and RAMESH, S.P.T. 2013. Fixed-bed column studies on biosorption of crystal violet from aqueous solution by Citrullus lanatus rind and Cyperus rotundus. Applied Water Science, vol. 3, no. 4. pp. 673â&#x20AC;&#x201C;687.

CASSIDY, M.B., LEE, H., and TREVORS, J.T. 1996. Environmental applications of immobilized microbial cells: A review. Journal of Industrial Microbiology, vol. 16. pp. 79â&#x20AC;&#x201C;101.

DEPARTMENT OF WATER AFFAIRS AND FORESTRY (DWAF). 2005. A drinking water quality framework for South Africa. http://www.orangesenqurak.org/UserFiles/File/OtherV2/Drinking%20Wat er%20Quality%20Framework%20for%20South%20Africa%20DWAF%202 005.pdf [Accessed May 2014].

FENG, Y., GONG, J.-L., ZENG, G.-M., NIU, Q.-Y., ZHANG, H.-Y., NIU, C.-G., DENG, J.H., and YAN, M. 2010. Adsorption of Cd (II) and Zn (II) from aqueous solutions using magnetic hydroxyapatite nanoparticles as adsorbents.

Chemical Engineering Journal, vol. 162. pp. 487â&#x20AC;&#x201C;494.

MATOUQ, M., JILDEH, N., QTAISHAT, M., HINDIYEH, M., and SYOUF, M.Q. 2015. The adsorption kinetics and modeling for heavy metals removal from wastewater by Moringa pods. Journal of Environmental Chemical Engineering, vol. 3. pp. 775â&#x20AC;&#x201C;784.

SEEPE, L. 2014. The use of cassava waste in the removal of cobalt, chromium and vanadium metal ions from synthetic effleunts. MSc (Eng) dissertation, University of the Witwatersrand, Johannesburg.

SHEN, Y., TANG, J., NIE, Z., WANG, Y., REN, Y., and ZUO, L. 2009. Preparation and application of magnetic Fe3O4 nanoparticles for wastewater purification.

Separation and Purification Technology, vol. 68. pp. 312â&#x20AC;&#x201C;319.

SIMATE, G.S., NDLOVU, S., IYUKE, S.E., and WALUBITA, L.F. 2015. Biotechnology and nanotechnology: A means for sustainable development in Africa.

Chemistry for Sustainable Development in Africa. Gurib-Fakim, A. and Eloff, J.N. (eds). Springer-Verlag, Berlin. pp. 159â&#x20AC;&#x201C;191.

SIMATE, G.S. and NDLOVU, S. 2015. The removal of heavy metals in a packed bed column using immobilized cassava peel waste biomass. Journal of Industrial and Engineering Chemistry, vol. 21. pp. 635â&#x20AC;&#x201C;643.

SONG, J., KONG, H., and JANG, J. 2011. Adsorption of heavy metal ions from aqueous solution by polyrhodanine-encapsulated magnetic nanoparticles.

Journal of Colloid and Interface Science, vol. 359. pp. 505â&#x20AC;&#x201C;511.

TSEZOS, M. 1990. Engineering aspects of metal binding by biomass. Microbial Mineral Recovery. Ehrlich, H.L. and Brierly, C.L. (sds). McGraw-Hill, New York.

VIMALA, R., CHARUMATHI, D., and DAS, N. 2011. Packed bed column studies on Cd(II) removal from industrial wastewater by macrofungus Pleurotus platypus. Desalination, vol. 275. pp. 291â&#x20AC;&#x201C;296.

VINODHINI, V. and DAS, N. 2010. Packed bed column studies on Cr (VI) removal from tannery wastewater by neem sawdust. Desalination, vol. 264. pp. 9â&#x20AC;&#x201C;14.

VOLESKY, B. 2001. Detoxification of metal-bearing effluents: biosorption for the next century. Hydrometallurgy, vol. 59. pp. 203â&#x20AC;&#x201C;216.

ZHOU, Y. 2013. XXIVth International Congress of Pure and Applied Chemistry.

Oxford, Butterworth-Heinemann.

MOHAN, S. and SREELAKSHMI, G. 2008. Fixed bed column study for heavy metal removal using phosphate treated rice husk. Journal of Hazardous Materials, vol. 153. pp. 75â&#x20AC;&#x201C;82.

ZULFADHLY, Z., MASHITAH, M.D., and BHATIA, S. 2001. Heavy metal removal in fixed bed column by the macrofungus Pycnoporus sanguineus.

Environmental Pollution, vol. 112. pp. 463â&#x20AC;&#x201C;470. â&#x2014;&#x2020;

5 555555555555555555555555555555555555555

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MEENA, A.K., MISHRA, G.K., RAI, P.K., RAJAGOPAL, C., and NAGAR, P.N. 2005.

Removal of heavy metal ions from aqueous solutions using carbon aerogel as an adsorbent. Journal of Hazardous Materials, vol. 122. pp. 161â&#x20AC;&#x201C;170.

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http://dx.doi.org/10.17159/2411-9717/2015/v115n12a2

Optimization of complex integrated water and membrane network systems

by M. Abass*, E. Buabeng-Baidoo*, D, Nezungai*, N. Mafukidze*, and T. Majozi*

Water and energy are key resources in the process and mining industries.

Increasing environmental and social pressures have made it necessary to develop processes that minimize the consumption of both these resources.

This work considers the synthesis and optimization of water networks through partial treatment of water (regeneration) before recycle/re-use.

Two types of membrane regenerators are considered, namely electrodialysis and reverse osmosis. For each of the membrane regenerators, a detailed design model is developed and incorporated into the water network model in order to minimize water and energy consumption, and operating and capital costs. This represents a rigorous design and accurate cost representation as compared to the â&#x20AC;&#x2DC;black-boxâ&#x20AC;&#x2122; approach. The presence of continuous and integer variables, as well as nonlinear constraints, renders the problem a mixed integer nonlinear programming (MINLP) problem. Four cases are presented. The first case looks at the incorporation of multiple electrodialysis regenerators with single contaminant streams within a water network (WN), while the second considers the multiple contaminant scenario. Case 3 examines the incorporation of a reverse osmosis network superstructure within a WN, and case 4 looks at both electrodialysis and reverse osmosis membranes. The developed models are applied to a pulp and paper and a petroleum case study to demonstrate their applicability, assuming both a single and multiple contaminant scenario. The model was solved in GAMS using BARON and DICOPT. The results indicate a wastewater reduction of up to 80% and savings of up to 44% in fresh water intake, 82% in energy, and 45% in the total annualized cost.

sustainable, synthesis, optimization, reverse osmosis, electrodialysis.

Water and energy are important resources for the development and wellbeing of humanity.

They are key components in both the process and the mining industry, and great amounts of each resource are consumed to produce the other. Process integration is often employed in order to establish a holistic water network superstructure for minimizing the consumption of water and energy. This is done through an integrated water network that is open for direct re-use, recycle, and regeneration re-use/recycle for sustainable, cost-effective water and energy usage.

Water pinch techniques and mathematicalbased optimization techniques are the two main approaches used for optimal synthesis of water networks in the process industries.

Wang and Smith (1994, a, b) presented the

* School of Chemical and Metallurgical Engineering, University of Witwatersrand, Johannesburg Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015.

1143

â&#x2013;˛

seminal work in water pinch analysis which sets to target the re-use, regeneration, and reuse/recycle of waste water in order to reduce fresh water consumption. That work has since developed into advanced graphical, tabular, and heuristic methods for water network synthesis. The insight-based techniques do not involve computational algorithms in generating solutions. They do, however, require significant problem simplifications and assumptions, and are inherently limited to mass-transfer-based operations (Manan et al., 2004; Bandyopadyay and Cormos, 2008; Tan et al., 2009).

Takama et al. (1980) presented a superstructure optimization approach for water minimization in a petrochemical refinery based on a fixed mass load. The work was later extended by several other researchers (Rossiter and Nath, 1995; Doyle and Smith, 1997; Huang et al., 1999; Karrupiah and Grossmann, 2006; Ahmetovic and Grossmann, 2010). Quesada and Grossmann (1995), Karrupiah and Grossmann (2006), and Faria and Bagajewicz (2011) presented algorithms to obtain feasible solution in cases of the more complex nonlinear programming (NLP) and mixed integer nonlinear programming (MINLP) problems that are in many cases a challenge to solve. Mathematical optimization allows water network synthesis problems to be treated in their full complexity by considering representative cost functions, multiple contaminants, and various topological constraints (Takama, et al., 1980; Savelski and Bagajewicz, 2000; Bagajewicz and Savelski, 2001; Grossman and Lee, 2003; Gunaratman et al., 2005). Mathematical optimization approaches also have an added advantage of

Optimization of complex integrated water and membrane network systems simulating the water network into a desired network structure and operational condition (Chew et al., 2008).

Tan et al. (2009) presented a water network superstructure with a single membrane partitioning regenerator which allows for possible re-use/recycle. The work considered the â&#x20AC;&#x2DC;black-boxâ&#x20AC;&#x2122; approach, which uses linear cost functions for the membrane regenerators. This does not give an accurate cost representation of the water network.

Khor et al. (2011) addressed this deficiency by developing a detailed model representation for water network regeneration synthesis using a MINLP optimization framework. This work of was, however, limited to a single regenerator with a fixed design. In a more recent development, Yang et al. (2014) proposed a unifying approach by combining multiple water treatment technologies capable of treating all major contaminants. The work focused on unit-specific short-cut cost functions in order to gain detailed understanding of tradeoffs between efficiency of treatment units and the cost of the units, as well as the impact on the unit design. To date, all the work on water and membrane regeneration has focused on minimizing water usage and the cost functions of the water networks. No effort has been devoted to the simultaneous synthesis of the membrane regeneration units and water network for water and energy minimization.

The membrane technologies adopted in the current work are electrodialysis (ED) and reverse osmosis (RO).

Electrodialysis is based on the electromigration of ions through cation and anion exchange permselective membranes by means of an electrical current (Korngold, 1982; Tsiakis and Papageorgiou, 2005; Strathmann, 2010). Industrial applications of ED include brackish water desalination, boiler feed and process water, and wastewater treatment (Strathmann, 2010). The current work employs insights on the mathematical relations in the work of Lee et al. (2002) and Tsiakis and Papageorgiou (2005).

RO is a pressure-driven membrane separation process that selectively allows the passage of one or more species through the membrane unit. Industrial applications of RO include municipal and industrial water and wastewater treatment. It has also gained widespread industrial usage in partitioning regenerators to enhance water quality for reuse/recycle (Garud et al., 2011). A detailed mathematical model of an RO unit that allows for process simulation and optimization has been developed by El-Halwagi (1997).

In the application of membrane systems as regenerators in water network optimization for wastewater reduction, an enormous amount of energy is used. Most published work, however, uses linear cost functions and â&#x20AC;&#x2122;black-boxâ&#x20AC;&#x2122; representation for membrane partitioning regenerators (Alva-ArgĂĄez et al., 1998; Tan et al., 2009; Khor et al., 2012). This does not result in an accurate cost representation of the membrane systems. There is thus an opportunity for energy minimization through detailed synthesis of membrane regeneration systems in order to obtain optimal variables that affect the operation and economics of the regenerator unit.

The main objective of the current work is to develop an integrated water and membrane regeneration network superstructure that incorporates possibilities for water and energy minimization. The membrane regenerators in this representation are ED and RO. The choice of regenerators is motivated by the increasing use of membrane technology for

â&#x2013;˛

1144

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water treatment in the process and mining industries, and also the potential of different membrane systems to treat specific ranges of waste. A detailed synthesis of the membrane regeneration systems is conducted to determine optimal operating conditions for efficient energy usage in terms of costs. The detailed model of the regenerators is incorporated in the overall water network objective function in order to minimize fresh water and energy consumption, and also give a true representation of costs as compared to the â&#x20AC;&#x2DC;black-boxâ&#x20AC;&#x2122; method. The idea of using variable removal ratios to describe the performance of regenerators is also explored.

97 3<2=56;6<2<:6 The main aim of this study is to develop a water network superstructure for the synthesis of a combined water and membrane network for water and energy minimization based on the following data: â&#x17E;¤ A set of water sources, J, with known flow rates and contaminant concentrations â&#x17E;¤ A set of water sinks, I, with known flow rates and known maximum allowable contaminant concentrations â&#x17E;¤ A set of membrane regeneration units, R, with the potential for parallel/series connection for partial treatment of wastewater from sources for re-use/recycle â&#x17E;¤ A fresh water source, FW, with known concentration, and variable and unlimited flow rate â&#x17E;¤ A wastewater sink, WW, with maximum allowable contaminant concentration, and variable and unlimited flow rate.

The following outputs are required: â&#x17E;¤ The minimum fresh water intake and wastewater generation, the energy consumed in the ED and RO units, and the total annualized costs for ED (TACe) and RO (TACr) â&#x17E;¤ Optimal water network configuration â&#x17E;¤ Optimum design variables of the regenerators.

*0,<956904609<=9<,9<5<:6;687: Based on the problem statement, the water network superstructure in Figure 1 is developed. The superstructure representation is an extension of the work by Khor et al.

(2011). The superstructure in this work incorporates multiple regenerators which are open for parallel and series connection as well as recycle and re-use of both permeate and reject streams from the regenerators. The fixed flow rate approach adopted in this work considers water-using processes in terms of sources and sinks that generate or consume a fixed amount of water respectively. Total fixed flow rate is adopted because it presents a general representation of water-using operations based on both mass transfer and non-mass transfer (Khor et al., 2012).

&7-<3=-< <37,2<:6=;:-=;,,384;687: This work considers four different cases, all of which are based on the superstructure given in Figure 1. â&#x17E;¤ Single contaminant, multiple ED units â&#x17E;¤ Multiple contaminants, single ED unit â&#x17E;¤ Multiple contaminants, multiple RO units

Optimization of complex integrated water and membrane network systems

!8/09<=1= = <:<9;3=.;6<9=:<6.79+=50,<956904609<=.86 =20368,3<=2<2 9;:<=9</<:<9;6795

â&#x17E;¤ Single contaminant, ED and RO units For each of the cases considered the model is applied to a case study. For comparison, different modelling scenarios are presented for each case.

can tolerate. In this regard, the corresponding contaminant balance for the regenerator feed was modelled as: [3]

This case considers the synthesis of an optimal water network with multiple ED regenerators using a single contaminant framework. The model is made up of water balances of the entire network and the mechanistic model of the regeneration network. The detailed model of the regeneration subnetwork incorporated in the network allows for the design of the subsystem.

Similarly, the water balances for the two splitters connected to the regenerator diluate and concentrate streams are given by the constraints in Equations [4] and [5] respectively.

[4]

#" $ #" # ! $ ! #"$ ! # # $

[5]

[1] The balance for the fresh water source is modelled in a similar way. Material balances on the regeneration network show the connectivity between individual regenerators and the rest of the water network. The water balance around the mixer preceding each regenerator can be modelled as: [2]

The flow balance for the sink is modelled as: [6] The balance for the wastewater sink is modelled in a similar way. The maximum allowable load that each sink tolerates has to be taken into account. As such, the corresponding contaminant balance for each sink can be modelled as: [7]

$ # " ! ! $ $ $ #" ! $" ! $

Depending on the design of the regenerator, each regenerator has a limit to the amount of contaminant that it

The model formulation for the detailed design of the ED regeneration unit is based on the work by Tsiakis and

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1145

â&#x2013;˛

To ensure connectivity between the regeneration network, the sources, and the sinks, water balances are established based on the superstructure presented in Figure 1. The flow balance for the source is modelled as:

Optimization of complex integrated water and membrane network systems Papageorgiou (1995) and Lee et al. (2002). Figure 2 is a schematic representation of a typical ED unit. For computational simplicity, one stage per regenerator is assumed.

The following assumptions are made in order to describe the plant using a set of mathematical equations describing its operation. â&#x17E;¤ The fluids considered are Newtonian and have steady, fully developed, incompressible laminar flow â&#x17E;¤ The unit is operated under a co-current set-up â&#x17E;¤ Concentrate and diluate cells have identical geometry and flow patterns and changes in the ohmic resistance of the solutions are negligible (Tsiakis and Papageorgiou, 1995) â&#x17E;¤ The concentrations of the salt species are operated using molar equivalents â&#x17E;¤ Water transportation across the membrane is negligible compared to the concentrate and diluate stream flow rates (Tsiakis and Papageorgiou, 1995) â&#x17E;¤ To avoid the collapse of the membrane system due to pressure differences it is assumed that the immediate diluate and concentrate streams have the same flow rate.

Water balances as well as corresponding contaminant balances for each regenerator were conducted in accordance with Figure 2. With regard to the design aspect of ED regenerator, important variables and physical parameters of the ED are incorporated in the mathematical relations that describe the performance of the regenerator. The electrical current required to drive the ED process is given by:

[10] where Îą is the spacer shadow factor. The required process path length for the ED stack can be expressed in terms of the membrane area, Ar, the cell width, w, and the number of cell pairs, Nr, as follows: [11] The direct energy required for the process is dependent upon the voltage and current applied on each stack. The voltage applied can be expressed as follows:

[12]

The specific energy required for desalination is defined by: [13] The specific pumping energy, Erpump, required for the process is directly linked to the pressure drop, Pr, for laminar flow across the unit and is given by: [14]

[8] where The extent of desalination obtained by an ED unit is dependent on the membrane area, Ar, which based on Tsiakis and Papageorgiou (1995), and given by: [9]

where, Cr is the concentration difference across a stage (Cfr â&#x20AC;&#x201C; Cdilr). Fpr is the diluate stream flow rate from the regenerator, r, which is expressed by Equation [10].

[15] The regeneration subnetwork involves both capital and operational costs. The representative total annualized cost (TAC) function for the regeneration network is given by Equation [16]. This function is included in the overall objective function of the water network, such that the energy consumption and subsequent cost of regeneration are minimized in conjunction with water consumption. The model is enabled to select only the necessary regenerators that result in an optimal solution by prefixing the TAC function with a binary variable, yrED , which becomes zero when the respective unit is not activated.

[16]

$! $ " $! "

!8/09<= = =*4 <2;684=9<,9<5<:6;687:=7)=;=6 ,84;3=58:/3< 56;/<=% 9</<:<9;679

â&#x2013;˛

1146

($ &%=11 =====

The objective is to minimize the total annualized cost of the water network, which comprises the fresh water cost, wastewater treatment cost, annualized regeneration cost, as well as the capital and operating cost of piping. The formulation of the objective function is expressed in Equation [17].

Optimization of complex integrated water and membrane network systems Note that within this scenario two cases were considered; that is, the case where the removal ratio of the regenerator is fixed at 0.733 and the case where it is variable. For the case where the removal ratio is fixed, an arbitrary value is chosen.

Scenario 1.3 is similar to scenario 1.2 except that it has the capability of using two regenerators. Fixed removal ratios of 0.733 and 0.950 for the first and second regenerators, respectively, are chosen for the fixed removal ratio case.

Comparisons of the presented cases show that Scenario 1.3 is the most preferable, since the largest amount of water was treated at the lowest total cost, thereby minimizing the fresh water intake and wastewater generation. It is evident from Table II that by allowing the solver to choose the optimal configuration within the regeneration subnetwork in terms of recycles, series and parallel connections, as well as making the removal ratio and number of regenerators required variable, there is the possibility of obtaining better solutions rather than fixing them arbitrarily beforehand. In this way the designer gains more control of the unit performance by being able to stipulate the required membrane characteristics to the manufacturer.

The results also show that incorporating multiple regenerators can increase the chances of a better optimal solution, as long as the regenerators are not forced into the system. In this case this situation was handled by the binary variable yrED that represented the existence of a regenerator which allowed the optimization tool to decide on the optimum number of regenerators. Figure 3 shows the optimal network configuration and flow rates for the best-case scenario. All flowrates are reported in kg/s.

With this configuration in place, the plant is capable of generating savings of up to 12.7% in fresh water intake,

[17]

where

is an annualization factor. It is assumed that all the pipes share the same p and q parameter properties, stream velocity v, and 1-norm Manhattan distance. The resulting mathematical model is a MINLP problem that was solved using GAMS/DICOPT with CPLEX as the MILP solver and CONOPT 3 as the NLP solver. BARON was used to solve the RMINLP problem.

" #" $!$ # $ The mathematical model developed is applied to a literaturebased pulp and paper plant case study (Chew et al., 2008). The industry produces a lot of ionic effluent and also involves miscible water networks, whereby the mixing streams lose their identities as they mix. This renders the fixed flow rate framework adopted in the model ideal for this particular plant (Poplewski et al., 2010). The limiting data is shown in Table I. Three scenarios are considered. Scenario 1.1 is water integration without regeneration. Scenario 1.2 considers a water network with one detailed ED regenerator with capabilities of recycle within the regeneration subnetwork.

# $!

82868:/=-;6;=)79=6 <=.;6<9=57094<5=;:-=58:+5 *7094< =

1 2 3 4 FW

*8:+5 =

!37.=9;6<= #+/ 5"

7:4<:69;687:= #+/ 2 "

!37.=9;6<= #+/ 5"

&; =47:4<:69;687:= #+/ 2 "

247.3 40.3 28.4 860.8 â&#x2C6;&#x17E;

0.000003 0.2696 0.000014 0.4998 0

1 2 3 4 WW

388.75 40.28 160.06 860.8 â&#x2C6;&#x17E;

0.034 0 0.000 370 0 0.3983

# $!

$,68202=9<50365=)79=.;6<9=:<6.79+

Fresh water intake (kg/s) Wastewater generation (kg/s) Total water regenerated (kg/s) Total cost (million $) Optimal RR* CPU time (s) *RR:-removal ratio

*4<:;987=1 !8 <-='' (;98; 3<=''

*4<:;987=1 !8 <-='' (;98; 3<=''

1134 861 0 56.9 -

1055 782 596 52.7 -

1023 750 217 50.8 r1= 0.867

1006 733 699 50.2 -

0

8

72

6129

($ &%=11 =======================================

989 716 586 48.9 r1= 0.779 r2= 0.770 17 230

1147

â&#x2013;˛

*4<:;987=1 1

Optimization of complex integrated water and membrane network systems

!8/09<= = = <=7,682;3=.;6<9=:<6.79+=47:)8/09;687:=)79=6 <= <56 4;5<=54<:;987

reduction of up to 16.2% in wastewater generation, and a 14.1% saving in the total annualized cost compared to the worst-case scenario. The optimal regenerator design suggests an installation of two regenerators, r1 and r2, one with 2880 cell pairs and the other with 4356, amounting to a total membrane area of 3837 m2 and 3921 m2 respectively. It is noteworthy that the CPU time incurred was high for scenario 1.3, due to the nature and complexity of the model.

In this case, it is necessary to develop a multicontaminant model for ED design. This requires the consideration of the ionic interaction between the different components within the ED unit, and the impact of these interactions on the unit design. In the following formulation, the subscript r is omitted from the notation because only a single regenerator is considered.

#" $ #" # ! $ The individual concentrations of the contaminants feeding into the ED unit are combined using an equivalent concentration expression, as defined in Equation [18],where subscripts c, a, and s denote the cation, anion, and salt respectively. All calculations pertaining to the ED unit were performed using an equivalent concentration. However, the subscript eq has been omitted for clarity.

[18] The calculation of equivalent concentration must be performed in all streams entering and exiting the ED unit as follows: [19]

â&#x2013;˛

1148

[21] The solution conductivity is a fundamental property of the fluid that plays an integral part in determining the ED design. It must, therefore, be determined based on the actual concentration of the contaminants that enter the unit. This can be done empirically or analytically by the use of conductivity-concentration relationships such as the Deybe-HĂźckelOnsager. The latter approach is adopted in this work. It is important to note that as the complexity of the electrolytes increases, such relationships become less accurate, and experimental determination of the dependence of solution conductivity on salt concentration is advised. The DeybeHĂźckel-Onsager equation is given by Equation [22]: [22] where Î&#x203A;° is the electrolyte conductivity at infinite dilution. This value can be obtained from the literature. The constants A and B are dependent on temperature, valence, and viscosity, and for dilute solutions at 25°C it can be assumed that A = 60.58z3 and B = 0.22293z3, where z is the valence of the salt (Wright, 2007). Once the conductivities of the individual salts are known, they are then combined to result in the solution conductivity using the mixing relationship for binary systems.

[23] In this expression, a refers to the fraction of the salt in the solution and Îş is the specific conductance of the solution or the individual components. In order to relate the specific conductance to the solution conductivity, the following relationship is employed

[20]

[24]

($ &%=11 =====

Optimization of complex integrated water and membrane network systems This expression can be applied to both the individual electrolytes and the overall solution. The combination of these three equations allows one to calculate the conductivity of a solution given the individual concentrations and their infinite conductivities.

$ " # ! $ " The following ED energy minimization model was developed for a single-stage process. The electrical current is determined using a modified form of Faradayâ&#x20AC;&#x2122;s law. This expression relates the driving force with the physical characteristics of the plant, the required capacity and the degree of desalination. Either the cationic or anionic valence and stoichiometric coefficients may be used in Equation [25].

[25] The practically applied limiting current density, beyond which the ED must not operate, is given by the empirically determined relationship: [26] Coefficients Ď&#x192; and Ď&#x2020; are experimentally determined constants, u is the fluid velocity, and Îľ is a practicality factor that relates the limiting current density to the unitâ&#x20AC;&#x2122;s flow patterns.

$ ! $ #" While many of the design constraints are similar to the single contaminant case as described above, some modifications must be made to incorporate the equivalent concentrations for the multicontaminant case. The total length of the ED stack is given by the following relationship:

$ " $! " The water network and ED model culminate in an overall cost function to be minimized, given by Equation [30]. All pipes are assumed to operate at the same fluid velocity, up, and use the same costing coefficients p and q. The piping cost is calculated as a function of the Manhattan distance, D, between any two units.

[30]

" #" $!$ # $ The above model is applied to a pulp mill and bleached paper plant adapted from Chew et al. (2008). In the original scenario, shown in Figure 4, four separate fresh water feeds are used, with a total consumption of 8500 t/d, and four separate effluent streams are produced, totalling 10 500 t/d.

Two contaminants were identified, namely NaCl and MgCl2. The flow rates and contaminant concentrations of the sources and sinks are detailed in Table III. Two process integration scenarios were compared. In both cases, the model was solved using GAMS/BARON. â&#x17E;¤ Scenario 2.1: a â&#x20AC;&#x2DC;black-boxâ&#x20AC;&#x2122; model is used and the costing of the actual required ED unit is performed separately, i.e. water minimization only â&#x17E;¤ Scenario 2.2: simultaneous minimization of water and energy, using the developed model. Input data for the ED units was kept constant for comparison between the two scenarios.

#"$ ! #" [27]

The conductivity, Î&#x203A;, is determined using the constraints in Equations [22]â&#x20AC;&#x201C;[24]. The corresponding required membrane area is determined as a function of the path length and the cell width. A correction factor, β, is introduced to account for the effect of the spacers.

[28]

$ ! $ #" The energy consumption in an ED unit can be attributed to the migration of electrons across the membranes as well as the energy required to pump fluids through the unit.

Assuming that operation is ohmic, i.e. current density does not exceed limiting current density, the voltage across the unit is given by:

In this scenario, the objective is water minimization. The water regeneration is represented only by a constant removal ratio and a linear cost expression. The actual ED cost is determined based solely on the throughput. The results from the WNS are then input to a standalone ED model in order to determine the true cost of regeneration under these conditions.

A full range of results is given in Table IV. Simple water minimization results in a 36% saving in fresh water and 60% reduction in wastewater generated, compared to the original plant. A comparison between the estimated and true costs of regeneration highlights the inaccuracies involved when a linear cost function is applied to a nonlinear membrane process. The linear cost function considers only the flow rate of feed to the ED; the true cost is determined by all aspects of the units design. Table IV shows that there is an 85% discrepancy between the â&#x20AC;&#x2DC;black-boxâ&#x20AC;&#x2122; estimate of regeneration cost and the cost of the actual required ED unit under the same conditions. The â&#x20AC;&#x2DC;black-boxâ&#x20AC;&#x2122; approach presents the risk of misrepresenting the water network, resulting in suboptimal solutions.

#"$ !# !$ $ ! #" [29]

($ &%=11 =======================================

1149

â&#x2013;˛

The specific energy for desalination and pumping energy are subsequently calculated using Equations [13] and [14].

In the water and energy minimization case, the entire model, including the detailed ED, was used, with the same inputs as in the first scenario. The final plant configuration is shown in Figure 5.

Optimization of complex integrated water and membrane network systems

!8/09<= = =*82,38)8<-=,974<55=)37.=-8;/9;2=7)=,03,=2833=;:-= 3<;4 <-=,;,<9=,3;:6=#)37.=9;6<5=5 7.:=8:=42 5"

# $!

8 <:=-;6;=)79=.;6<9=:<6.79+ *7094<5

*7094< Stripper 1 Screening Stripper 2 Bleaching Fresh water

!37.=9;6<=#42 5" 2.07 0.34 0.24 7.22 Variable

*8:+5 7:6;28:;:6=47:4<:69;687:= #+273 42 " ; 3 &/ 3 0 0.046 0 0.026 -

0 0.035 0 0.0002 -

&; 8202=47:6;28:;:6=47:4<:69;687:= #+273 42 " !37.=9;6<=#42 5" ; 3 &/ 3

*8:+= Washer Screening Washer/filter Bleaching Wastewater

3.26 0.34 1.34 7.22 Variable

0.0046 0.0125 0 0.0002 0.01

0.0004 0.0007 0 0.00003 0.01

# $!

*022;9 =7)=9<50365=)79=54<:;9875=1=;:-=

;5<=4;5< $98/8:;3 Fresh water Wastewater Regeneration cost (energy) Piping Total cost * Costs are given in $1000/annum

â&#x2013;˛

1150

*4<:;987=1= ;6<9=28:828 ;687: %5682;6<-=% =4756 90<=% =4756

2 814.86 3 468.12 6 282.98

($ &%=11 =====

1 776.00 1 122.80 3.90 92.40 2 995.10

1 776.00 1 122.80 26.08 92.40 3 017.28

*4<:;987= ;6<9=;:-=<:<9/ = 28:828 ;687: 1 736.70 1 083.50 5.25 86.62 2 912.07

Optimization of complex integrated water and membrane network systems

!8/09<= = = 03,=;:-=,;,<9=,3;:6=)7337.8:/=.;6<9=;:-=<:<9/ =28:828 ;687: =5 7.8:/=:<.=49755 ,3;:6=,8,8:/=47::<4687:5=#)37.=9;6<5=5 7.:=8:=42 5"

# $!

72,;9857:= <6.<<:=+< =-<58/:=4 ;9;46<9856845=7) 6 <=% =0:86=8:=54<:;9875=1=;:-=

Area Number of cell pairs Desalination energy Pumping energy Total cost

:86

*4<:;987=1

*4<:;987=

m2

438 353 105 494 912.3 26 083

144 229 18 476 18.32 5 216

kWh/a kWh/a $/annum

This case work proposes a superstructure optimization for the synthesis of a detailed RON within a WNS. A rigorous nonlinear RON superstructure model, which is based on the state space approach by El-Halwagi (1992), is included in the WNS to determine the optimum number of RO units, pumps, and turbines required for an optimal WNS. A fixed flow rate model that considers the concept of sources and sinks is adopted. The model takes into account streams with multiple contaminants. The idea of using a variable removal ratio to describe the performance of the regenerators is also explored in this case. The water balances are similar to those proposed in case 1.

#" $ #" # ! $ $ $ $! ! " # " The characteristics of the RO membrane need to be described in order to relate flow rate to pressure. The pressure drop across the membrane Î&#x201D;Pr is given in Equation [31] (Khor et al., 2011). The equation was simplified by assuming a linearshell side concentration and pressure profiles (El-Halwagi, 1997).

[31] The osmotic pressure, r , is defined as a function of the contaminant concentration on the feed side (Saif, Elkamel, and Pritzker, 2008a) and is shown in Equation [32].

[32]

($ &%=11 =======================================

1151

â&#x2013;˛

A comparison between the ED units from scenarios 1 and 2 shows that when the optimization of the ED is embedded into the water network the required unit has a more conservative design and therefore consumes less energy. Table V shows key variables determined in the optimization, highlighting the comparison between the two scenarios. The integrated approach, therefore, results in an 80% reduction in the overall cost of the ED unit required.

Key characteristics of the models are presented and compared in Table V. While the model sizes are similar, the time taken to solve the integrated model (scenario 2) was close to 21 hours, while the â&#x20AC;&#x2DC;black-boxâ&#x20AC;&#x2122; (scenario 1) required only 2 minutes. This can be attributed to the nonlinearity of the ED model combined with the already nonconvex WNS model. It is necessary, therefore, to further develop the model to reduce its computational complexity, which will constitute future work.

Optimization of complex integrated water and membrane network systems The permeate flow rate per module is given in Equation [33].

[33] av on the feed side is given The average concentration Cq,m

by Equation [34].

[34] The concentration of contaminants on the feed side must also be described in terms of the pressure drop and the osmotic pressure. This is described in Equation [35].

â&#x17E;¤ Treatment cost of wastewater (WW) â&#x17E;¤ Capital and operation costs of the piping interconnection.

The total annualized cost of the RON consists of the capital cost of the RO modules, pumps, and energy recovery turbines, operating cost of pumps and turbines, as well as pretreatment of chemicals. The operating revenue of the energy recovery turbine is also considered in the determination of the TAC and is shown in Equation [38]. The set n represents the mixing node before a regenerator unit and is used to connect the water network to the RON superstructure.

[35] [38]

A mass and concentration balance around the regenerator is also needed and is described in Equations [36] and [37] respectively.

[36]

[37]

$ " $! "

The piping cost of components is formulated by assuming a linear fixed-charge model. In the formulation, a particular cost of a pipe is incurred if the particular flow rate through the pipe falls below the threshold value. This is achieved by using 0-1 variables. Equation [39] represents the objective function of the total regeneration network.

The objective function of the combined RON superstructure and WNS is used to minimize the overall cost of the regeneration network on an annualized basis which consists of: â&#x17E;¤ TAC of the RON â&#x17E;¤ Cost of fresh water (FW)

[39]

# $!

82868:/=-;6;=)79=.;6<9=:<6.79+

!37.=9;6<

(kg/s) 7.3 10.65 3.5

1 2 3 FW

*7094<5 =8 7:6;28:;:6=47:4<:69;687:=#+/ 2 "

TDS 3.5 4 1 2

COD 3.5 4 3 1

1 2 3 WW

!37.=9;6<

(kg/s) 0.83 40 5.56

*8:+5 = &; =47:6;28:;:6=47:4<:69;687:= #+/ 2 " TDS 2.5 2 2.5 25

COD 2.5 2 2.5 25

# $!

*022;9 =7)=9<50365=)79=4;5<=1=;:-=

Fresh water flow rate (kg/s) Wastewater flow rate (kg/s) Cost of regeneration ($ million/year) Total cost ($ million/year) Network configuration Number of HFRO modules CPU time (h)

â&#x2013;˛

1152

!8 <-=''=#54<:;987= 1"

(;98; 3<=''=#54<:;987= "

28.87 3.91 0.23 1.32 Parallel 37 for each regenerator 6

27.68 2.72 0.096 1.11 Parallel 15 for each regenerator 54

($ &%=11 =====

Optimization of complex integrated water and membrane network systems

!8/09<= = = <6.79+=7 6;8:<-=)79=54<:;987=1 =#20368,3<=9</<:<9;6795=.86 = ;98; 3<=9<27 ;3=9;687"

" #" $!$ # $ The above model was applied to a petroleum refinery case study based on the work presented by Khor et al. (2011).

The model was implemented in GAMS 24.2 using the general purpose global optimization solver BARON, which obtains a solution by using a branch-and-reduce algorithm. The network consists of four sources and four sinks. The limiting water data for the sources and sinks is given in Table VI. Table VII shows the comparison between a case where multiple regenerators with fixed (scenario 3.1) and variable removal ratio (scenario 3.2) were used. The removal ratio chosen by the model in scenario 3.2 was 0.97 for all contaminants instead the fixed value of 0.95 in scenario 3.1.

Scenario 3.2 led to 3.12% reduction in fresh water and 30.43% reduction in wastewater generation in comparison with scenario 3.1. A 15.91% reduction in the total network cost was also achieved. The large decrease in the total cost of the network in scenario 3.2 can be attributed to the higher removal ratio selected by the model than the value that was initially predicted. The modelling of scenario 3.2 is, however, computationally expensive as can be seen in Table VII. Figure 6 shows the water network for scenario 3.2 with the corresponding flow rate for each stream. The best case used 15 HFRO modules per regenerator. The model selected two regenerators, two pumps, and two energy recovery turbines, as can be seen in Figure 6. It can also be seen that a parallel configuration of the network was chosen by the

model. In comparison with the case where no regeneration was considered, scenario 3.2 leads to a 28% reduction in fresh water consumption and 80% reduction in wastewater generation.

The long computational time for solving the model in scenario 3.2 was due to the complexity of the problem as well as the large number of 0-1 variables. The model solves quicker when tighter bounds are imposed on the feed and retentate pressure. The use of the energy recovery turbines in the RON led to a reduction in the regeneration cost of the network, and as a result, a reduction in energy usage by the system was achieved.

In this case, an integrated water network of ED and RO unit is developed with the possibilities of water and energy minimization. The choice of regenerators is motivated by the increasing demand for and use of membrane technology for water treatment and also the varying potential of different membrane systems to treat specific waste ranges.

#" $ #" # ! $ The model formulation in this representation included constraints for mass and concentration balances of the ED and RO units in cases 1 and 2, detailed formulation of the ED and RO unit respectively, and the overall total annualized costs of both regeneration units represented in cases 1 and 2, which is incorporated in the objective function as follows. ($ &%=11 =======================================

1153

â&#x2013;˛

The overall model results in a nonconvex MINLP due to the bilinear terms as well as the power function in the constraints.

Optimization of complex integrated water and membrane network systems # $!

;584=-;6;=)79=.;6<9=57094<5=;:-=58:+5 *7094<5 =

1 2 3 4 FW

*8:+5 =

!37.=9;6<=#+/ 5"

7:4<:69;687:= #+/ 2 "

!37.=9;6<=#+/ 5"

&; =47:4<:69;687:= #+/ 2 "

2.07 0.34 0.024 7.22

0.0002 0.0051 0 0.0083 0

1 2 3 4 WW

3.26 0.34 1.34 7.22

0.00057 0 6.16x10-6 0 0.01

# $!

Optimal results of water network based on the case study

*4<:;987=1

Fresh water use (kg/s) % of freshwater savings Wastewater generated (kg/s) % of wastewater saved Total cost of water network ($) CPU time

*4<:;987=

18.300 39.1 15.785 1.170Ă&#x2014;106 0.06

*4<:;987=

!8 <-=''

(;98; 3<=''

!8 <-=''

(;98; 3<=''

11.145 45.3 8.958 43.2 5.97Ă&#x2014;105 865

10.012 38.89 7.796 50.6 5.08Ă&#x2014;105 2764.20

11.183 44.32 8.996 43.01 6.26Ă&#x2014;105 687.50

10.189

$ " $! " Equation [40] represents the objective function that minimizes the overall annualized cost of the water network.

This includes fresh water cost, wastewater treatment cost, and annualized regeneration cost, as well as capital and operating costs of piping interconnections. The costs related to piping are accounted for by specifying an approximate length of pipe, the material of construction, and linear velocities through the pipes.

[40]

7.742 50.95 5.66Ă&#x2014;105 16709.78

industry. Moreover, the pulp and paper industry involves miscible phase networks that consist of water-water systems where streams lose their identities through the mixing process, hence the case study is suitable for a fixed flow rate method adopted for this work.

Table VIII shows the basic data for the plant water network, which comprises five water sources, including the fresh water source, and five water sinks, including the waste sink.

The case study was applied to three different model cases in order to ascertain the benefits of incorporating a detailed network of the membrane regeneration units in the constraints of the water network.

# $!

A 1-norm Manhattan distance is considered for all piping interconnections. All pipes are assumed to be of the same material of construction; as a result, the carbon steel pipe parameters of p and q are adopted for the piping costs. Af is the annualization factor adopted from Chew et al. (2008) which is used to annualize the piping cost. The resulting mathematical model is a MINLP. The nonlinear terms are due to the presence of bilinear terms in mass balance equations and power terms in the cost functions of regeneration units.

The MINLP model was solved using GAMS 24.2, using the general-purpose global optimization solver BARON.

" #" $!$ # $ The developed mathematical model is verified and applied to the pulp and paper case study adopted from Chew et al.

(2008). The choice of the case study is motivated by the high amount of ionic components produce by the pulp and paper

â&#x2013;˛

1154

($ &%=11 =====

$,682;3=-<58/:=9<50365=)79=% =;:-='$=0:86=8: 54<:;987= (;98; 3<

(;30<

Nr Ar (m2) Lr (m) Ir (A) vr (m/s) Ur (V) spec Er (J/s) pump Er (J/s) Î&#x201D;P (kPa) f Fr (kg/s) RRr s Nr f Pr (kPa) q Pr (kPa) Î&#x201D; r (kPa) f Fr (kg/s)

50 54.375 0.821 12.447 0.01 30.152 0.021 0.004 16.303 1.025 0.8 10 5.73Ă&#x2014;105 5.33Ă&#x2014;105 1.63 0.72

Optimization of complex integrated water and membrane network systems

!8/09<= = =$,68202=.;6<9=:<6.79+=47:)8/09;687:5=)79=54<:;987= =#(;98; 3<=''"

â&#x17E;¤ Scenario 4.1 considered a model of the water network without regeneration â&#x17E;¤ Scenario 4.2 considered a model of water network with regeneration units based on the â&#x20AC;&#x2122;black-boxâ&#x20AC;&#x2122; approach â&#x17E;¤ Scenario 4.3 considered a detailed synthesis of the regeneration units incorporated into the overall water network objective function.

For scenarios 4.2 and 4.3, the optimization was conducted for both a fixed and a variable removal ratio. For comparison, in both scenarios the removal ratio had a fixed value of 0.7.

The optimal results for all scenarios are presented in Table IX. Scenario 4.1 represents the water network model without regeneration. Scenario 4.2 represents the â&#x20AC;&#x2122;black-boxâ&#x20AC;&#x2122; formulation with both fixed and variable removal ratios. The results showed a reduction in fresh water consumption, wastewater generation, as well as the total annualized water network cost as compared to the non-regeneration scenario.

The results of scenario 4.3 are displayed in Figure 7. For both fixed and variable removal ratios scenario 4.3 showed significant reduction in water network cost as well as fresh water consumption and wastewater reduction as compared to the direct water network model without regeneration.

However, there was an increase in the total water network cost of scenario 4.3 for both the fixed and the variable removal ratios cases compared to scenario 4.2. This is a result of scenario 4.3 being a true representation of the total water network, as it incorporates a detailed design of the membrane regeneration units and gives an accurate expression of the regeneration cost compared to the linear cost function of scenario 4.2, which uses the â&#x20AC;&#x2122;black-boxâ&#x20AC;&#x2122; method.

From the results in Table IX it is evident that the variable removal ratio in case 3 presents the optimal configuration, since the model is allowed to choose the performance parameters of the membrane regenerators. The results also

show that incorporating multiple membrane regenerators with different performance and inlet and outlet contaminant limits in a water network can lead to an optimal use of fresh water. The inlet contaminant limits were set at different levels in order to allow the membrane regenerators various options for contaminant treatment. The variable removal ratio model in scenario 4.3 proves to be the optimal results for the case study as represented in Figure 7. The configuration showed that regeneration re-use and recycle within the water network between the regenerators resulted in a 44.3% reduction in fresh water consumption, 50.9% reduction in wastewater generation, and 45% savings in the total annualized water network cost as compared to case 1. Table X shows the design results of the ED and RO units respectively.

($ &%=11 =======================================

7:430587:

1155

â&#x2013;˛

This work addresses the synthesis of a multi-membrane regeneration water network by proposing a water network model that incorporates detailed models of ED and RO regenerators. Different cases were considered under which the respective MINLP models were developed, and for each case a relevant literature case study was applied to demonstrate the applicability of the proposed model. Overall, the results showed that the use of a detailed model guarantees more accurate and reliable results in terms of water network synthesis as well as regenerator design.

Savings of up to 44% in fresh water intake and reductions of up to 80% in wastewater generation and 45% in the total annualized cost were obtained. Additionally, because a detailed regenerator model presents an expression of the regeneration cost, it also gives optimal regenerator operating variables for minimal energy usage, thereby illustrating the inadequacy of the â&#x20AC;&#x2DC;black-boxâ&#x20AC;&#x2122; approach to superstructure optimization. Energy savings up to 82% were achieved. The results also showed an added advantage in setting the

Optimization of complex integrated water and membrane network systems regenerator removal ratio as compared to fixing it arbitrarily.

It is noteworthy that although the proposed models cater only for ED and RO regeneration technologies, they offer scope for future work, and the problem can be extended to incorporate other membrane technologies such as ultrafiltration, microfiltration, and nanofiltration.

72<:43;609<

{j|j=water source} {i|i=water sink} {m|m=contaminants} {r|r=regeneration units}

Dj,is d Dr,i y Dr,r' k Dj,r da Dj,n Prm PrP Îź A Af aLCD bLCD Cchem Celec CFW Cmod Cpump Ctur CWW F kel km kmb ktr LRr m n OS

p q Sm td v w z ι β δ ξ Μ Ρ

Manhattan distance between source j and sink i Manhattan distance between regenerator r and sink, i Manhattan distance between regenerators r and râ&#x20AC;&#x2122; Manhattan distance between source j and regenerator r Manhattan distance between source j and node n Shell side pressure drop per module Pressure of a permeate stream from regenerator r Solution viscosity Water permeability coefficient Annualization factor LCD constant LCD constant Cost parameter for chemicals Cost of electricity Fresh water cost Cost per module of HFRO membrane Cost coefficient for pump Cost coefficient for turbine Wastewater treatment cost Faraday constant Cost of electricity Solute permeability constant Cost of membrane Conversion factor Liquid recovery for regenerator r Interest rate per year Maximum equipment life Proportionality constant between the osmotic pressure and average salt mass fraction on the feed side Parameter for carbon steel piping Parameter for carbon steel piping Membrane area per module Operating time per year Pipe linear velocity Cell width Valence Spacer shadow factor Volume factor Cell thickness Safety factor Current utilization Pumping efficiency

â&#x2013;˛

1156

Pump efficiency Turbine efficiency Equivalent conductance Infinite conductivity Total membrane resistance Limiting current density constants Dimensionless constant

J I M R

Ρpump Ρtur Îť Î&#x203A;° Ď Ď&#x192;,Ď&#x2020; Ď&#x2019;

($ &%=11 =====

TACr Ar Erspec Erpump Ir Lr vr Ur Pr Frf Frdil Frp Frw Frcr Frr Frcon d Fr,i c Fr,i Fj k Fj,r s Fj,i x Fr,r' y Fr,r' b Fi Crf Crwf Crcr Crw Crdil Crcon SrU Cj CiU da Fj,n pe Fr,i q Fr,j

Fna Pna Pni Pno Prq av Cr,m f Cr,m

Total annualized cost for regenerator r Membrane area required by regenerator r Specific desalination energy required by regenerator r Specific pumping energy required by regenerator r Electrical current required by regenerator r Stack length Linear flow velocity at stage s Voltage applied Pressure drop across the regenerator Regenerator feed flow rate Final diluate stream flow rate of regenerator r Diluate stream flow rate for regenerator r Concentrate stream flow rate for regenerator r Concentrate stream recycle flow rate for regenerator r Recycle stream flow rate for regenerator r Final concentrate flow rate for regenerator r Diluate flowrate to sink i Concentrate flow rate to sink i Source flow rate Flow rate from source j to regenerator r Flow rate from source j to sink i Recycle from diluate stream to regenerator feed Recycle from concentrate stream to regenerator feed Sink i flow rate requirements Regeneration feed concentration for regenerator r Concentration of feed concentrate stream for regenerator r Concentration of recycling concentrate for regenerator r Concentration of concentrate waste stream for regenerator, r Diluate contaminant concentration Concentrate contaminant concentration Maximum allowable regenerator concentration Source concentration of Maximum allowable sink concentration Allocated flow rate between sources j and node n Flow rate of the permeate stream from regenerators r to sinks i Flow rate of the retentate stream from regenerators r to sinks i Flow rate of streams from re node n Pressure of streams leaving node n Pressure of an inlet stream to an energy recovery turbine from node n Pressure of an outlet stream from an energy recovery turbine from node n Pressure of a retentate stream from regenerator r Average concentration of contaminant m in the highpressure side of regenerator Concentration of contaminant m in the feed to the

Optimization of complex integrated water and membrane network systems pe Cr,m

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regenerator r Concentration of contaminant m in permeate stream leaving regenerator r Flow rate of permeate/diluate stream leaving the regenerator r Flow rate of retentate stream leaving the regenerator r Concentration of contaminant m in retentate stream leaving regenerator r Feed pressure into regenerator r Equivalent concentration Fresh water flow rate Practical limiting current density Removal ratio for regenerator r Waste water flow rate Pressure drop over regenerator r Osmotic pressure on the retentate side of regenerator r Specific conductance Equivalent conductivity

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4+:7.3<-/<2<:6 The authors would like to thank the National Research Foundation (NRF) for funding this work under the NRF/DST Chair in Sustainable Process Engineering at the University of the Witwatersrand, South Africa.

'<)<9<:4<5 AHMETOVIC, E. and GROSSMANN, I.E. 2010. Strategies for global optimization of integrated process water networks. 20th European Symposium on Computer Aided Process Engineering â&#x20AC;&#x201C; ESCAPE20. Pierucci, S. and Buzzi Ferraris, G. (eds). Elsevier.

ALVA-ARGĂ EZ, A., KOKOSSIS, A., and SMITH, R. 1998. Wastewater minimization of industrial systems using an integrated approach. Computers and Chemical Engineering, vol. 22. pp. 741â&#x20AC;&#x201C;744.

BAGAJEWICZ, M. and SAVELSKI, M. 2001. On the use of linear models for the design of water utilization systems in process plants with a single contaminant. Waste Management, vol. 79. pp. 600â&#x20AC;&#x201C;610.

BANDYOPADHYAY, S. and CORMOS, C.-C. 2008. Water management in process industries incorporating regeneration and recycle through a single unit.

Industrial and Engineering Chemical Research, vol. 47. pp. 1111â&#x20AC;&#x201C;1119.

CHEW, I.M.L., TAN, R., NG, D.K.S., FOO, D.C.Y., MAJOZI, T., and GOUWS, J. 2008.

Synthesis of direct and indirect and interplant water and network.

Industrial and Engineering Chemical Research, vol. 47. pp. 9485â&#x20AC;&#x201C;9495.

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DOYLE, S.J. and SMITH, R. 1997. Targeting water reuse with multiple contaminants. Process Safety and Environmental Protection, vol. 75, no. 3. pp. 181â&#x20AC;&#x201C;189.

Optimization of complex integrated water and membrane network systems EL-HALWAGI, M. 1997. Pollution Prevention through Process Integration.

Academic Press, San Diego.

ROSSITER, A.P. and NATH, R. 1995. Wastewater Minimization using Nonlinear Programming. McGraw-Hill.

SALVESKI, M. and BAGAJEWICZ, M. 2000. On the optimality conditions of water utilization systems in process plants with single contaminants. Chemical Engineering Science, vol. 55. pp. 5035â&#x20AC;&#x201C;5048.

STRATHMANN, H. 2010. Electrodialysis, a mature technology with a multitude of new applications. Desalination, vol. 264. pp. 268â&#x20AC;&#x201C;288.

TAKAMA, N., KURIYAMA, T., SHIROKO, K., and UMEDA, T. 1980. Optimal planning of water allocation in industry. Computers and Chemical Engineering, vol. 4, no. 80. pp. 251â&#x20AC;&#x201C;258.

TAN, R.R., NG, D.K.S., FOO, D.C.Y., and AVISO, K.B. 2009. A superstructure model for the synthesis of single-contaminant water networks with partitioning regenerators. Process Safety and Environmental Protection, vol. 87, no. 9. pp. 197â&#x20AC;&#x201C;205.

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($ &%=11 =====

TAWARMALANI, M. and SAHINIDIS, N.V. 2005. A polyhedral branch-and-cut approach to global optimization. Mathematical Programming, vol. 103, no. 2. pp. 225â&#x20AC;&#x201C;249.

TSIAKIS, P. and PAPAGEORGIOU, L.G. 2005. Optimal design of an electrodialysis brackish water desalination plant. Desalination and the Environment, vol.

173, no. 2. pp. 173â&#x20AC;&#x201C;186.

YANG, L., SALCEDO-DIAZ, R., and GROSSMANN. E.I. 2014. Water network optimization with wastewater regeneration models. Industrial and Engineering Chemistry Research, vol. 53. pp. 17680â&#x20AC;&#x201C;17695.

WANG, Y.P. and SMITH, R. 1994a. Wastewater minimization. Chemical Engineering Science, vol. 49, no. 94. pp. 981â&#x20AC;&#x201C;1006.

WANG, Y.P. and SMITH, R. 1994b. Design of distributed effluent treatment systems. Chemical Engineering Science, vol. 49, no. 94. pp. 3127â&#x20AC;&#x201C;3145.

WRIGHT, M.R. 2007. An Introduction to Aqueous Electrolyte Solutions. Wiley, Chichester, UK. â&#x2014;&#x2020;

http://dx.doi.org/10.17159/2411-9717/2015/v115n12a3

The impact of coal quality on the efficiency of a spreader stoker boiler

by R.L. Taole*, R.M.S. Falcon*, and S.O. Bada*

This research establishes the combustion characteristics and efficiencies of South African coals of different qualities and their impact on the performance of a grate spreader stoker boiler. Four different coal samples were tested in the particle size range 6.25 Ă&#x2014; 25 mm. A detailed investigation involving the boiler operating conditions associated with the physicochemical characteristics of the coals, petrographic properties, and temperature profiles from a thermal camera was conducted. The thermal analysis indicates that there is a strong correlation between thermographic data (combustion behaviour and maximum flame temperatures) and petrographic composition of the coals. This association is not reflected in calorific values and proximate analyses of the coals. In terms of combustion efficiencies, all coals yielded relatively high amounts of unburnt carbon in the fly ash (about 36.90%). The highest steam output obtained was 41.76 t/h at the highest combustion efficiency of 79.13%.

The thermographic results obtained from this study led to the conclusion that South African low-grade Gondwana coals undergo delayed ignition and burn at unusually high temperatures (1500â&#x20AC;&#x201C;1800°C), which is in contrast to the original belief that the combustion temperature is around 1400°C. 6" 43%/ coal, combustion, macerals, thermographic camera, travelling grate.

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There are about 6000 industrial-scale boilers in South African industries today, all using lower grade coals than they were initially designed for (Johns and Harris, 2009). The travelling grate spreader stoker boiler is one of the oldest combustion technologies that have been in use since the beginning of the twentieth century (Giaier and Loviska, 1997).

However, these traditional coal-fired boilers are still widely used for electricity generation in South African industries. The pulp and paper, sugar, cement, and many other industries use steam to generate power, consuming approximately 9 Mt of coal per annum (SANEDI, 2013). Numerous investigations have also been conducted on the competitiveness of using existing convectional coal-fired utilities, such as grate stoker boilers, in firing and co-firing a wide range of fuels (Li, et al., 2009; Thai, et al., 2011; Sheng et al., 2012). Despite having been in the market for many years, coal-fired spreader stoker technology still presents challenges in regard

* School of Chemical and Metallurgical Engineering, Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015 and revised paper received Nov. 2015

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to inefficient combustion of coal (Lin et al., 2009). This has always been regarded as a technical operational problem, rather than being due to the inherent characteristics of coal. This investigation is aimed at the study of feed coals utilized in a specific boiler and the effects of their properties on the efficiency of combustion.

Most of the previous research in the field of industrial stoker-fired boilers, including spreader stokers, has been undertaken in Europe and America (Falcon, 2010).The results of these studies reside with boiler manufacturers, who rarely publish their findings. The only published results that can be found locally using South African coal (SAC) are limited to investigations conducted mostly by the sugar, pulp, and paper industries (Falcon, 2010). These studies focus mainly on the effect of operating conditions on boiler performance, and not specifically on the impact of coal quality. There is thus little or no knowledge on the compatibility of SACs and stoker fired boilers in this country. There is virtually no published information which clearly draws the relationship between coal quality, technical operational conditions, and the efficiency of spreader stoker boilers for SACs. In addition, the characteristics of coals should also be well understood if retrofitting of the existing boilers is to be successful (Falcon and Ham, 1988). It is important that this standpoint be fully embraced, especially in the South African context because the majority of the old boilers were designed by overseas manufacturers (mostly American and British), using their own types of coal and hardly any local coals (Falcon, 2010). This implies that original designs of most of the old boilers did not necessarily match SAC types.

The impact of coal quality on the efficiency of a spreader stoker boiler This paper attempts to refine the current understanding of the effect of varying coal qualities and operating conditions on boiler efficiency in one particular travelling grate spreader stoker boiler. The study focuses on the combustion characteristics of four different coal samples and their impact on boiler efficiency. An advanced thermographic visual testing system in the boiler is used to interpret the results, together with petrographic techniques and conventional physical and chemical analyses (proximate and ultimate analyses).

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Four coal samples, identified as A, B, C, and D, of similar calorific value and different abrasive indexes, were used in this study. The coals were sourced from separate mines in the Witbank area of South Africa, except for coals A and D which were both from the same mine. The coals were crushed to the standard designed size specified for a spreader stoker boiler at 6.25 Ă&#x2014; 25 mm. The coal samples were sampled in accordance with ISO 18283:2006 (E) guidelines in order to obtain the most representative coal fed into the boiler furnace. The particle size distributions (PSDs), Hardgrove indexes (ASTM D3402), and abrasive indexes (Eskom standard) of the samples are presented in Table I. The design coal specification for the spreader stoker boilers utilized in this study is 6.25 Ă&#x2014; 25 mm size fraction. The PSDs (Table I) below indicates that coal D has the lowest proportion of finer particles at 16.47% <6.25 mm, while coal A contained the highest amount of finer particles at 29.62% <6.25 mm.

Proximate analysis was conducted to determine the total moisture (ISO 589: 2008); inherent moisture (SABS 925:1978); volatile matter (ISO 562: 1998); ash content (ISO 1171: 1997); and fixed carbon (by difference). The ultimate analysis (ASTM D 5373), along with the calorific value, which is the measure of the heat content, was determined in accordance with ASTM D5865-04. The total sulphur (ASTM D4239:1997) and species of sulphur (ISO 157) were also determined. Both the bottom ash and fly-ash samples were analysed for unburnt carbon (UBC) using the standard ASTM D4239:199 to determine the total carbon concentration. Ash fusion temperature (AFT) was determined for all samples in accordance to ISO 540, and the results are shown in Table II.

Leica DM4500P petrographic microscope was used for the optical determination of the organic, inorganic, and associated components by analysing the microlithotypes, including the carbominerites and minorities analyses. The rank, as indicated by the mean random reflectance, Rr%, is of the order of 0.61 to 0.76%, as seen in Table III. In terms of rank, all coals are of the bituminous C category, with coals A and D slightly lower in maturity. The flue gas was analysed using an Orsat apparatus. The gases measured were carbon dioxide (CO2), carbon monoxide (CO), and oxygen (O2). The concentration of other gases, such as NOx and SOx, in the flue gas was analysed using a gas chromatograph in the laboratory after capturing the flue gas in a gas pipette and Tedlar bags.

The thermographic furnace camera is the main analytical tool in this study. The technique uses infrared radiation to acquire and analyse thermal information using a non-contact thermal imaging device. This provides the capability to differentiate between the thermal characteristics of different coal samples during combustion. The furnace temperature profiles and the sample flame morphology were studied to understand the thermal behaviour of the samples according to different colours emitted during combustion. The video (DURAG type D-VTA 100-10 series) and thermography system utilized allows for the analysis of the furnace conditions and the visualization of the flame temperature profiles during coal combustion in real time. In addition, the camera provides for temperature determinations at individual points; such as thermal analysis of local temperature distribution, classification of temperature-definable measuring windows and lines, referred to as regions of interest (ROIs). The thermographic camera D-VTA100-10 has the following technical output: Optical field of view 72° horizontal, 54° vertical, and 90° diagonal Thermography from a total radiation range: 1000â&#x20AC;&#x201C;1800°C Cooling water volume 350 l/h Compressed air volume max. 25 Nm3/h.

The location of the thermal camera field of view with reference to the boiler furnace is depicted in Figure 1. The figure illustrates a typical arrangement of the thermographic system for data capturing in the boiler furnace and conveyance to a programmable logic controller (PLC) system

The coals were prepared according to ISO 7404/2 (1998). A

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The impact of coal quality on the efficiency of a spreader stoker boiler

The water-tube spreader stoker boiler used in this investigation has a heating surface area of 169.5 m2, mean height of 9.98 m, width of 4 m, effective length of 4.8 m, a grate area of about 19.3 m, and sample feed rate capacity of about 42.43 t/h. The boiler has a steam generation capacity of 45 t/h, producing saturated steam at 31 bar gauge (barg) pressure. The boiler consists of a negative pressure furnace house, an economizer, and an electrostatic precipitator (ESP) for capturing particulates as seen in the layout shown in Figure 3. The full details of the spreader stoker boiler have been reported elsewhere (Taole, 2015). The coal is fed through coal feeders at the front of the furnace. Lighter coal particles burn in suspension and the heavier ones fall onto the grate, burning on it. The grate travels from the back of the furnace towards the front, where the ash is discharged.

The boiler was operated under a steady load conditions as far as possible during the test period, i.e. operations were allowed to stabilize at least an hour prior to commencement of the tests. Steady-state conditions were determined from the analysis of combustion gases in the flue gas stream. All boiler operating conditions, i.e. the grate speed, coal feeder stroke rate, and the under-grate air (UGA) system, which conveys primary combustion air to the overlying coal bed, were kept constant during the trials, in order to establish the impact of coal quality on combustion performance. The tests were performed under full-scale operation. Fluctuations in operating conditions were occasionally experienced, mostly the grate speed. This led to tests being run on each sample over a two-day period to constitute two separate sample batches for the same coal in order to allow for repeatability of the results.

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The calorific value (CV) of the coals ranges from 25.54 to 27.00 MJ/kg. Coal C has the highest CV of 27 MJ/kg and lowest volatile matter content of 23.50%. All four coal samples are considered to be of reasonably low ash, ranging from 14.70 to 17.30%. All the coals utilized contain about 0.02%. sulphate sulphur. Pyritic sulphur is higher in coals A (0.78%) and D (0.71%) compared to coal B (0.13%). The highest fraction of organic sulphur is also found in coal A at 0.66%, while coal B has the lowest proportion at 0.24%. The ultimate analysis results show that the fraction of nitrogen for the four coals is fairly similar, with the lowest value being 1.59% for coal D and the highest being 1.66% for both coals A and C. This indicates that coals A and C are likely to produce higher proportions of fuel NOx contributing to the total NOx emissions.

The HGI values for the coals in this study range from 52 to 70, while the AI values vary from 54 to 246. Coal A was the hardest sample, with an HGI of 52 and AI of 246, while coal sample D was the softest with an HGI value of 70 and AI of 54. It was noted that coal A and coal C, with an HGI of 52 and 59 respectively, have similar HGI values but clearly different AI values of 246 for coal A and AI of 99 for coal C. This distinctive difference in AI might be a positive influence on the grindability and thermal shattering of coal C in the freeboard of the spreader stoker furnace, compared with coal A. The propensity of the four coals to slagging and clinker formation on the grate and furnace heat transfer equipment was also investigated. The flow ash fusion temperatures (AFTs) for the four coals ranged from 1400°C to 1500°C. The highest values were recorded for coals A and C, both at 1500°C, while the lower ash fusion temperatures were detected in coals B and D at around 1400°C.

The overview of the petrographic results for the four coals is presented in Table III. Coals A and D are vitrinite-rich, at 47% and 44%, respectively, whereas coals B and C have significantly high proportions of inertite at 68% and 70% respec-

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for operator control and monitoring. In order to perform a thermographic test for furnace temperature profiling, the positioning of the video camera was first defined and used as a reference to the extent of the optical field viewed and of data captured. The camera was placed about 1 m above the boiler grate level and from the furnace arch where the coal was fed into the boiler (Figure 2). This arrangement allowed for coverage of almost the entire furnace area of interest, based on an optical field of view of 72°.

The impact of coal quality on the efficiency of a spreader stoker boiler

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Proximate: (Ar%) % fixed carbon 50.40 54.50 58.10 48.60 % moisture 4.8 3.4 3.7 4.5 % volatile matter 29.20 24.60 23.50 30.20 % ash 15.60 17.30 14.70 16.70 CV (MJ/kg) 26.13 26.42 26.90 25.54 Ultimate: % carbon 65.86 65.13 67.36 61.58 % hydrogen 3.97 3.61 3.44 3.68 % nitrogen 1.66 1.62 1.66 1.59 % oxygen 6.65 8.56 8.63 8.76 Sulphur species % mineral 0.78 0.13 0.15 0.71 % organic 0.66 0.24 0.34 0.51 % sulphate 0.02 0.01 0.02 0.01 AFT (T, °C) Deformation >1500 1351 >1500 1320 Flow >1500 1403 >1500 1400 HGI 52 61 59 70 AI 246 149 99 94 Ar: as received; AFT: ash fusion temperature; HGI: Hardgrove grindability index; AI: abrasive index

tively. Total reactive macerals for the four coals range from 54 to 64%. Coal D has the highest proportion of total reactive macerals at 64%, while coal C shows the lowest fraction at 54%. Coal D appears to have a slightly higher proportion of abnormal (weathered) constituents than the other three coals, at 25%. This indicates the organic components in coal D are more extensively cracked, weathered, and oxidized than in the other three coals. The mean random reflectance values (Rr%) for the four coals range between 0.61 to 0.76%. In terms of rank, all coals are the bituminous C, with coals A and D slightly lower in maturity.

Table IV presents the results obtained from the performance of the test equipment in the form of the rates of steam output and combustion efficiencies of the coals. Sampling was performed throughout the testing period as the boiler loading or operating steam output was confirmed steadied for about three hours. This test provides an insight into the conditions

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of flue gas exiting the boiler furnace and before entering the economizer section, in terms of exit temperatures and combustion gases. The readings recorded indicate averaged values over the four-hour testing period for each coal sample.

The indications are that coal C, with the highest O2 content and the lowest CO2 fraction of the flue-gas, exhibits poor combustion as evidenced by the relatively high amounts of unburnt carbon (UBC) reported in the ash. Coal D, with the lowest O2 content and the highest proportion of CO2 in the flue gas, displays improved combustion considering the comparatively low amount of UBC in ash.

The impact of the physicochemical properties of the coal samples utilized in this study on the boiler performance and efficiency is further elucidated in Figure 4. The performance of the boiler during the combustion of each coal sample was determined by monitoring the proportion of carbon loss in the fly ash as well as the steam output. Figure 4 also depicts how the physical and chemical properties of coal, namely the calorific value and volatile matter content, possibly affected the coals during combustion. It was observed that the combustion efficiency increases with decreasing amounts of unburnt carbon in the fly ash and increasing volatile matter content, but does not appear to correlate with the calorific value. Increasing combustion efficiency correlates with increasing volatile matter and decreasing fixed carbon, and inversely with the unburnt carbon.

However, the petrographic analysis provides vital information for the holistic understanding of the combustion behaviour of the coals. The analyses and associated

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300.06 181.06 38.59 10.9 10.0 30.13 16.97 4.92

306.42 179.74 37.79 10.5 11.1 42.76 22.70 8.92

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The impact of coal quality on the efficiency of a spreader stoker boiler combustion profiles of the four coals are illustrated in Figure 5. The results indicate that higher combustion efficiency is correlated with higher vitrinite content and total reactive macerals. Coals D and A had higher combustion efficiencies of 79.13% and 77.98%, and total reactivities of 64% and 63%, respectively, compared to coals C and B. Coal D produced the highest steam output (41.76 t/h) and combustion efficiency (79.13%), while coal C yielded the lowest steam output (34.56 t/h) and lowest combustion efficiency of 71.05%. It was also noted that higher amounts of unburnt carbon corresponded with higher quantities of inertinite and lower combustion efficiency.

The primary objective of this investigation was to establish the combustion characteristics and efficiencies of four coals and their impact on the performance of one specific spreader stoker boiler. In seeking to determine the dominant parameters influencing combustion efficiency and boiler performance, a detailed investigation involving the boiler operating conditions associated with physical and chemical characteristics of the coals, petrographic properties, and thermographic data as observed in the boiler was conducted.

From Table V, it is noticeable that coals B and C, with the highest calorific values and lowest volatile matter contents, yielded the lowest steam outputs and combustion efficiencies.

In contrast, coals A and D, with the lowest calorific values

and highest volatile matter contents, produced higher steam outputs and combustion efficiencies. It was also observed that for coals with the closest similarities in physical and chemical properties, such as coals A and D, there were noteworthy differences in the boiler performances under matching operating conditions, as marked by varying steam outputs and combustion efficiencies. The superior performance of coals A and D, compared to coals B and C, may be attributed partly to higher volatile matter contents, as this would imply the coals were easier to ignite. In terms of boiler performance based on proximate analyses, the highest steam output of 41.76 t/h and highest combustion efficiency of 79.13% was observed for coal D, which had the highest volatile matter content and lowest fuel ratio (FR) value. The lowest steam output at 34.56 t/h and lowest combustion efficiency at 71.05% were yielded by coal C, with the lowest volatile matter content and highest FR value. However, the high steam output correlated with high volatile matter and high combustion efficiency, but correlated inversely with fuel ratio and unburnt carbon, as shown in Table V. The fuel ratio is determined from the ratio of fixed carbon to volatile matter and is used to approximate the ease of ignition and burnout for a given coal sample.

The results in Table VI indicate that increasing combustion efficiency correlates with increasing total reactivity. Conversely, high combustion efficiency proves to be inversely proportional to the amount of unburnt carbon and total inertinite. With regard to steam production, the highest steam outputs correlate with high vitrinite content, higher combustion efficiency, and lowest unburnt carbon.

Coal D, with the second highest vitrinite content of 44% mmf and lowest inertinite content of 47% mmf, produced the highest steam output at 41.76 t/h. The association between steam output and petrographic composition was also consistent for the other three coals B, C, and D, which yielded steam outputs paralleling their respective petrographic compositions in terms of total reactive and inert maceral contents. These results show that the impact of petrographic characteristics is crucial in understanding the combustion behaviour of coal. It can further be asserted that for combustion behaviour of any particular coal sample to be wholly known, there has to be an equally comprehensive study of the petrographic characteristics of the coal

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The investigation into the combustion behaviour of the four coals tested was based on thermographic analysis and temperature profiling of the furnace during combustion.

Thermography provides insight into the thermal behaviour of the different coals tested by showing maximum combustion temperatures in the flames and the characteristics of ignition combustion. A summary of the thermographic temperature profiles is presented in Figure 6, and the behaviour of each coal is illustrated in terms of flame characteristics and associated temperature readings. All four coals showed significantly different combustion characteristics despite having comparable calorific values, volatile matter contents, and ash contents. The results indicate that there is a strong correlation between combustion efficiency, unburnt carbon, and petrographic composition of the coals. There is a

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ad: air dry basis; VM: volatile matter; FC: fixed carbon; CV: calorific value; UBC: unburnt carbon; : combustion efficiency; FR: fuel ratio = % FC/% VM; ROI1: region of interest 1 (flame temperatures at highest parts of the furnace); ROI5: region of interest 5 (flame temperatures at lowest parts of the furnace)

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Total vitrinte (%)

Total reactivity (%)

Total inertinite (%)

Rank RoVr%

(%)

(%) UBC/ (Fly ash)

Flame T°C Lowest RO1

Flame T°C Highest RO5

D

44

64

47

0.63

79.13

1771

1793

A

47

63

49

0.61

77.98

1509

1549

B

28

56

68

0.70

75.54

1709

1779

C

24

54

70

0.76

71.05

31.90 (16.97) 30.13 (16.97) 42.76 (22.70) 42.81 (21.62)

1616

1722

Average steam output (O2 in flue gas %) 41.76 (10.27) 38.59 (11.5) 37.79 (11.4) 34.56 (11.7)

ad: air dry basis; VM: volatile matter; FC: fixed carbon; CV: calorific value; UBC; unburnt carbon; : combustion efficiency = [(Fuel - Heat input - Stack losses)/Fuel - Heat input] Ă&#x2014;100

correlation between the combustion efficiency and the total reactive macerals, i.e. the highest combustion efficiency and the lowest unburnt carbon correlate with a high content of reactive organic materials. Low combustion efficiency and high unburnt carbon correlate with high-inertinite coals. This association is not reflected in calorific values or data from the

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proximate analysis. In addition, according to Table V, there is a correlation between the combustion efficiency, fixed carbon, and volatile matter. The lower the fixed carbon of the samples, the higher the combustion efficiency, and the higher the volatile matter, the higher the combustion efficiency The different thermographic trends observed in coals A and D from the same colliery illustrate the lack of a clear correlation between flame temperature, calorific value, combustion efficiency, and ash and volatile matter content. Despite having fairly similar proximate analyses and calorific values, the two coals burnt at notably different flame temperatures under similar operating conditions. Coal A burnt with the lowest maximum flame temperature of all the four coals at ROI5 = 1549°C, while coal D recorded the highest maximum flame temperature amongst the four coals at ROI5 = 1793°C. Coal A, with 14% weathered oxide content, has similar petrographic properties to coal D, which is relatively fresh and unaltered and therefore is likely to burn in its normal condition. Coal B was noted as the coal with the second highest flame temperature at ROI5 = 1741°C. Although this coal possesses the highest calorific value, its flame characteristics did not exhibit good combustion or ignition as the

The impact of coal quality on the efficiency of a spreader stoker boiler

)4.-0+/24.

This research compared the combustion performance of the four coals with their physicochemical properties and their petrographic characteristics. This information provided valuable insight into the differences in combustion behaviour. â&#x17E;¤ The quality of coal proved to significantly influence the combustion performance in the stoker boiler under investigation. This was best reflected in the petrographic composition of the coals and the thermorgaphic results as indicated by flame temperatures and combustion flame characteristics â&#x17E;¤ The most relevant results were observed fro the combustion performance of coals A and D, both from the same colliery. These coals had the same proximate analyses, calorific values, and ash contents, but differed significantly in combustion temperatures, flame shapes, as well as petrographic composition â&#x17E;¤ In terms of efficiency, coal A produced the second highest combustion efficiency and steam output, and burnt at the lowest flame temperatures of all four coals.

Coal D, on the other hand, while producing the highest steam output and combustion efficiency, burnt at the highest flame temperatures of all four coals, with a massive flame that encompassed virtually the entire freeboard above the grate as well as on the grate.

Under these conditions, extensive thermal damage of boiler plant equipment could be expected â&#x17E;¤ The reasons for the difference in combustion performance between coal A and coal D were revealed in part by petrographic analyses, which showed that coal A was a fresh coal and coal D comprised 25% oxidized and weathered organic matter. This was supported by an unusually high Hardgrove index (soft grindability), a particularly low abrasion index (AI), and a lower than normal ash fusion temperature (AFT) relative to the values found in coal A â&#x17E;¤ The massive fireball and high temperatures in the freeboard produced by coal D are interpreted to be due to the presence of friable weathered coal material that underwent intense thermal shattering as the particles

entered the hot zone and were lifted up and thrown across the boiler chamber â&#x17E;¤ The combustion characteristics of coals B and C were found to differ significantly from those of coals A and D. Both coals exhibited limited ignition, reduced flames, and poor burnout characteristics leading to higher unburnt carbon contents in the fly ash. These results occurred despite these coals having the highest calorific values and nominal ash contents. The lower combustion efficiencies of these coals can be attributed to increased proportions of relatively inert forms of organic components (inertinite) â&#x17E;¤ Coal A would be the preferred feed for the boiler under investigation, owing to its lower propensity to slagging due to the lowest flame temperatures of all four coals, its high AFT, second highest combustion efficiency and steam output, and the lowest flame temperatures of all four coals.

6*636.-6/ FALCON, R.M.S. and HAM, A.J. 1988. The characteristics of Southern African coals. Journal of the South African Institute of Mining and Metallurgy, vol. 88, no. 5. pp. 145â&#x20AC;&#x201C;161.

FALCON, R.M.S. 2010. Internal unpublished reports. School of Chemical and Metallurgical Engineering, Faculty of Engineering and the Built Environment, University of the Witwatersrand.

FLETCHER, T.H., MA, J., RIGBY, J.R., BROWN, A.L., and WEBB, B.W. 1997. Soot in coal combustion system. Progress in Energy and Combustion Science, vol.

23, no. 3. pp. 283â&#x20AC;&#x201C;301.

GIAIER, T.A. and LOVISKA, T.R. 1997. Vibrating grate stokers for the sugar industry. Proceedings of the Annual Congress of the South African Sugar Technologists Association, vol. 71. pp. 172â&#x20AC;&#x201C;175.

JOHNS, A.R. and HARRIS, M. 2009. Boiler Efficiency Calculations. Lecture notes: Coal Combustion and Power Generation course, University of Witwatersrand, Johannesburg, 31 August 2009.

LI, Z., ZHAO, W., LI, R., WANG, Z., LI, Y., and ZHAO, G. 2009. Combustion characteristics and NO formation for biomass blends in a 35-ton-per-hour travelling grate utility boiler. Bioresource Technology, vol. 100. pp. 2278â&#x20AC;&#x201C;2283.

LIN, P, JI, J, LUO, Y., and WANG, Y., 2009. A non-isothermal integrated model of coal-fired travelling grate boilers. Applied Thermal Engineering, vol. 29. pp. 3224â&#x20AC;&#x201C;3234.

SANEDI. 2013. Overview of the South African Coal Value Chain. South African Coal Roadmap. http://www.sanedi.org.za/archived/wpcontent/uploads/2013/08/sacrm%2 0value%20chain%20overview.pdf [Accessed 26 May 2015].

SHENG, J.S. WANG, B.B., and LI, W.J. 2012. A study on structural characteristics of biomass briquette boiler. Applied Mechanics and Materials, vol. 197. pp. 211â&#x20AC;&#x201C;215.

TAOLE, R.T. 2015. The Impact of Coal Quality and Technical Operating Conditions on the Efficiency of a Spreader Stoker Boiler. http://wiredspace.wits.ac.za/handle/10539/17553 THAI, S.M., WILCOX, S.J., CHONG, A.Z.S., WARD, J., and PROCTOR, A. 2011.

Development of fuzzy based methodology to commission co-combustion of unprepared biomass on chain grate stoker fired boilers. Journal of the Energy Institute, vol. 84, no. 3. pp. 123â&#x20AC;&#x201C;131. â&#x2014;&#x2020; 7## 777777777777777777777777777777777777777

1165

â&#x2013;˛

flame burnt irregularly and was segregated to discrete parts of the furnace. This observation further confirms that there is no correlation between flame temperature, calorific value, and proximate analysis data. With the exception of coal B, which produced highest temperature in the middle of the furnace (the desirable combustion zone), all other coal samples tended to yield higher flame temperatures both on the grate and in the upper fireball zones of the furnace where the boiler heat-exchangers (steam drum) are located. This indicates delayed combustion at the back end of the boiler.

Such conditions are undesirable as they imply loss of efficiency due to combustion in regions outside of the furnace heat transfer zones, leading also to fouling of the heat exchange surfaces and blocking of convective passes by ash deposits. High flame temperatures pose a greater risk of soot formation due to volatile matter components of the coal, especially tar, undergoing secondary reactions at high temperature (Fletcher et al., 1997).

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http://dx.doi.org/10.17159/2411-9717/2015/v115n12a4

Coal quality and uranium distribution in Springbok Flats Coalfield samples

by M. Ndhlalose*, N. Malumbazo*, and N. Wagnerâ&#x20AC;

The presence of coal in the Springbok Flats Coalfield (SFC) has been known since the beginning of the 1900s. However, the SFC has not been mined to any degree of economic profit, mostly due to the presence of uranium in the coal. Five boreholes were drilled in the SFC (BH1 to BH5); BH5 intersected two coal zones, the other boreholes intersected one coal zone. Coal samples were collected, selected, and characterized using proximate, ultimate, and calorific value analyses. X-ray fluorescence, instrumental neutron activation analysis, and inductively coupled plasma mass spectrometry were used to determine uranium content. The BH1 intersection and the upper coal zone in BH5 had ash contents higher than 50% and were considered to be primarily carbonaceous shale. BH2 was observed to have better coal quality, resembling typical South African bituminous coal used in local electricity generation. The highest uranium content was found in BH3 (up to 199 mg kg-1, followed by BH2 and BH1.

BH4, the upper coal zone in BH5, and the lower coal zone in BH5 all had uranium contents averaging less than 10 mg kg-1. Uranium in the SFC samples was found both in the coal and carbonaceous shale. For all boreholes except BH5, uranium is concentrated within the uppermost 1 m of the coal zone. X-ray fluorescence was the preferred analytical technique since the analysis gave consistent results that compared well with instrumental neutron activation analysis results. <& ;7%4 Springbok Flats Coalfield, coal quality, uranium.

897;%6-95;8 Coal in South Africa is found in 19 coalfields located in the middle and northern sections of the country (Jeffrey, 2005). The main coal mining areas in the country at present are in the Witbank-Middelburg, Waterberg, and Sasolburg coalfields of the Mpumalanga and Limpopo provinces. The Springbok Flats Coalfield (SFC), located in the Limpopo Province, has not been mined to any degree of economic profit, predominantly due to the presence of uranium in the coal. The first coordinated exploration programme was conducted by the Council for Geoscience (CGS) between 1952 and 1957, where 27 boreholes were drilled in the northeastern portion of the SFC (Visser and Van der Merwe, 1959).

Further exploration by the CGS in the western and south-central portions of the coalfield was halted in 1972 when uranium was detected in the upper Ecca coal zone (Christie, 1989).

Similar to most materials in nature, coal

* Council For Geoscience, Pretoria, South Africa. â&#x20AC; School of Chemical and Metallurgical Engineering, University of the Witwatersrand, (now Department of Geology, University of Johannesburg). Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received June 2015 and revised paper received Nov. 2015.

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contains small quantities of naturally occurring radionuclides such as 40K, 238U, 232Th, and their decay products (Papastefanou, 2010).

The Medium Rank C bituminous coal zones in the Springbok Flats Basin, hosted in the coal horizons of the Late Permian in the uppermost part of the Hammanskraal Formation within the SFC basin, have a significant uranium content (Cole, 1998). Further, the uranium in the SFC is believed to be disseminated throughout the coal and the associated carbonaceous shale (Christie, 1989). This is particularly noteworthy as it means that this coalfield could potentially have areas that are rich in uranium but with very little coal present. This gives metallurgists the opportunity to concentrate on extracting uranium from the carbonaceous horizons without worrying about the effects of the uranium extraction process on coal and its ability to combust post-extraction.

Overall, there is limited public domain research pertaining to the quality of coal present in the SFC as well as the uranium associated with the coal and carbonaceous horizons. This knowledge is strategically important in determining the viability of the SFC as a potential source of either coal or uranium, thus addressing two key energy markets. The Department of Mineral Resources (DMR) has seen a need for South African coal researchers and metallurgists to investigate cleaner coal processing and energy production, and has thus created intervention strategies for the optimal beneficiation of coal (Department of Mineral Resources, 2011), which, among numerous other objectives, seek to invest in metallurgical research on the

Coal quality and uranium distribution in Springbok Flats Coalfield samples quality of the coal associated with uranium in the SFC. Thus, the aim of this study is to assess the quality of newly acquired borehole core coal samples, and to accurately determine the uranium content in those samples. Once an understanding of the uranium content and distribution is obtained, the extraction of the uranium from specific localities can be considered; this discussion is targeted for a future publication.

0<753<89=:>07;-<%67<> The study covers five boreholes drilled in the SFC (BH1 to BH5) in 2013. BH1 to BH4 intersected a single coal zone, while BH5 intercepted two coal zones, an upper and a lower zone. Thus, six coal localities were included in this research.

Figure 1 depicts the five farms where the drilling occurred.

The boreholes were drilled up to a depth of 450 m, recovering a 4 cm cylindrical core. The recovered cores were placed in 1.5 m long core trays, logged, and stored at the CGS Donkerhoek core shed, Pretoria, for about a month prior to

sampling. One quarter section of core from each coal horizon was removed (the rest retained for future projects), and milled using a Reutsch mill to obtain a -1 mm split (retained for coal petrography) and a subsequent -250 Îźm sample. A MACSALAB design rotary cascade splitter was used to obtain a representative -250 Îźm split for geochemical analysis (proximate, ultimate, CV, uranium determination). All samples were studied on an as-received basis. Proximate analysis was conducted at the CGS coal laboratory following ISO 1171:1981, SANS 5924:2009, and ISO 562:1981. Leco CHN and Leco S instruments were used to determine ultimate analysis using ISO 17247:2013. The CV data was obtained using a Parr 3600 bomb calorimeter where net CV (NCV) was used as the measure of CV. To determine uranium content, Xray fluorescence (XRF) data was processed using a PANalytical wavelength-dispersive Axios X-ray fluorescence spectrometer. Inductive coupled plasmaâ&#x20AC;&#x201C;mass spectrometry (ICP-MS) analysis was conducted using a Bruker 500 MHz NMR spectrometer. Eleven samples that revealed an uranium content higher than 10 mg kg-1 were subjected to instrumental neutron activation analysis (INAA) to confirm the results obtained from ICP-MS and XRF.

.;=:> 6=:59&>7<46:94> Figure 2 shows the major coal quality parameters relative to depth for each borehole coal zone, with the actual data reported in Tables Iâ&#x20AC;&#x201C;V for each of the coal zones sampled. Photographs of the coal zone intersections are provided in Figure 3.

BH1: The volatile matter content was highest in the samples proximal to the roof of the coal zone where the bright bands were observed. The average ash content for BH1 peaked at 88.4%, indicative of carbonaceous shale horizons or partings in the coal zone (Table I). The CV peaked at 4.2 MJ/kg, which

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Coal quality and uranium distribution in Springbok Flats Coalfield samples

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indicates a coal zone that is virtually incombustible. It was thus concluded that the whole coal zone sampled is predominately carbonaceous shale instead of coal as defined by SANS 10320:2004.

BH2: Relatively good CV data was obtained for samples in BH2, peaking at 27 MJ/kg (Table II). However, the sulphur content was alarmingly high for a number of coal samples, reaching a maximum of 8.9%. Sulphur was found to be abundant in the samples with high CV and volatile matter, and low ash content. The ash content was higher towards the floor of the coal zone. The majority of the coal zone registered ash contents well below 50%, indicating that the zone is made up predominately of coal.

BH3: When one considers the entire coal zone in BH3, it is can be noted that 60% of the 3.6 m coal zone contained

samples with ash contents higher than 50% (Table III). The remaining 40% of the samples recorded CV and volatile matter averages of 18.7 MJ/kg and 25.5% respectively.

Similar to BH2, these samples also recorded a higher average sulphur content (3.5%).

BH4: The ash content in BH4 was fairly constant in all samples (46â&#x20AC;&#x201C;58.4%), except for the sample close to the floor of the seam. Table IV shows that the coal quality in BH4 is very poor, supported by the low CV that peaked at 16.5 MJ/kg. Similar to the other boreholes, the sulphur content was highest (4.2%) in the regions where the coal quality was better than the surrounding samples.

BH5 upper coal zone: 90% of the coal zone had an ash content higher than 50%. The lowermost sample was of comparatively better coal quality, with a CV and ash content

<09/>132 277.0â&#x20AC;&#x201C;277.9 278.0â&#x20AC;&#x201C;278.8 278.8â&#x20AC;&#x201C;279.4 279.4â&#x20AC;&#x201C;280.0 280.0â&#x20AC;&#x201C;280.5 308.7â&#x20AC;&#x201C;309.1 309.1â&#x20AC;&#x201C;309.6 Average

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74.9 88.4 85.1 76.2 84.9 82.5 62.2 79.2

13.7 0.2 6.3 12.1 4.1 9.6 5.3 7.3

0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.2

3.5 0 0.7 4.2 1.0 2.4 0.8 1.8

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22.4 29 19.3 25.4 31.8 33.2 23.8 22.4 16.6 19.1 24.3

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38.6 51.7 34.4 47.8 65.3 57.7 46.8 44 27.9 31.4 44.6

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58.4 46.7 46.0 49.7 53.4 73.9 54.7

26.1 37.8 41.2 40.2 38.6 19.0 33.8

4.2 4.1 1.0 0.6 0.6 0.3 1.8

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64.7 75.1 79.8 61.9 69.0 62.2 76.0 60.0 66.3 43.3 65.8

27.3 18.9 13.6 32.0 25.4 31.2 18.0 33.1 26.7 40.0 26.6

3.6 2.2 0.7 0.8 0.7 0.9 0.7 1.0 0.5 12.4 2.4

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Coal quality and uranium distribution in Springbok Flats Coalfield samples

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0.3 0.3 0.3 0.4 0.7 0.6 0.2 0.2 0.3 1.5 0.5

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of 17.8 MJ/kg and 43.3% respectively (Table V). The proximate analysis and CV results for the upper coal zone of BH5 are below the limits of typical South African coals, and the results resemble those of carbonaceous shale instead of coal (Martins et al., 2010).

samples, peaking at a moderate 15.8 MJ/kg (Table VI). The proximate analysis and CV results for the upper coal zone of BH5 are below the limits of typical South African coals, and the results resemble those of carbonaceous shale instead of coal (Martins et al., 2010).

BH5 lower coal zone coal: The ash content in the upper coal zone in BH5 was high, with no sample recording ash content less than 40%. The majority of the coal zone reported ash contents higher than 50%. The CV was low for all

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Figure 4 provides the uranium content for each of the five borehole core samples. Figure 5 depicts the average concentrations. As the samples included the high-ash carbonaceous shales, the uranium values are not indicative of only the coal-rich zones.

ICP-MS produced the lowest uranium values of all the analytical techniques used, and XRF consistently produced the highest uranium values (Table VII). INAA (on selected samples) reported higher uranium values than ICP-MS, and the results were closer to the XRF values (Table VII). The variation in some ICP-MS results led to the conclusion that an error (either technical or human) could have occurred during analysis. Due to the consistent results provided by XRF, these results were used in the subsequent interpretations and discussion.

BH1: The uranium content in the BH1 samples ranged from 5.3 mg kg-1 to 73 mg kg-1. The highest uranium values occurred at the roof of the coal zone. Since the BH1 sample consisted entirely of carbonaceous shale, this gives metallurgists the opportunity to concentrate on extracting uranium from these horizons without worrying about the effects of the uranium extraction process on coal and its combustion qualities post-extraction.

BH2: Samples from BH2 had uranium contents that ranged from 2.9 mg kg-1 to 130 mg kg-1. The uranium content was highest where the ash content was < 50%, with a significant peak occurring towards the middle of the coal zone (96 mg kg-1), also a coal-rich zone.

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BH3: The uranium content of sample 1421 was 199 mg kg-1, the highest of all samples. Relative to coal quality, both carbonaceous shale regions and coal regions contained uranium; however, the coal-rich samples yielded higher uranium values.

Coal quality and uranium distribution in Springbok Flats Coalfield samples

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BH5 LCZ BH5 LCZ BH3 BH3 BH2 BH1 BH1 BH1 BH1 BH1 BH4

12 14 199 18 96 73 52 51 36 14 52

8.9 11.8 161 15.6 86.9 64.6 43.2 39.4 29.3 11.5 33.5

8.6 9.8 145.9 11.3 85.9 34.1 13 19.4 20.9 6.2 34.4

BH4: Maximum uranium content was detected where the coal zone reported an ash content of 58.4%. Similar to previous boreholes, uranium was found to be abundant at the roof of the coal zone.

BH5 lower coal zone coal: The lower coal zone coal in BH5 returned a peak uranium content of 14 mg kg-1. Similar to BH2, other peaks of interest were found further down the coal zone. The uranium was distributed in some areas that consisted predominately of coal, and in areas that were predominately carbonaceous shale.

Carbonaceous shale (blue arrows) dominated the entire coal zone. The lower coal zone in BH5 also had very few coal and carbonaceous shale (blue arrows) dominated the entire coal zone.

The average ash content of boreholes BH1, BH3, BH4, and the upper and lower coal zones in BH5, were far greater than the 40.3% recorded in the CGS database, and higher than the 30â&#x20AC;&#x201C;55% estimated by De Jager (1983), while also being higher than the 30â&#x20AC;&#x201C;35% ash inferred by the Petric Commission (1975). BH2 average ash content of 40.8% agrees with the 40.3% recorded in the CGS database for coal from the same locality, and is in line with the 30â&#x20AC;&#x201C;55% ash content estimated by De Jager (1983). BH2 coal quality resembles a typical South African bituminous coal (Falcon and Ham, 1988; Pinhiero, 1999); however, the sulphur content average of 3.2% is higher than the 2.8% recorded in the CGS database for samples from the same region, while also being higher than 0.4â&#x20AC;&#x201C;1.29% reported by Wagner and Hlatshwayo (2005) for Highveld coals, and 1.47% found by Roberts (2008) for samples in Mpumalanga.

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It was apparent from visual inspection that the coal zones sampled do not consist only of coal, but carbonaceous and sandstone horizons are interbedded in the coal zone, as shown in Figure 2. The darker horizons in the cores represent the coal zones, made up of interbedded coal and carbonaceous shale. BH1 was dominated by carbonaceous shale (blue arrows) with very few visible bright coal bands.

BH2 had significantly more bright coal bands compared to BH1, where the coal zone appeared to be made up predominately of bright coal (red arrows to left) interbedded with carbonaceous shale (blue arrow to right). Calcite cleats (green arrow top right) were visible in some areas in the coal zone.

BH3 coal zone consisted of bright coal (red arrows to left) clustered at the top of the coal zone; the bright bands of coal diminished and carbonaceous shale (blue arrows to right) dominated further down the coal zone. BH4 contained very few bright bands of coal. Carbonaceous shale dominated the top of the coal zone, with regular bright coal bands a little further down, towards the middle of the coal zone, which diminished again towards the bottom of the coal zone. The upper coal zone in BH5 had very few bright bands of coal, with large areas showing no bright bands of coal at all.

Figure 5 shows the average uranium contents for each of the boreholes studied. All borehole coal zones studied had uranium contents averaging higher than the 2 mg kg-1 world average reported by Swaine (1990), and the 2.9 ppm global average for coals (Ketris and Yudovich 2009). Ren et al., (1999) determined a 7.52 mg kg-1 arithmetic mean uranium content in Chinese coals.

The uranium content relative to selected coal quality results can be seen in Figure 6. Uranium in the SFC samples was disseminated throughout the coal and carbonaceous shale, as reported by Cole (2009) and Hancox and Gotz (2014). The uranium in the coal zones was generally restricted to a single layer, usually the highest in the local sequence, except in BH2 and the lower coal zone coal in BH5, where uranium mineralization was found in multiple locations in the coal zone. This finding is in agreement with Cole (2009), Christie (1989), and Nel (2012). BH3 had the highest average uranium content, and the highest uranium content (199 mg kg-1) was determined in a sample from this coal zone. BH4 and the upper and lower coal zones in BH5 all had average uranium contents less than 10 mg kg-1 (which is still high in the global context).

BH5 upper coal zone: Similar to BH1, the entire coal zone was made up of carbonaceous shale, and thus uranium in this coal zone occurred in the carbonaceous shale. Unlike the other intersections, where the maximum uranium content was found at the roof, the uranium was distributed fairly evenly throughout the coal zone with a difference of 5 mg kg1 between the maximum and the minimum values determined.

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Coal quality and uranium distribution in Springbok Flats Coalfield samples

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In summary, BH1 and the upper coal zone in BH5 reported ash contents higher than 50% for all the samples collected throughout the coal zone; these coal zones are made up almost entirely of carbonaceous shale and are thus not suitable for coal exploitation. BH2 samples reported coal qualities that resemble a typical South African bituminous coal and could potentially be of economic benefit to the country, depending on the available tonnages in the area.

BH3 and BH4 had coal horizons that are potentially mineable, and could be of use in the coal conversion industries.

.;8-:645;84>;8>67=8563>-;89<89 INAA reported higher uranium values than ICP-MS, with the results being closer to the XRF values; which were the highest for all the samples. All borehole coal zones studied had an average uranium content higher than the 2 mg kg-1 world average reported by Swaine (1990). Uranium in the coal zones sampled was generally restricted to a single layer, usually the highest in the local sequence, except in BH2 and the lower coal zone coal in BH5, where uranium mineralization occurred in multiple locations in the coal zone. This finding is in agreement with Cole (2009) and Nel (2012).

Overall, uranium in the SFC samples was disseminated throughout the coal and carbonaceous shale horizons, findings supported by Hancox and Gotz (2014). BH4 and the upper and lower coal zones in BH5 all had average uranium content less than 10 mg kg-1 , but BH2 and BH3 had average values over 25 mg kg-1. Table VII shows the samples selected

for INAA analyses to confirm the high uranium values; these samples were selected for leaching experiments to extract and concentrate the uranium. This work will be reported in a future publication.

"- 8; :<%)<3<894 This research was sponsored by the CGS and the National Research Foundation (NRF).

We would also like to thank Dr Samson Bada for assistance with the proximate analyses, and Ms Zwanga Mulibana for assistance with ultimate analysis.

< <7<8-<4 CHRISTIE, A.D.M. 1989, Demonstrated coal resources of the Springbok Flats Coalfield. Report 1989-0069. Geological Survey of South Africa. 25 pp COLE, D.I. 1998. Uranium. Mineral Resources of South Africa. Wilson, M.G.C. and Anhaeusser, C.R. (eds), Handbook 16, Council for Geoscience, Pretoria. pp. 642â&#x20AC;&#x201C;658 COLE, D.I. 2009. A review on uranium deposit In the Karoo Supergroup of Southern Africa. Search and Discovery Article no. 80047. Council for Geoscience, Pretoria. pp. 1â&#x20AC;&#x201C;9.

DE JAGER, F.S.J. 1983. An evaluation of the coal reserves of the Republic of South Africa as at 1982. Report no. 1983â&#x20AC;&#x201C;0006. Council for Geoscience, Pretoria.

DEPARTMENT OF MINERAL RESOURCES. 2011. Beneficiation Strategy. http://www.dmr.gov.za/publications/summary/162-beneficiationstrategy-june-2011/617-beneficiation-strategy-june-2011-.html [Accessed 6 November 2014]. + #( >**!>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>

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.;8-:645;84>;8>-;=:> 6=:59&

Coal quality and uranium distribution in Springbok Flats Coalfield samples FALCON, R.M.S. and HAM, A.J. 1988. The characteristics of Southern African coals. Journal of the South African Institute of Mining and Metallurgy, vol.

88, no. 5. pp. 145â&#x20AC;&#x201C;161.

HANCOX, J.P. and GOTZ, A.E. 2014. South Africaâ&#x20AC;&#x2122;s coalfields â&#x20AC;&#x201C; a 2014 perspective. International Journal of Coal Geology, vol. 132, no. 1. pp.

170â&#x20AC;&#x201C;254.

JEFFREY, L.S. 2005. Characterization of the coal resources of South Africa.

Journal of the South African Institute of Mining and Metallurgy, vol. 105, no. 2. pp. 95â&#x20AC;&#x201C;102.

KETRIS, M.P. and YUDOVICH, Ya.E. 2009. Estimations of Clarkes for carbonaceous biolithes: world averages for trace element contents in black shales and coals. International Journal of Coal Geology, vol. 78. pp. 135â&#x20AC;&#x201C;148.

MARTINS, M.F., SALVADORA, S., THOVERT, J.F., and DEBENEST, G. 2010. Co-current combustion of oil shale â&#x20AC;&#x201C; Part 1: Characterization of solid and gaseous products. Fuel, vol. 89, no. 1. pp. 144â&#x20AC;&#x201C;151.

PETRIC COMMISSION. 1975. Report of the Commission of Enquiry into the Coal Resources of the Republic of South Africa. Government Printer, Pretoria.

PINHIERO, H.J. 1999. A techno-economic and historical review of the South African coal industry in the 19th and 20th centuries and analysis of coal product samples of South African collieries. Bulletin 113. South African Bureau of Standards and Department of Minerals and Energy, Pretoria.

REN, D., ZHAO, F., WANG, Y., and YANG S. 1999. Distribution of minor and trace elements in Chinese coals. International Journal of Coal Geology, vol. 40. pp. 109â&#x20AC;&#x201C;118.

ROBERTS, D.L. 2008. Chromium speciation in coal combustion by products: case study at a dry disposal power station in Mpumalanga province, South Africa. PhD thesis, University of the Witwatersrand, Johannesburg. p. 235.

SWAINE, D.J. 1990, Trace Elements in Coal. Butterworths, London.

NEL, L. 2012. The geology of the Springbok Flats. PhD thesis, Department of Geology, University of the Free State.

VISSER, H.N. and VAN DER MERWE, S.W. 1959. The Northern Springbok Flats Coalfields. Records of boreholes 1-27. Bulletin of the Geological Survey of South Africa. pp. 31â&#x20AC;&#x201C;97.

PAPASTEFANOU, C. 2010. Escaping radioactivity from coal-fired power plants (CPPs) due to coal burning and the associated hazards: a review. Journal of Environmental Radioactivity, vol. 101, no. 3. pp. 191â&#x20AC;&#x201C;200.

WAGNER, N.J. and HLATSHWAYO, B. 2005. The occurrence of potentially hazardous trace elements in five Highveld coals, South Africa.

International Journal of Coal Geology, vol. 63. pp. 228â&#x20AC;&#x201C;246. â&#x2014;&#x2020;

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http://dx.doi.org/10.17159/2411-9717/2015/v115n12a5

Synthesis of sodium silicate from South African coal fly ash and its use as an extender in oil well cement applications

by T. Kaduku*, M.O. Daramola*, F.O. Obazu*, and S.E. Iyuke*

In this work, the use of sodium silicate derived from South African coal fly ash (CFA) in oil well cement (OWC) applications is reported. Silica (SiO2) was extracted from the CFA and used to synthesize CFA-derived sodium silicate (CFA-Na2SiO3), a typical OWC slurry extender. The physicochemical properties of the CFA-Na2SiO3 were compared to those of a commercial sodium silicate (com-Na2SiO3) using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy. OWC slurries with varying proportions of cement, distilled water, and 2% CaCl2 by weight of water (BWOW) were prepared and extended using the CFA-Na2SiO3 and the com-Na2SiO3 at compositions ranging from 0.25-2.5% by weight of cement (BWOC).

Rheological properties of the slurries were evaluated using American Petroleum Institute procedures and compared. The physico-chemical properties of the CFA-Na2SiO3 are consistent with those of com-Na2SiO3, indicating the purity of the CFA-Na2SiO3. A comparative study of the OWC slurries indicated that the slurries extended with CFA-Na2SiO3 have slightly lower densities, lower viscosities, and higher compressive strength than those extended with com-Na2SiO3. This indicates that CFA-Na2SiO3 slurries would be easier to pump and preferable where early strength development is critical. This report could be instrumental in providing a way for the beneficiation of South African CFA in the petroleum, oil, and gas industry.

oil well cementing, coal fly ash, sodium silicate, compressive strength.

During the oil and gas well cementing process, some wells often lose circulation zones, and are therefore prone to formation breakage.

Often, low-density slurries are required to overcome these problems, and extenders, which help to reduce the weight of the slurry, are utilized (Salim and Amani 2013; Ahmaruzzaman 2010; Shahriar 2011). The commonly used extenders are water extenders such as bentonite and sodium silicate, which allow addition of water to the slurry; and lowdensity aggregates such as microspheres and pozzolans, which have densities lower than that of Portland cement (3.15 g.cm-3) (Nelson et al., 1990). These extenders reduce the density of the slurry, resulting in a reduction of the hydrostatic pressure during cementing (Nelson et al., 1990). Extenders also increase slurry yield by replacing a substantial amount

* School of Chemical and Metallurgical Engineering, Faculty of Engineering and the Built Environment, University of the Witwatersrand, Wits 2050, Johannesburg, South Africa. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received June 2015 and revised paper received Nov. 2015.

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of the cement required to complete a given task, thereby reducing the expenditure.

One of the most commonly used water extenders for oil well cement (OWC) is sodium silicate (Na2SiO3). It has been reported that Na2SiO3 as a water extender is five times more effective than bentonite (Nelson et al. 1990).

Unlike pozzolanic extenders such as fly ash, Na2SiO3 is highly reactive with OWC (Joel and Ujile, 2009). Na2SiO3 reacts with the Ca2+ ions from the lime in the OWC or calcium chloride to produce additional calcium-silica-hydrate (C-S-H) gel (Nelson et al., 1990). The gel structure provides sufficient viscosity to allow the use of large quantities of mix water without excessive free water separation (Nelson et al., 1990). The further C-S-H formation also results in a reduction in thickening time, hence the accelerating effect of Na2SiO3 (Joel and Ujile, 2009). A low concentration of Na2SiO3 is required for a high yield as compared to other extenders such as bentonite and raw coal fly ash, making it a preferred additive for OWC (Joel and Ujile 2009). While fly ash is added in concentrations of up to 50% by weight of cement (BWOC) and bentonite up to 20% BWOC, Na2SiO3 additions range from 0.2% to 3.0% BWOC (Nelson et al., 1990). The accelerating effect of Na2SiO3, however, limits its application at lower temperatures, typically at less than 52°C bottom hole circulating temperature (BHCT) (Nelson et al., 1990; Joel and Ujile 2009). However, it can be used at higher temperatures with the addition of a retarder, although in the presence of a retarder, the effectiveness of Na2SiO3 as an extender is reduced because of the inhibition of C-S-H formation (Nelson et al., 1990; Joel and Ujile, 2009).

Synthesis of sodium silicate from South African coal fly ash At industrial scale, commercial sodium silicate is traditionally manufactured by calcination of sodium carbonate (Na2CO3) and SiO2 at a temperature range of 1400â&#x20AC;&#x201C; 1500°C in furnaces (Folleto et al., 2006). Although the raw materials are cheap, the process is not cost-effective due to its high energy consumption and maintenance cost (Folleto et al., 2006). The process also emits dust, nitrogen, and sulphur oxides, contributing to air pollution. Alternatively, Na2SiO3 can be produced by the reaction of SiO2 with NaOH solution in an autoclave, at high temperature and pressure (McDaniel et al., 1961). In light of the information at hand, it is necessary to carry out an investigation on alternative methods, which are less energy intensive, for producing Na2SiO3 for use as an additive to OWC. In addition, the SiO2, one of the raw materials required in the aforementioned alternative preparation method of Na2SiO3, can be obtained from coal fly ash (CFA).

CFA is an inorganic powder that is produced during the combustion of coal (Ahmaruzzaman, 2010). Several studies have been carried out and reported on the beneficiation of CFA (Iyer and Scott, 2001; Ahmaruzzaman, 2010; Taylor, 1990; Kamarudin et al., 2009; Park et al., 2012).

Beneficiation of fly ash from other materials such as rice husks, bagasse, and corn cobs has also been reported (Aigbodion et al., 2010; Foleto et al., 2006; Okoronkwo et al., 2013). The use of CFA in OWC has been reported (Shahriar, 2011), but composition of the CFA differs from country to country and this could affect its suitability as additive in OWC operations. Furthermore, the use of raw CFA results in slower strength gain and longer setting times, thereby resulting in low early-age strength and delays in the well completion process (Bazzar et al., 2013). In South Africa, about 25 Mt of CFA is produced annually and its disposal constitutes a huge environmental problem. In this study, SiO2 was extracted from CFA and used as starting material to synthesize Na2SiO3. The potential use of the synthesized CFA-derived sodium silicate as an OWC extender was evaluated and compared with that of commercial sodium silicate (com- Na2SiO3).

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Class G cement was obtained from Dyckerhoff, Germany, and CFA from a power station in South Africa. Demineralized water was prepared in-house. Hydrochloric acid solution (37%), sodium hydroxide pellets (98% purity), calcium chloride (99.99% purity), and commercial sodium metasilicate (95%) were purchased from Sigma Aldrich and used as delivered without any modification or purification.

" ! " ! ! "! " ! ! !

Small quantities of CFA were scooped randomly from different points and then mixed together to make the representative sample. The CFA samples were characterized using X-ray diffraction (XRD: Brucker D2 X-ray diffraction machine), X-ray fluorescence (XRF: PANalytical AXIOS Xray fluorescence spectrometer), scanning electron microscopy (SEM: Zeiss Sigma VP field emission scanning electron

â&#x2013;˛

1176

, !#"D55/

microscope), and thermogravimetric analysis (TGA: TGA DSC STA 600 with Pyris software). The pH of CFA (slurried in water) was measured using a Metrohm 744 pH meter, and the particle size distribution of the CFA was obtained using a Malvern Mastersizer 2000.

! " " ! " ! ! " " ! " " The metal oxides such as Al2O3 and CaO were removed from CFA by acid refluxing using 3 M HCl at 100°C for 6 hours as described by Tang et al. (2012). The solid product, SiO2, was filtered out and purified by successive washings with demineralized water. The wet SiO2 was dried in an oven at 200°C for 2 hours to obtain an amorphous silica powder which was then analysed using SEM-EDX, XRD, and Fourier transform infrared spectroscopy (FTIR: Brßker Tensor 27 Fourier transform infrared spectrometer). 60 g of the amorphous silica was reacted with 80 g sodium hydroxide pellets in 100 ml distilled water in a Pyrex flat-bottomed flask at 80°C and atmospheric pressure to produce a colourless viscous solution. The solution was then poured into a crucible and calcined at 300°C for 3 hours to produce a white solid (CFA-Na2SiO3) which was crushed to a powder using a mortar and pestle. The product was then subjected to SEMEDX, XRD, and FTIR analyses.

! ! "! " ! ! ! " " " Slurries containing varying amounts of cement, distilled water, 2% calcium chloride (CaCl2) by weight of water (BWOW), com-Na2SiO3, and CFA-Na2SiO3 were prepared and their densities, rheology, and thickening times evaluated. A Chandler Ametek constant speed mixer (Model 30-60) was used for mixing and the slurries were pre-conditioned using a Chandler Ametek Atmospheric Consistometer (Model 1200) prior to the rheology tests. The rheology tests were conducted using a Chandler Ametek automated viscometer (Model 3530) and a Chandler Ametek pressurized mud balance was used to determine the density of the slurries. A Chandler Ametek twin cell ultrasonic cement analyser (UCA) (Model 4262) was used to determine the development of compressive strength of the slurries. All the tests on the cement slurries were carried out according to the specification for materials and testing for well cements (American Petroleum Institute Specification 10A, 2002). The compositions of the slurries are presented in Table I.

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Figure 1 shows the XRD patterns for the CFA. The patterns are consistent with those reported for previously studied South African CFAs (Ayanda et al., 2012; Mainganye et al., 2013; Ikotun et al., 2014). Table II shows the XRF analysis of the CFA together with results from reports in the literature (Ayanda et al., 2012; Mainganye et al., 2013). The major components of the CFA are silica, alumina, iron oxide, calcium oxide, and carbon (inferred from the loss on ignition (LOI) test). The CFA is of class F (ASTM C618, 2012). The metal oxide contents decreased in the order SiO2> Al2O3> Fe2O3> CaO> MgO> K2O> Na2O> TiO2. This is consistent with previous reports on South African CFA (Ayanda et al., 2012; Mainganye et al., 2013; Ikotun et al., 2014). Interestingly,

Synthesis of sodium silicate from South African coal fly ash ! "

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! " " " ! ! ""! " ! ! ! " ! " "" The morphologies of the extracted SiO2, synthesized CFANa2SiO3, and com-Na2SiO3 were characterized by SEM. Figure 3 shows the SEM images of the extracted SiO2. Similar images for precipitated SiO2 have been reported in the literature (Music et al., 2011). The elemental compositions obtained using energy dispersivee X-ray spectroscopy (EDS) (not shown in this manuscript) indicated the presence of Si and O, confirming the presence of SiO2. The XRD pattern in Figure 4 shows the characteristic slope and pattern for amorphous SiO2, consisting of a broad band with a peak which indicates that the substance is amorphous and contains pure SiO2 (Saikia et al., 2008; Essien et al., 2011; Music et al., 2011; Okoronwo et al., 2013). Similar patterns for amorphous silica have been recorded in the literature (Saikia et al., 2008; Okoronwo et al., 2013). The two sharp peaks in the pattern are due to the presence of quartz, corroborating the results obtained from EDS. The FTIR spectrum of the SiO2 is depicted in Figure 5. The bands of absorption at 1199 cm-1, 964 cmâ&#x20AC;&#x201C;1, and 682 cmâ&#x20AC;&#x201C;1 can be attributed to the absorption peaks characteristic of SiO2 (Ying-Mei et al., 2010). The absorption peak at 1199 cmâ&#x20AC;&#x201C;1

4B1<ACD6D D0"#D9B;A?1A=+8D?.D>8CD0?<>8D2.AB;=7D342 , !#"D55/

1177

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the CFA contained about 58% SiO2, which is one of the required materials for the synthesis of Na2SiO3.

The morphology of the CFA is depicted in the SEM micrograph in Figure 2. The shapes of the CFA particles are determined by the exposure conditions (time and temperature) in the combustion chamber (Fisher et al., 1978). As seen in Figure 2, most of the particles are spherical, especially in the finer fractions. A similar observation has been reported for other South African CFAs (Ayanda et al., 2012; Mainganye et al., 2013). The particles are a mixture of opaque and non-opaque spheres. The opaque spheres are predominantly iron oxides and some silicates, while the non-opaque spheres are mainly silicates (Fisher et al., 1978). Previous studies have shown that fly ash is made up of, in some cases, smaller particles (<< 1 Îźm) which are attached to the surface of larger particles, hollow spheres (cenospheres), and some spheres containing other spheres (plerospheres) (Mainganye et al., 2013). In addition, the SEM micrograph shows the presence of some nonspherical particles. These amorphous particles arise mainly from incomplete combustion of coal components (Fisher et al., 1978). Furthermore, the TGA shows that the CFA contains about 0.2% moisture, 1.6% volatile matter, and 1.7% fixed carbon. The particle size ranges from 0.32â&#x20AC;&#x201C;112 Âľm. These results are also in agreement with previous studies (Ayanda et al., 2012 ; Ikotun et al., 2014). A rise in pH from 7 to 10.7 was observed when the CFA was mixed with de-ionized water over a period of 5 hours. This could be attributed to the dissolution of compounds such as CaO in the CFA. This observation is in good agreement with previous reports (Ayanda et al., 2012).

Synthesis of sodium silicate from South African coal fly ash

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corresponds to the asymmetrical stretching vibration of Siâ&#x20AC;&#x201C;O (Ying-Mei et al., 2010). In addition, the absorption peaks at 964 cmâ&#x20AC;&#x201C;1 and 682 cmâ&#x20AC;&#x201C;1 correspond to the symmetrical stretching vibrations of Siâ&#x20AC;&#x201C;O groups on the surface of the amorphous solid (Ying-Mei et al., 2010; Essien et al., 2011).

The stretch between 1500 cmâ&#x20AC;&#x201C;1 and 2000 cmâ&#x20AC;&#x201C;1 can be attributed to the presence of the Siâ&#x20AC;&#x201C;OH and bending vibration absorption of the Oâ&#x20AC;&#x201C;H bond of physically adsorbed water, respectively (Music et al., 2011).

The XRD patterns for CFA-Na2SiO3 and com-Na2SiO3 are shown in Figure 6. The two patterns are similar, although a small difference in the intensities of some of the peaks was observed. Curve fitting showed that there is a slight shift in the peaks of CFA-Na2SiO3. The shift in the peaks could be attributed to the small quantity of the sample used in the analysis. Figure 7 depicts the SEM images for CFA-Na2SiO3 and com-Na2SiO3. The morphology of the CFA-Na2SiO3 is totally different from that of com-Na2SiO3. However, the EDS results showed the same elemental components with different compositions. Figure 8 shows the FTIR spectra for the comNa2SiO3 and CFA-Na2SiO3. The FTIR analysis of the two samples indicates that there is no observable chemical difference between the samples. Both samples show absorption bands at 2340 cm-1, 1160 cmâ&#x20AC;&#x201C;1, 1125 cmâ&#x20AC;&#x201C;1, 980 cmâ&#x20AC;&#x201C;1, and 715 cm-1 that characterize the presence of sodium metasilicate (Miller and Wilkins, 1952). The stretch between 1500 cmâ&#x20AC;&#x201C;1 and 2000 cmâ&#x20AC;&#x201C;1 could be attributed to the presence of Siâ&#x20AC;&#x201C;OH and bending vibration absorption of the Oâ&#x20AC;&#x201C; H bond (Ying-Mei et al., 2010).

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The compositions and the densities of the slurries prepared using CFA-Na2SiO3 and com-Na2SiO3 as additives are shown in Table I. The slurries had similar densities, with slight differences as the amount of additive added increased. Some of the slurries containing CFA-Na2SiO3 had slightly lower densities compared to the slurries containing com-Na2SiO3.

There was a 0.02% difference in the densities of the slurries containing 2% additive (CFA-Na2SiO33 and com-Na2SiO3).

The difference may be due to the fact that slurries prepared using CFA-Na2SiO3 contained a lot of froth. The rheologies of slurries prepared using CFA-Na2SiO3 and com-Na2SiO3 as additives are shown in Tables III and IV, respectively. The

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slurries prepared using both additives exhibited good rheology, with plastic viscosities (Pv) between 3.75 and 18.75 cp and yield points (Yp) between 13.5 and 61.75 lb/100 ft2. The slurries containing com-Na2SiO3 generally had higher rheological values than those prepared using the CFA-Na2SiO3. At 60 r/min the viscosity of the slurry containing 1% com-Na2SiO3 was 45 cp, while that for the CFA-Na2SiO3 slurry was 26 cp. The slurries prepared using CFA-Na2SiO3 were less viscous and this can be attributed to the presence of froth.

It is known that the use of sodium silicate as a water extender in OWC operation helps to prevent breakdown of weak formations and loss of circulation (Nelson et al., 1990).

In addition, it helps to lower the hydrostatic pressure, thereby enhances the â&#x20AC;&#x2DC;pumpabilityâ&#x20AC;&#x2122; of the cement slurry (Nelson et al., 1990). When sodium silicate is used as a water extender in OWC operation, it reacts with calcium hydroxide in the cement slurry to produce a viscous C-S-H gel that allows addition of large volume of water to the slurry, thereby

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SiO2 Al2O3 Fe2O3 FeO MnO MgO CaO Na2O K20 TiO2 P2O5 Cr2O3 NiO LOI Sum

57.9 31.12 0.33 2.65 0.04 0.95 4.28 0.13 0.66 1.519 0.39 0.0223 0.0008 0.73 100.72

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Synthesis of sodium silicate from South African coal fly ash reducing the density of the slurry and increasing its yield.

From the results from the rheology analysis of the CFANa2SiO3 prepared from CFA in this study and tested in the formulation of OWC slurries, it is obvious that slurries prepared with CFA-Na2SiO3 might be preferable to those prepared with com-Na2SiO3 for an OWC operation that requires early strength development.

Tables V and VI show the compressive strength results for slurries containing com-Na2SiO3 and CFA-Na2SiO3, respectively. As expected, there was a decrease in compressive strength for all slurries as the amount of water added increased. This is consistent with findings from the literature. An increase in water-to-cement ratio results in a dramatic decrease in the compressive strength of the slurries (Fawzi, 2012), Figures 9â&#x20AC;&#x201C;11 show that the slurries containing CFA-Na2SiO3 had higher compressive strength than those containing com-Na2SiO33 at 8 hours, 12 hours and 24 hours. From Tables V and VI, it can be observed that the CFA-Na2SiO3 slurries gained a compressive strength of 0.34 MPa earlier than the Na2SiO3 slurries. This is the minimum strength required to hold the casing in position. In addition, the earlier gain of the compressive strength by the with CFA-Na2SiO3 slurries indicates that the slurries with CFA-Na2SiO3 set quicker than those with com-Na2SiO3. The results obtained from the ultrasonic cement analyser (UCA)

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also indicate that the same observation was obtained for slurries that attained a compressive strength of 3.4 MPa within the first 24 hours. A strength of 3.4 MPa is sufficient to hold the casing when further drilling or perforation of the casing is required.

3?7;:<@B?7@ The results indicate that the South African CFA used in this study is a Class F CFA and contains 58% amorphous SiO2.

The physico-chemical properties of the synthesized Na2SiO3 are consistent with those of the commercial Na2SiO3, indicating the purity of the as-prepared Na2SiO3 from the CFA. In addition, the synthesis protocol, which was at a mild temperature, confirms the energy efficiency of the method used. Cement slurries prepared with CFA-Na2SiO3 show better performance than those prepared with com-Na2SiO3.

Rheological testing indicated that the slurries prepared with CFA-Na2SiO3 are less viscous than those prepared with comNa2SiO3. The CFA-Na2SiO3 slurries will thus be easier to pump and handle during OWC operation compared to the slurries prepared with com-Na2SiO3. UCA analysis showed that the slurries prepared with CFA-Na2SiO3 have higher compressive strength in comparison to those prepared from the com-Na2SiO3. Although a small concentration of sodium silicate (0.2% to 3.0% BWOC) is always used in OWC operations to yield a reasonable compressive strength (Nelson et al., 1990), the higher compressive strength of the slurries with CFA-Na2SiO3 implies that smaller amounts of CFA-Na2SiO3 will be required for OWC operations. In addition, slurries prepared with CFA-Na2SiO3 will be preferable to those prepared with com-Na2SiO3 for an OWC operation that requires early strength development. The results of this study could provide a platform for further research development on the beneficiation of South African CFA in the petroleum, oil, and gas industry.

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The authors hereby acknowledge the financial support from Chemical Industries Education and Training Authorities (CHIETA) South Africa and Baker Hughes South Africa (Mossel Bay) for availing their cement testing laboratory facility for use in this study.

Synthesis of sodium silicate from South African coal fly ash LEA, F.M. 1971. The Chemistry of Cement and Concrete. Chemical Publishing Company Inc., New York, USA.

C.CAC7;C@ AHMARUZZAMAN, M. 2010. A review on the utilization of fly ash. Progress in Energy and Combustion Science, vol. 36, no. 1. pp. 327â&#x20AC;&#x201C;363.

MAINGANYE, D., OJUMU, T.V., and PETRIK, L. 2013. Synthesis of zeolites Na-P1 from South African coal fly ash: Effect of impeller design and agitation.

Materials, vol. 6. pp. 2074â&#x20AC;&#x201C;2089.

AIGBODION, V.S., HASSAN, S.B., AUSE, T., and NYIOR, G.B. 2010. Potential utilization of solid waste (bagasse ash). Journal of Minerals and Materials Characterization and Engineering, vol. 9, no. 1. pp. 67â&#x20AC;&#x201C;77.

MCDANIEL, G.R. 1961. Wet Production of Silicates. US patent no. US2983423.

AMERICAN PETROLEUM INSTITUTE SPECIFICATION 10A. 2002. Specifications for Cementing and Materials for Well Cementing. ANSI/API 10A/ISO 104261-2001.

MILLER, F.A. and WILKINS, C.H. 1952. Infrared spectra and characteristic frequencies of inorganic ions: their use in qualitative analysis. Analytical Chemistry, vol. 24, no. 8. pp. 1253â&#x20AC;&#x201C;1294.

ASTMC618. 2012. Standard specification for coal fly ash and raw or calcined natural Pozzolan for use in concrete.

MUSIC, S., VINCEKOVIC, N.F., and SEKOVANIC, L. 2011. Precipitation of amorphous SiO2 particles and their properties. Brazilian Journal of Chemical Engineering, vol. 28, no. 1. pp. 89â&#x20AC;&#x201C;94.

AYANDA, O.S., FATOKI, O.S., ADEKOLA, F.A., and XIMBA B. J. 2012.

Characterization of fly ash generated from Matla Power Station in Mpumalanga, South Africa. E-Journal of Chemistry, vol. 9, no. 4. pp. 1788â&#x20AC;&#x201C;1795.

ESSIEN, E.R., OLANIYI O.A., ADAMS L.A., and SHAIBU R.O. 2011. Highly porous silica network prepared from sodium metasilicate. Journal of Metals, Materials and Minerals, vol. 21, no. 2. pp. 7â&#x20AC;&#x201C;12.

FAWZI, R.H. 2012. Thickening time and compressive strength correlations for Bentonitic â&#x20AC;&#x201C;class â&#x20AC;&#x2DC;Gâ&#x20AC;&#x2122; cement slurries. Iraqi Journal of Chemical and Petroleum Engineering, vol. 13, no. 2. pp. 37â&#x20AC;&#x201C;45.

FISHER, G.L., PRENTICE, B.A., SILBERMAN, D., ONDOV, J.M., BIERMANN, A.H., RAGAINI, R C., and MCFARLAND A.R. 1978. Physical and morphological studies of size- classified coal fly ash. Journal of the American Chemical Society, vol.

12, no. 4. pp. 477â&#x20AC;&#x201C;451.

FOLETTO, E.L., GRATIERI, E., HADLICH DE OLIVEIRA, L., and JAHN S.L. 2006.

Conversion of rice hull ash into soluble sodium silicate. Materials Research, vol. 9, no. 3. pp. 335â&#x20AC;&#x201C;338.

IKOTUN, B.D., MISHRA, S., and FANOURAKIS G.C. 2014. Structural characterization of four South African fly ashes and their structural changes with βcyclodextrin. Particulate Science and Technology, vol. 32, no. 4. pp. 360â&#x20AC;&#x201C;365.

IYER, R S. and SCOTT, J.A. 2001. Power station fly ash - a review of value-added utilization outside of the construction industry. Resources, Conservation and Recycling, vol. 31. pp. 217â&#x20AC;&#x201C;228.

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NELSON, E.B., BARET, J.F., and MICHAUX, M.1990. Well Cementing: Cement Additives and Mechanisms of Action. Elsevier, USA.

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Chemistry and Materials Research, vol. 3, no. 4. pp. 68â&#x20AC;&#x201C;72.

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10 pp.

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http://dx.doi.org/10.17159/2411-9717/2015/v115n12a6

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel

by D.E.P. Klenam*â&#x20AC; , C. Poleseâ&#x20AC; â&#x20AC;Ą, L.H. Chown*â&#x20AC; , S. Kwofieâ&#x20AC;Ąâ&#x20AC;Ą, and L.A. Cornish*â&#x20AC;

The effect of surface hardening by pack carburizing on the mechanical properties of AISI 316L steel was studied. Pack carburizing with 60 wt% BaCO3, 30 wt% activated carbon, and 10 wt% sodium chloride was carried out at 450, 550, 650, 700, and 750°C for 24 hours and the specimens were furnace-cooled. Tensile, impact, hardness, and fatigue tests were conducted, and SEM and was used to characterize the specimens.

The ultimate tensile strength of the as-received steel was similar to specimens carburized at 450 and 550°C (approx. 650 MPa), but decreased from 638 to 603 MPa with further increase in carburizing temperature from 650 to 750°C. Hardness profiles of the specimens treated at 450°C and 550°C were similar to the as-received steel, at approximately 250 HV0.5. Typical case hardening profiles were obtained for specimens carburized at 650, 700, and 750°C. The number of cycles to failure (N) of the as-received specimens was close to 60 000, which was similar to those carburized from 450 to 650°C. Further increase in carburizing temperature decreased the cycles to failure to approximately 25 000 (700°C) and 7000 cycles (750°C).

Crack initiation was mainly characterized by cleavage (mode I) for all tested carburized and as-received specimens. Specimens carburized at 450, 550, and 650°C also showed secondary cracking. The final rupture zone contained ductile fracture with dimples, and the specimens showed extensive plastic deformation. < 6;+7 316L austenitic stainless steel, mechanical behaviour, fractography, pack carburizing.

,3:;6+54:863 Austenitic stainless steels are widely used for structural applications in the petrochemical, telecommunication, aerospace, and foodprocessing industries. This is due to their excellent corrosion resistance and good mechanical properties, such as toughness, ductility, and formability (Bain and Griffiths, 1927; Jenkins et al. 1937; Zapffe, 1949).

However, due to the austenitic structure, these steels have quite low surface hardness and poor wear resistance (Bell, 2002; Fewell et al., 2000). To improve the surface properties, diffusion and thermochemical surface treatment techniques such as carburizing (Agarwal et al., 2007; Fewell et al., 2000), nitriding (Bell, 2002), nitro-carburizing (Renevier et al., 1999) and ion implantation (Liang et al., 2007) have been used, without impairing the corrosion resistance of the steel

* School of Chemical and Metallurgical Engineering, University of the Witwatersrand, Johannesburg. â&#x20AC; DST-NRF Centre of Excellence in Strong Materials, University of the Witwatersrand, Johannesburg. â&#x20AC;Ą School of Mechanical, Industrial and Aerospace Engineering, University of the Witwatersrand, Johannesburg. â&#x20AC;Ąâ&#x20AC;Ą Department of Materials Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015 and revised paper received Oct 2015.

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(Bell, 2002; Renevier et al., 1999). The treatment temperatures were kept below 500°C to prevent the formation of chromium carbides and nitrides, which deplete chromium from the matrix and reduce corrosion resistance (Matula et al., 2001).

Little has been reported on the pack carburizing of austenitic stainless steels and its effects on the mechanical properties. This is probably because pack carburizing of these stainless steels is considered a difficult process, due to the presence of the Cr2O3 oxide surface layer (Davis, 1994; Mingolo et al., 2006). The tenacious Cr2O3 surface layer serves as an inhibiting barrier and is also selfhealing, which contributes to the â&#x20AC;&#x2DC;stainlessâ&#x20AC;&#x2122; characteristic of stainless steels. However, it was felt a worthwhile endeavour to ascertain whether this cheaper method could be used.

Other forms of carburizing, such as gas and plasma, are normally used for stainless steel rather than pack carburizing, which is more commonly used for medium- and low-carbon steels (Agarwal et al., 2007; Fewell et al., 2000; Renevier et al., 1999). The major parameters that influence carburizing are soaking time, carburizing temperature, and carbon potential (Shewmon, 1963).

As a high proportion of mechanical failures are due to fatigue, extensive research is being done in this area (Akita and Tokaji, 2006).

Nucleated fatigue cracks grow into macrocracks, resulting in catastrophic failures.

Initiation of fatigue is a surface phenomenon, and approximately 80% of all engineering

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel failures are due to fatigue, which is a cause for concern in surface-modified structures and components (BerrÄąĚ os et al., 2001; BerrÄąĚ os-OrtÄąĚ z et al., 2004). Fatigue behaviour of austenitic stainless steels with their surfaces modified by techniques such as plasma carburizing and nitriding, ion implantation, shot peening, and physical vapour deposition of coatings with TiN, CrN and ZrN has been studied by Ceschini and Minak (2008), Fewell et al. (2000), Agarwal et al.

(2007), Azar et al. (2010), BerrÄąĚ os et al. (2001), Collins et al.

(1995), Liu et al. (2003), Samandi et al. (1993), and BerrÄąĚ osOrtÄąĚ z et al. (2004). Surface hardness, wear resistance, and fatigue strength were improved by most of these techniques (BerrÄąĚ os et al., 2001; BerrÄąĚ os-OrtÄąĚ z et al., 2004; Ceschini and Minak, 2008). Much work has been done on fatigue in stainless steels, but there is no study on pack carburized austenitic stainless steels.

This research was conducted to study the effects of pack carburizing on the mechanical properties and microstructure of AISI 316L stainless steel, and to ascertain which temperatures in the range of 450 to 750°C would provide a suitable carburized case.

. '<;8)<3:9-=';64<+5;< As-rolled AISI 316L stainless steel plates (1000Ă&#x2014;1000Ă&#x2014; 30 mm) containing 17.1 wt% Cr were purchased and the composition was determined by optical emission spectroscopy (Table I).

Flat tensile specimens (dogbone shaped) were machined from the as-received plate in the longitudinal rolling direction according to ASTM E8. The length of each sample was 60 mm with the gauge length of 7 mm and thickness of 12 mm. The fatigue specimens having continuous curvature were machined according to ASTM STP91-A. The dimensions were: gauge length of 23 mm, radius of curvature of 190 mm, and a thickness of 6 mm. The Charpy V-notch specimens (45°, 2 mm deep notched bar of length of 55 mm and 10Ă&#x2014;10 mm thick) were machined according to ASTM A370 (ASTM Standards, 2000). The Charpy V-notch specimens were all notched before the carburizing heat treatment was done. All tests were done in triplicate at all carburizing temperatures.

A container with a lid of dimensions 145Ă&#x2014;80Ă&#x2014;80 mm was fabricated from mild steel for the carburizing heat treatment.

The tensile, fatigue, and Charpy V-notch specimens were pack carburized in the container with 60% BaCO3 (as the energizer), 30% activated charcoal (source of carbon), and 10% NaCl (activator). The carburizing heat treatment was done at temperatures of 450, 550, 650, 700, or 750°C for 24 hours in a LentonŽ muffle furnace, followed by furnace cooling.

Tensile tests were performed according to ASTM E8 using a Tinius OlsenÂŽ tensile testing machine under a uniaxial load.

Fatigue tests were performed according to ASTM STP91-A using an Instron 1342ÂŽ fatigue testing machine. The testing was performed at a peak stress of 500 MPa with a stress ratio R of 0.1 (where R = minimum peak stress / maximum peak stress), stress range of 1, and a frequency of 7 Hz. The fractured sample was cut for secondary electron imaging of the fractured surfaces using a FEI NovaÂŽ NanoSEM 200.

Room-temperature Charpy V-notch impact tests were performed on three impact test samples for each carburizing temperature, according to ASTM A370 (ASTM Standards, 2000). All mechanical tests were performed on pack carburized specimens and on as-received specimens for comparison.

Transverse sections of the carburized and tested samples were prepared metallographically to examine the microstructure from the surface to the centre. The final polishing was done using a colloidal silica suspension on satin woven acetate cloth. The polished specimens were chemically etched using 15 ml HCl, 10 ml HNO3, and 10 ml ethanol for approximately 8 minutes and were then rinsed in alcohol and water. Scanning electron microscopy with EDX was used to study the microstructures of the as-received and the carburized specimens.

Micro-Vickers hardness testing was done on sectioned samples from the surface to the centre of the carburized and as-received steel specimens, using a load of 500 g and a dwell time of 10 seconds. Hardness-depth profiles were then plotted.

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The effects of carburizing on the ultimate tensile strength (UTS) of AISI 316L steel is shown in Figure 1. Within error, the ultimate tensile strength was unchanged at approximately 651 MPa for carburizing temperatures of 450°C and 550°C, which is marginally higher than the as-received steel (648 MPa). Further increase in temperature caused a sharp decrease in UTS to 638 MPa (650°C), 627 MPa (700°C), and 603 MPa (750°C).

The effect of carburizing temperature on ductility is shown in Figure 2. The total elongation was almost unchanged with increasing temperature up to 650°C (46-45% compared to the as-received 49%) and decreased more sharply above 650°C to 32% at 750°C. An increase in temperature had a stronger effect on decreasing the reduction in area (% RA). The RA after carburizing at 450°C was the same as the as-received at 79%, and dropped to 65% at 650°C and 45% at 750°C. The impact energy of the as-received AISI 316L steel was 272 J. After carburizing between 450-750°C, the impact energies decreased with increasing temperature, as shown in

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from the surface (Ceschini and Minak, 2008), with the extent of the case indicated by the position where there is a sudden drop in hardness. At 650°C, there was a negligible increase of approximately 5 HV0.5 in the hardness of the surface compared to the core; and at 700°C and 750°C the increases were approximately 25 HV0.5 and 42 HV0.5 respectively.

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Figure 3, from 257 J at 450°C showing a constant drop in impact energy with increasing carburizing temperature from 550°C (243 J) to 750°C (132 J).

The microhardness measurements for the as-received material varied, with an average surface hardness of 255 HV0.5 and a core hardness of 248 HV0.5. The specimens that were carburized at 450 and 550°C showed only small differences in hardness between the surface and the core, ranging from 246â&#x20AC;&#x201C;255 HV0.5, as shown in Figure 4a. Not all the carburizing compound in the case burnt off, thus carburizing was not properly achieved at these two temperatures. However, the surface hardness did increase nominally with increasing temperature for samples carburized at temperatures of 650, 700 and 750°C (Figure 4b). These specimens showed a hardness profile similar to that found in case hardening, with higher hardnesses at the surface and core hardnesses similar to the as-received material. The case depth is related to the amount of carbon diffused inwards

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel

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and b), showing austenite grains, annealing twins, pores, and some oxides. Figure 5b shows deformation at the sample surface from the rolling process of the as-received steel.

There were prominent grain boundaries and etch pits (as found by Fong and Tromans, 1988) throughout the microstructure. No carbides were found by EDX analysis in the specimens treated at 450°C or 550°C. The passive oxide layer on the surface of the sample carburized at 550°C was approximately 8.0 Οm thick (Figure 6).

The core and near-surface microstructures of the samples carburized at 700°C also showed austenite grains, annealing twins, slip lines, and pores. Grooved grain boundaries were formed at the core and at the near surface. Intergranular oxidation at the surface of the samples (Figures 7a and b) could be possible, but not at the core since the diffusion of oxygen at temperatures of 550â&#x20AC;&#x201C;750°C for 24 hours would be

too sluggish for penetration to the core. The grooved grain boundaries at the core could be attributed to the combined effect of sensitization and etching, which produce similar effects in austenitic stainless steels in the ranges of 450â&#x20AC;&#x201C; 800°C (Agarwal et al., 2007; Ceschini and Minak, 2008).

EDX analyses revealed a higher amount of carbides and oxides near the surface compared to the core (Table II). The thin white layer on the surface (Figure 7b) contained calcium and chloride compounds from the carburizing chemicals and the etchant (Figure 7b). There were more slip lines and smaller grains at approx. 50 Îźm beneath the surface on the near surface (Figure 7b), due to deformation from the finishing rolling.

Micrographs of samples carburized at 750°C (Figures 8a and b) revealed similar microstructural features to the lower temperature treatments in terms of grain size, carbides, oxides, and voids. Both the core and the near surface underwent grain boundary oxidation. There were more pores on grain and sub-grain boundaries and fewer annealing twins (Figure 8) than at lower carburizing temperatures. The carburized layer was measured as approximately 95â&#x20AC;&#x201C;103 Îźm thick (Figure 9). The grain boundaries became more prominent with increased carburizing temperature.

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The effect of carburizing temperature on the fatigue strength of AISI 316L austenitic stainless steel is shown in Figure 10.

The fatigue behaviour of samples carburized at 450 to 650°C was similar to the as-received sample, with 50â&#x20AC;&#x201C;60 thousand cycles to failure (N). Lower cycles to failure were observed at carburizing temperatures of 700°C (N approx. 26 000), and 750°C (N approx. 8 000), indicating decreasing fatigue resistance of the steel with increase in testing temperature.

Visual inspection of the fractured fatigue surfaces identified ratchet marks and â&#x20AC;&#x2DC;thumbnailsâ&#x20AC;&#x2122;, indicating regions of slow growth, where the crack was able to maintain its preferred orientation transverse to the applied stress (Roylance, 2001). Macro-examination showed that the edges of the fractured surface were slightly brighter and shiny, a feature known as small fatigue cracks (Ritchie and Lankford,

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel

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1986; Agarwal et al., 2007; Ceschini and Minak, 2008;). The fractured surfaces of samples carburised at 450, 550, and 650°C showed more secondary cracking and fatigue pre-

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel cracks along the sides than samples carburized at 700 and 750°C. SEM examination of the fractured surfaces of all samples showed the crack initiation, propagation, and rupture zones.

Cleavage was the characteristic feature of the crack initiation zone (around the edge of the fatigue specimen), with secondary cracking (indicated by an arrow in Figure 11a) for samples carburized at 450°C. The initiation zones showed brittle cleavage, which is a characteristic feature of fatigue crack initiation zones (Fong and Tromans, 1988). The crack propagation zone in Figure 11b shows areas of fatigue striations at regions around the core. The final rupture for the as-received sample was ductile fracture with dimples and micro-voids nucleated within the surface (Figure 11c).

After carburizing at 650°C, the crack initiation stage was characterized by cleavage and dispersed secondary cracking, as shown in Figure 12a. As the cracks propagated, fatigue striations were also found on the fracture surface (Figure 12b). At lower magnification (Figure 12c), the rupture zone showed a step-like pattern. Fractographs of samples carburized at 700 and 750°C (not shown) displayed similar characteristic features to those treated at the lower temperatures.

The fracture surfaces of the Charpy test samples were analysed using SEM. The as-received samples (Figure 13a) and samples carburized at 450°C (Figure 13b) and 550°C

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showed dimples and microvoid coalescence, which are characteristic of ductile fracture. After carburizing at 650, 700, and 750°C, the fracture surface showed evidence of transgranular brittle fracture. This is shown in Figure 13c for the sample carburized at 750°C.

874577863 When compared to the as-received sample, carburizing the AISI 316L steel at 450°C slightly improved the ultimate tensile strength, caused marginal decreases in ductility (both elongation and reduction in area), and was detrimental to toughness. At 550°C, the ultimate tensile strength was the same as for 450°C, but the ductility and toughness were lower. Above 550°C, these bulk mechanical properties were compromised, as shown by the incremental loss of ultimate tensile strength, ductility, and toughness with increasing carburization temperature. This was due to the increased coarsening of grain boundary carbides (Fong and Tromans, 1988).

Micrographs of all carburized specimens showed intergranular voids and oxidation along the grain and subgrain boundaries. These defects are potential nucleation sites for cracks (Zavattieri and Espinosa, 2001). Uniaxial tension around these defects could lead to crack opening and the oxides can act as brittle zones (King and Cotterill, 1990), decreasing ductility and toughness of the AISI 316L steel. At

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450 and 550°C, strengthening from carbon uptake was slightly more beneficial than the negative effect from intergranular oxidation, as seen by the higher tensile strength values.

The amount of carbon that diffused into the steel at 450 and 550°C was too low to significantly increase the surface hardness (Figure 4a). Pores and annealing twins in the austenitic microstructure caused the slight variations in the hardness of these samples and the as-received material. The tenacious, self-healing 8.0 Οm thick Cr2O3 layer that formed on the steel surface prevented an increase in surface hardness, as these carburizing temperatures and times were insufficient for carbon to diffuse through this inhibitive

surface layer. In contrast, the plasma and gas carburizing processes produce permeable oxide layers, which allow enough carbon diffusion into the steel (Renevier et al., 1999; Fewell et al., 2000; Bell, 2002). Thus, high hardness values can be obtained by these processes.

Samples treated at higher temperatures of 650 to 750°C showed hardness profiles similar to those achieved by case hardening, with higher hardness at the surface and core hardness values similar to that of the as-received steel. The highest surface hardness was 294 HV0.5 (750°C), which is 18% higher than the core hardness. This indicates a moderate intake of carbon and surface carbon enrichment from the carburizing treatment, which also contributed to the decrease in the ductility and toughness. The presence of twins could also increase the hardness, although the annealing twins were fairly well-distributed throughout the steel and were not concentrated towards the surface. Twin boundaries are known to impede dislocation motion (Lu et al., 2009), which would also contribute to the hardness.

However, the main contribution to the higher near-surface hardness was the increasing carbon content from the core to the surface of the stainless steel.

Surface hardnesses of up to 1400 HV have been reported for plasma and gas carburized AISI 316L steel (Fewell et al., 2000; Mingolo et al., 2006). This is substantially higher than the maximum of 294 HV0.5 found for the pack carburized samples in this work. The very high surface hardnesses from these carburizing methods can be attributed to high compressive residual stresses from lattice distortion by interstitial carbon, facilitated by the diffusion of carbon through the permeable surface oxide (Fewell et al., 2000; Mingolo et al., 2006).

In XRD spectra, shifts in the austenite peaks to lower diffraction angles indicate compressive residual stresses, which usually improve the mechanical properties (Mingolo et al., 2006). However, the XRD patterns of the carburized samples in this work (not shown) did not display shifts in the austenite peaks. This indicates that there was little interstitial carbon uptake, no substantial change in lattice size occurred, and that negligible compressive residual stresses were induced. A 4% by volume content is required to reliably detect a phase by XRD (Liu, 2006), and the small amounts of carbides and oxides identified by EDX were below this limit. Carbides, which can be detrimental to the corrosion resistance of the AISI 316L steel (Bell, 2002), were present in small amounts in both as-received and carburized samples, as shown by the precipitation at the grain boundaries and within the grains. There was only a very thin observable carburized case.

The number of cycles to failure for the as-received AISI 316L steel and samples carburized from 450â&#x20AC;&#x201C;650°C ranged from approximately 52 000 to 61 500 (Figure 10), showing that the fatigue resistance was similar. As the carburizing temperature increased above 650°C, the number of cycles to failure decreased significantly: approximately 26 000 at 700°C and 7 100 at 750°C. Although carburizing at temperatures above 650°C has been reported to lead to stress relief of the compressive stresses and a significant decrease in fatigue strength (Gelfi et al., 2005; Ceschini and Minak, 2008), here the surface had already been removed by the machining of the fatigue samples. Thus, the decrease in the

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel fatigue strength is more likely to be due to the coarsening of carbides on the grain boundaries at higher carburizing temperatures, which would then have less effect in reducing the initiation and growth of fatigue cracks. Also, the oxides and voids act as imperfections in the material, which could also have been a contributing factor (Lampman, 1997).

The fractured surfaces of the as-received and all of the carburized samples showed cleavage fracture at the initiation stage. SEM examination of the as-received steel fracture surface showed that crack initiation occurred at the surface, which could be attributed to the cyclic and fatigue slip bands (Ceschini and Minak, 2008). Fatigue slip bands, also called persistent slip bands (PSBs), are zones of high cyclic slip activity (Lukåť and Kunz, 2004). The cyclic plastic deformation within PSBs result in surface extrusion and intrusion along the traces of the active slip plane, and fatigue micro-cracks start from these surface intrusions. The initiation of these cracks is also attributed to surface defects such as machining lines, notches, and stress concentration sites (Akita and Bell, 2002; Tokaji, 2006; Agarwal et al., 2007). Cleavage is a Mode I type of fracture, in which shear stresses act parallel to both the crack front and the plane of the crack (Yates and Mohammed, 1996; Tvergaard, 2008; De Freitas et al. 2011). The as-received and the carburized samples up to 650°C exhibited acceptable ductility, higher than 65% RA and 45% elongation. Above 650°C, cleavage was observed, which could be attributed to loss in ductility and toughness due to the coarsening of the grain boundary carbides.

Brittle fracture is characterized by quasi-cleavage, low release energy, and minimal plastic deformation (Hull, 1999).

These features were absent in the fractured surfaces of the as-received and carburized samples. The increased carburizing temperature enhanced the formation of brittle carbides and grain boundary oxides (Zavattieri and Espinosa, 2001), contributing to the decreased ductility and cleavage of the carburized samples at the crack initiation zones. The fractures originated on the surfaces of the samples, and propagated towards their cores.

The crack propagation zones in all fatigue specimens showed striations, beach marks, and a few secondary cracks, all characteristic features of fatigue failure (Akita and Tokaji, 2006; Bell, 2002). Striations can be attributed to microdepressions induced in the structure, with the plane normal to the fracture surface, confirming the hollow micro-relief of fatigue striations (Grosskreutz and Waldow, 1963; Ceschini and Minak, 2008). The formation of striations was also due to decohesion along the sub-grain boundaries and possible initiation sites for secondary cracking (Jin-Bo and Chen, 1988; Yang et al., 2008). Secondary cracks are formed by increased stresses due to voids, and occur at sites where there are micro-stress raisers and material defects during crack propagation (Jin-Bo and Chen, 1988). Twinning is caused by continuous mechanical deformation, which leads to discontinuity on the surface of the material, hence creating a site for crack nucleation when stress or strain is applied (James, 1981). Secondary cracks formed along twin bands and propagated below the primary fracture surface (Yang et al., 2008).

The final rupture zones of the as-received and carburized samples showed more ductile dimple rupture than brittle fracture. Ductile dimple rupture occurred by the formation

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and coalescence of micro-voids along the fracture path. There were faceted patterns within the fractures, suggesting incremental tearing, which could be due to either chemical or microstructural segregation patterns (Gao et al., 1995).

Fractured surfaces of the as-received AISI 316L and samples carburized at 450°C and 550°C showed predominantly ductile fracture, with dimples, microvoid coalescence, and an irregular and fibrous surface, which indicated plastic deformation (Hull, 1999). The dimples on the crack surface are attributed to dislocation movements, which coalesce into grain boundary voids. The carbon diffusion was low and could not cause a major change in the microstructure, nor in the ductility, at these temperatures. At 650°C and above, the fracture appearance was more brittle, with more faceting, which is a characteristic feature of transgranular fracture (Hull, 1999). The Charpy toughness is a bulk material property and the carburizing effect was very shallow, in the order of 100 ¾m. Therefore, reduced Charpy toughness could not be attributed to the carburizing effect, but rather attributed to the coarsening of grain boundary carbides, which is known to cause a decrease in toughness for austenitic stainless steels (Fong and Tromans, 1988).

The tensile behaviour was more sensitive to carburization than the fatigue behaviour. The tensile and fatigue specimens had different geometries, but this probably did not have a major effect, as the thicknesses were within 1 mm. All test pieces were mixtures of carburized layers and non-carburized cores, and the different proportions of these would have had an effect on mechanical properties. The tensile specimens were slightly thicker (7 mm diameter) than the fatigue specimens (6 mm thickness), and the surface to volume effect of the specimens would have meant that the proportion of the carburized layer of the fatigue specimens was slightly higher, due to their flat, rectangular cross-sections. However, since fatigue is a surface phenomenon, it would not be affected by the proportions of carburized to non-carburized material, although the tensile specimens would be affected. For tensile (and impact) tests and fatigue tests, the cracks initiated at different positions. Cracks initiated at the surface of the fatigue specimens, with some secondary cracks found on the sub-surfaces, whereas cracks initiated within the core of tensile and impact (around the notches) specimens. Thus, the decreased impact toughness and UTS of the carburized steel could be attributed to the brittle carbides and oxides that formed during carburizing, resulting in coarse grains (Figures 5â&#x20AC;&#x201C;8) allowing for easy crack propagation.

From this work, pack carburizing was shown to be unsuitable for AISI 316L stainless steel, as the process significantly reduced the ductility, ultimate tensile strength, and impact toughness. The plasma and gas carburizing techniques, in contrast, are known to considerably improve mechanical properties.

"634-578637 Surface hardness was unchanged at carburizing temperatures of 450 and 550°C, but increased with increasing temperature above 550°C due to intergranular and intragranular carbide precipitation.

An increase in pack carburizing temperature to 650, 700, or 750°C adversely influenced the mechanical properties of AISI 316L austenitic stainless steel by decreasing the ductility, toughness, tensile strength, and fatigue resistance.

Mechanical behaviour of pack carburized AISI 316L austenitic stainless steel The mode of failure was mostly cleavage, fatigue failure, and ductile dimples, with some secondary cracking from microvoid coalescence.

In summary, the process of pack carburizing at or above 650°C was found to be unsuitable for increasing the fatigue resistance of AISI 316L austenitic stainless steel, and carburizing below 650°C gave no benefit.

!4 36 -<+0<)<3:7 The authors thank the Department of Science and Technology and the National Research Foundation, South Africa for providing funding for this research. They also thank Mr Richard Couperthwaite of the Advanced Materials Division, Mintek, for help with the SEM imaging and analysis.

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Materials Science and Engineering A, vol. 491, no. 1-2. pp. 131â&#x20AC;&#x201C;136.

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2â&#x20AC;&#x201C;3. pp. 263â&#x20AC;&#x201C;268.

YATES, J.R. and MOHAMMED, R.A. 1996. The determination of fatigue crack propagation rates under mixed mode (I+III) loading. International Journal of Fatigue, vol. 18, no. 3. pp. 197â&#x20AC;&#x201C;203.

ZAPFFE, C.A. 1949. Stainless Steels. American Society for Metals, Materials Park, Ohio.

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12. pp. 1407â&#x20AC;&#x201C;1422.

http://dx.doi.org/10.17159/2411-9717/2015/v115n12a7

Making sense of our mining wastes: removal of heavy metals from AMD using sulphidation media derived from waste gypsum

by J. Mulopo*

This study investigates the recovery of water and THE selective removal of valuable metals from acid mine drainage (AMD) using sulphidation media (CaS) derived from waste gypsum. AMD systems containing Fe(II), Ni, Co, Zn, and Pb were investigated using CaS produced from the carbothermal reduction of Anglo Coal waste gypsum at 1025°C to precipitate metals as insoluble metal sulphides. The results show a sulphidation dependence on the pH, sulphide dosage, and metal concentration. The selective sulphidation of metals also showed significant dependence on the respective metal sulphide solubility order as a function of pH. According to the Department of Environmental Affairsâ&#x20AC;&#x2122; South African Waste Information Centre, over 42 million cubic metres of general waste is generated every year in South Africa and mining waste is by far the biggest contributor to the solid waste (about 72%)). Although alarming, these vast quantities of waste also present an opportunity for integrated economic development, particularly in the recycling sector. The major argument has always been that the mining sector generates a large number of waste streams which show strong differences in time, in their treatment methodologies, or even in their spatial distribution. This paper presents a case of a simple strategy for integrated recycling of two mining waste streams and highlights the need for the mining industry to break away from the traditional â&#x20AC;&#x2DC;linearâ&#x20AC;&#x2122; cul-de-sac disposal of wastes and think of new sustainable ways of waste management.

B) >95: acid mine drainage, waste gypsum, CaS, metals removal.

<@9>537@?>< Gypsum is a waste product generated by various industries, such as the mining, power generation, and fertiliser industries. For instance, phosphate fertilizer production using the â&#x20AC;&#x2DC;wet processâ&#x20AC;&#x2122; generates phosphoric acid which in turn generates around 4.5 t of waste gypsum per ton of phosphoric acid. Foskor, the only current producer of phosphoric acid in South Africa, operates a fertilizer complex at Richards Bay with a capacity of 780 000 t/a of phosphoric acid (http://www.sulphuricacid.com/sulphuric-acid-on-the-web/). The waste gypsum generated at this plant is pumped into the sea, representing a lost opportunity partially due to the lack of waste gypsum beneficiation or treatment. A total of 55â&#x20AC;&#x201C;70 Mt of waste gypsum is currently stockpiled in South Africa at various sites, and indications are that the amounts of waste gypsum generated in South Africa are going

+0 ,$C//*CC

CaSO4(s) + 2C(s) CaS(s) + 2CO2

[1]

CaSO4(s) + 4CO CaS(s) + 4CO2

[2]

CaSO4(s) + 2H2 CaS(s) + 4H2O

[3]

Wastewater containing toxic as well as valuable metals is discharged as acid mine drainage (AMD) in major mining and industrial operations. This has led to a sharp increase in metal contamination of water reserves and a potential risk of decant water

* University of the Witwatersrand, Sustainable Environment and Energy Research Group, School of Chemical and Metallurgical Engineering, Johannesburg, South Africa. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015 and revised paper received Oct. 2015.

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to increase substantially in the future as a result of the treatment of acid minewater and of flue gases in coal-burning operations.

Disposal of waste gypsum to landfill is not a viable option due to the shortage of landfill space and the formation of hazardous and toxic gaseous emissions in the form of hydrogen sulphide (H2S), when gypsum is landfilled with biodegradable wastes.

Moreover, legislative requirements for landfill disposal methods, such as the National Environmental Management Waste Act (NEMWA) 59 of 2008, are projected to be more stringent in future, resulting in the need to develop alternative waste management approaches. Previous studies have shown the potential of thermal reduction of waste gypsum at 900 to 1100°C to produce calcium sulphide (CaS) using reducing agents, including solid carbon materials such as coal or activated carbon (Equation [1]) (Kato et al., 2012; Ma et al., 2011; Mihara et al., 2008; Nengovhela et al., 2007), carbon monoxide gas (Equation [2]) (Miao et al., 2012; Zhang et al., 2012; Tian and Guo, 2009; Li and Zhuang, 1999), or hydrogen gas (Equation [3]) (Ning et al., 2011):

Making sense of our mining wastes: removal of heavy metals from AMD

1>=;>:?@?><C>4C@2BC#<68>C1>A8C A:@BC6);:3=CA:C5B@B9=?<B5C )C "CA<A8):?: Cr %

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0.027

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8.200

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from closed mines is looming in the Western, Central, and Eastern basins of the Witwatersrand, South Africa. Because of their toxicity, any of these metals in excessive quantities will adversely interfere with many beneficial uses of the water, such as human consumption and crop irrigation.

Current methods for the removal of heavy metals from wastewater generally require the use of chemical reagents for precipitation of these metals from solution. For instance, lime could be used to precipitate soluble metals in their insoluble hydroxide forms in an alkaline environment (Barnes et al., 1986). Other methods used for removal of metals from AMD include coagulation-flocculation, electro-coagulation, cementation, membrane separation, membrane filtration, solvent extraction, ion exchange, adsorption, and biosorption (Meunier et al., 2006; Kurniawan et al., 2006).

Among these methods, chemical precipitation with NaOH or Ca(OH)2 followed by filtration is by far the most widely used process to remove metals from wastewater. However, the major setback with hydroxide precipitation lies in the difficulty of efficiently dewatering the sludge, which leads to generation of enormous volumes of hydroxide sludge.

Other treatment methods such as sulphidation have attracted several researchers (Tokuda et al., 2008; Lewis et al., 2006; Maruyama et al., 1975; Kim, 1980; Bhattacharyya et al., 1979, 1981). The use of sulphidation media derived from waste gypsum as sulphide sources for metal precipitation has been reported by Mihara et al. (2008) and Soya et al. (2008) as a recycling process for gypsum boards in Japan.

This study considers the use of CaS produced by carbothermal reduction of waste gypsum for the treatment of AMD in an attempt to integrate the treatment of two waste streams that poses major challenges to the South African mining industry.

,A@B9?A8:CA<5C=B@2>5:

Waste gypsum from Anglo Coal (Landau Colliery) (Figure 1) was collected. XRD analysis showed that the sample contained 33.65% CaO, 51.38% SO3, 5.02% MgO, 0.02% Na2O, 0.15% P2O5, 0.03% Fe2O3, 0.01% Al2O3, and 0.01% SiO2. The waste sludge was sized to less than 250 Îźm. X-ray

â&#x2013;˛

1194

+0 ,$C//*CC

fluorescence (XRF) analysis was also used to identify the elemental composition in waste gypsum samples. Table I shows the trace metal contents in weight (%) or ppm.

Industrial coke from George (South Africa) was used for thermal treatment with composition 60.1% fixed carbon, 2.8% moisture, 10.5% ash content, and 26.7% volatile matters. Acid minewater was collected from Shaft 8, or Winze 18, Harmony Gold Mine (Table II) and the Navigation Coal Mines (Table III). The sulphide precipitation agent (CaS) was obtained by the reductive decomposition of the waste gypsum.

A tubular furnace consisting of a 750 mm long, 24 mm diameter mullite tube mounted horizontally and equipped with a temperature controller was used for the thermal reduction of waste gypsum to calcium sulphide. All precipitation experiments were carried out in 1 litre batch plastic beakers equipped with overhead stirrers fitted with radial turbine impellers. A Metrohm 691 pH meter was used to monitor and measure pH. A Perkin Elmer Analyst 700 atomic absorption spectrometer was used to determine Pb, Zn, Ni, and Co.

12B=?7A8C7>=;>:?@?><C>4C@2BC(A9=><)C >85C,?<B A@B9 A9A=B@B9

"BB5C =6.0

pH Sulphate Chloride Free acid Sodium Potassium Magnesium Calcium Pb Manganese Iron(II) Aluminium Zinc Nickel Cobalt

3.1 4510 37 500 96 3 113 559 16 174 1196 6 49 43 85

Making sense of our mining wastes: removal of heavy metals from AMD to give a total of 1 L mixture and batch equilibrium removal experiments were run at appropriate pH values using a pH cascading approach. The metal removal batch experiments were carried out for at least 5 minutes at a particular pH or until a steady pH was attained. At each pH used a 50 ml sample was collected, filtered using Whatman 12.5 cm qualitative filter papers, acidified with 2.5 ml concentrated HCl, and left overnight to drive out any residual sulphide and preserve the metals. A portion of the sample was used for Fe(II) determination while the rest of the sample was used for the determination of Pb, Zn, Ni, and Co by AAS. The residue was submitted for XRD analysis using a PANalytical Xâ&#x20AC;&#x2122;Pert Pro powder diffractometer with Xâ&#x20AC;&#x2122;Celerator detector and variable divergence and fixed receiving slits with Fe-filtered Co-KÎą radiation on a back-loading preparation method. The phases were identified using Xâ&#x20AC;&#x2122;Pert Highscore Plus software.

12B=?7A8C7>=;>:?@?><C>4C@2BC A%?6A@?><C1>A8C,?<B A@B9 <?@: pH Acidity Alkalinity Sulphate Aluminium Calcium Fe (II) Co Ni Pb Zinc

mg/L CaCO3 mg/L CaCO3 mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L

3.00 700 0 3200 43 447 840 75 93 0.09 75

B:38@:CA<5C5?:73::?>< The extent of metal sulphide precipitation in multi-metal systems such as AMD is expected to be a function of pH, reaction time, initial metal concentration, sulphide dosage, and the presence of chelating agents and other interfering ions. With some metals such as nickel and cobalt, the precipitation is also dependent on the reactor system (closed or open). The effect of pH on solubility can be used to separate metal ions by sulphide precipitation. Many metal sulphides are insoluble in water but dissolve in acidic solution.

Qualitative analysis uses this change in solubility of the metal sulphides with pH to separate a mixture of metal ions.

Hydrogen sulphide is a stronger acid than water, ionizing in water as a diprotic acid according to Equations [4] and [5]:

"?639BC/C C 2>@>69A;2C>4C@2BC#<68>C1>A8C A:@BC6);:3=

H2S(aq) + H2O(l) H3O+(aq) + HS-(aq); Ka1 = 8.9 Ă&#x2014; 10-8

[4]

HS-(aq) + H2O (l) H3O+(aq) + S2-(aq); Ka2 = 1.2 Ă&#x2014; 10-13

[5]

-

The ionization forms bisulphide ion, HS , and sulphide ion, S2-, which can combine with the metal ions to precipitate the metal sulphides. However, the S2â&#x20AC;&#x201C; ion is a strong base (Kb approx. 105) and will react immediately to form HSâ&#x20AC;&#x201C; and a hydroxide ion. The true concentration of S2â&#x20AC;&#x201C; in solution therefore is negligible.

By adjusting the pH in an aqueous solution, one can adjust the sulphide ion concentration in order to precipitate the least soluble metal sulphide while maintaining the other metal ions in solution. For instance, the solubility product constant of lead (II) sulphide is much smaller than that of zinc sulphide, therefore lead sulphide will be expected to precipitate before zinc sulphide.

In order to investigate the interactions between different metal ions and observe the possible differences in individual metal sulphide precipitation in typical AMD wastewater containing Pb, Zn, Ni, Co, and Fe(II),

The two AMD samples were submitted for Pb, Zn, Ni, and Co analysis by atomic absorption spectrometry (AAS) in accordance with the Standard Methods for the Examination of Water and Wastewater (APHA, 1992). Fe(II) in the AMD was determined in-house by iodometry. The amount of CaS required to remove the metals from the AMD was calculated from the total metal analyses using a sulphide/total metal ratio of 1.0.

CaS was produced by carbothermal reduction of waste gypsum in a muffle furnace at a temperature of 1025â&#x20AC;&#x201C;1030°C for 45 minutes using a C/CaSO4 molar ratio of 2. The CaS yield was about 78%, as shown in Table IV. The effect of sulphide addition to the AMD system was investigated using sulphide/total metal mole ratios of 0, 0.5, 0.75, 1.0, 1.5, 2.0, and 2.5. Appropriate amounts of CaS were added to the AMD

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CA<A8):?:C>4C1A'C;9>537B5C )C@2BC@2B9=A8C9B537@?><C>4C6);:3=C

Making sense of our mining wastes: removal of heavy metals from AMD

The pH values required for selective sulphidation of Pb, Zn, Ni, Co, and Fe (II) in typical AMD wastewater were determined based on the results reported by previous workers (Soya et al., 2008). The basis of metal sulphide solubility as a function of pH was also taken into consideration. In this regard, the pH range 3.0â&#x20AC;&#x201C;10.0 was targeted for selective sulphidation of Pb, Zn, Ni, Co, and Fe(II) in AMD wastewater.

The selective sulphidation of the various metals was carried out using a pH cascade approach. Figures 2 and 3 show the change in Zn, Ni, Co, and Fe (II) concentrations in the filtrate.

For reasons of clarity, the results for Pb are not plotted. It can be seen that the Zn concentration was reduced to a value below 1.0 mg/L for all AMD wastewaters studied at a molar ratio of sulphide to Zn of about 1.0. As the pH increased, selective removal of Ni was achieved at an average pH range of 5.0â&#x20AC;&#x201C;7.0. From Figures 2 and 3, it can be seen that Ni is 90% removed at pH 5.0 from Harmony AMD and at pH 7.0 from Navigation AMD. To achieve the same removal efficiency, both the Harmony would require a pH value of

"?639BC C C$44B7@C>4C;(C><C:B8B7@?%BC9B=>%A8C>4C=B@A8:C49>=C B 7A:@8B #, C?<CAC;(C7A:7A5BCB ;B9?=B<@C *C=?<3@B: C9BA7@?><C@?=BC;B9C3<?@C;( <?@?A8C=B@A8C7><7B<@9A@?><:C B9BC *C=6.0C <&C C=6.0C ?&C *C=6.0C1>& A<5C !

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6.0. The next metal to be removed from AMD was Co. Figures 2 and 3 show that Co is more than 80% removed at pH values above 7.0 for from Navigation AMD, while for the Harmony AMD the same removal is achieved at a lower pH of slightly greater than 4.0. Figures 2 and 3 show that significant Fe(II) removal occurs only at pH values higher that around 6.0 .

To achieve 90% Fe(II) removal, the pH of the AMD wastewater had to be increased to an average of 8.0. Fe(II) is removed to less than 50 mg/L at pH 9.0 from both types of AMD wastewater used in this study. At this pH, more than 99% of the Zn, Ni, and Co have already been completely removed.

Despite using an open reactor system, which is prone to atmospheric oxidation, no evidence for nickel sulphide and cobalt sulphide dissolution was observed. This could be due to the short retention times for the metal sulphide residue in the AMD wastewater.

The selective removal data trends for the two AMD wastewaters studied indicate the critical role of metal sulphide solubility and pH on the removal efficiency. The solubilities of the metal sulphides under consideration are in the order PbS < ZnS < NiS < CoS < FeS. In this regard, the least soluble metal sulphides (PbS and ZnS) are precipitated first while the most soluble metal sulphide (FeS) is precipitated last in a pH cascade experiment. NiS and CoS, with comparable solubilities, are removed within a narrow pH range. From these results, it was also inferred that under low pH conditions (pH < 4.0), H2S(aq) was the predominant species (GarcĂ­a-Calzada et al., 2000; Peters et al., 1985), and part of the H2S is released from the solution as H2S gas due to the poor precipitation of the metal sulphides in an acidic solution. Moreover, from molecular orbital theory, the highest occupied molecular orbital (HOMO) for HSâ&#x20AC;&#x201C; has been calculated to be â&#x20AC;&#x201C;2.37 eV, which compares well with the experimental value of â&#x20AC;&#x201C;2.31 eV (Drzaic et al. 1984; Radzig and Smirnov 1985). The HOMO for HSâ&#x20AC;&#x201C; is less stable than that for H2S (â&#x20AC;&#x201C;10.47 eV), indicating that HSâ&#x20AC;&#x201C; is more nucleophilic and basic than H2S, which is consistent with the observed reactivity for metal sulphide precipitation observed in this study. Thus, H2S is not a strong electron donor because the HOMO is so stable.

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â&#x2013;˛

1196

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Figure 4 shows the changes in the Pb, Zn, Ni, Co, and Fe(II) concentrations in filtrates obtained from Harmony AMD wastewater at different sulphide to total metal molar ratios over a period of 90 minutes. The order of metal removal follows the order of solubility of the respective metal sulphides, with the least soluble metal sulphide precipitated first. In the case of Pb, Zn, Ni, and Co, it can be seen that the metal concentrations in the filtrate were reduced to below 5% using a sulphide to total metal ratio of 1.0. In contrast, at this same sulphide to total metal molar ratio, less than 80% of Fe(II) is removed. At a sulphide to total metal ratio of 1.5, Pb, Zn, Ni, and Co in the filtrate were reduced to a value below 1.0 mg/L, representing more than 99% metal removal. Less than 40% of the Fe(II) was removed using this sulphide to total metal molar ratio. Thus the addition of the CaS agent at a sulphide to total metal ratio of 2.0 was necessary to achieve more than 70% Fe(II) removal in the filtrate.

The poor Fe(II) removal at sulphide to total metal ratios of 1â&#x20AC;&#x201C;1.5 can be explained in two ways. Firstly, Fe(II) forms the least soluble metal sulphide compared to all the other metals,

Making sense of our mining wastes: removal of heavy metals from AMD DRZAIC P.S., MARKS J., and BRAUMAN J.I. 1984. Electron photo-detachment from gas phase molecular anions. Gas Phase Ion Chemistry, vol. 3. pp. 167â&#x20AC;&#x201C;211.

GARCĂ?A-CALZADA, M., MARBĂ N, G., and FUERTES, A.B. 2000. Decomposition of CaS particles at ambient conditions. Chemical Engineering Science, vol. 55. pp.1661â&#x20AC;&#x201C;1674.

KATO, T., MURAKAMI, K., and SUGAWARA, K. 2012. Carbon reduction of gypsum produced from flue gas desulphurization. Chemical Engineering Transactions, vol. 29, no. 11. pp. 805â&#x20AC;&#x201C;810.

KIM, B.M. 1980. Treatment of metal-containing wastewater with calcium sulphide. AIChE Symposium Series 77. pp. 39â&#x20AC;&#x201C;48.

KURNIAWAN, T.A., CHAN, G.Y.S., LO, W.H., and BABEL, S. 2006. Physiochemical treatment techniques for wastewater laden with heavy metals. Chemical Engineering Journal, vol. 118. pp. 83â&#x20AC;&#x201C;98.

LEWIS, A. and VAN HILLE, R. 2006. An exploration into the sulphide precipitation method and its effect on metal sulphide removal. Hydrometallurgy, vol.

81. pp. 197â&#x20AC;&#x201C;204.

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C=6.8C"B &C/ C=6.8C ?&C/ C=6.8C1>&C/ C=6.8C <&CA<5C ! =6.8C C

Pb, Zn, Ni, and Co. In this regard, FeS is not expected to precipitate at pH values lower than 5.5, as shown by the pH profile for the sulphide to total metal ratios of 1.0â&#x20AC;&#x201C;1.5.

Secondly, rapid precipitation of both PbS and ZnS on the CaS particles could have brought about encapsulation of unreacted CaS inside the PbS and ZnS particles. As a consequence, a higher molar ratio of CaS to total metal was needed to achieve more than 70% removal of Fe(II) in the filtrate. Similar CaS encapsulation by CuS precipitation at low pH has been reported by Soya et al. (2008).

1><783:?><: The sulphidation behaviour of Fe (II) using CaS derived from waste gypsum as a sulphidation agent was investigated, together with the possibility of selective precipitation of Pb, Zn, Ni, Co, and Fe(II) from various AMD solutions. It was found that Pb, Zn, Ni, and Co can be removed as metal sulphides at lower pH values while Fe(II) stays in solution â&#x20AC;&#x201C; enabling the ferrous iron to be separated from the other metals, which is a great advantage for metal recovery.

Selective metal removal and recovery as metal sulphides may be achieved conveniently using CaS as the sulphidation medium. However the purity of CaS obtained by the thermal reduction of waste gypsum and mass transfer limitations associated with the AMD-CaS system may be critical for process development. Moreover, the settling characteristics of the precipitates are poor, but this could probably be improved by the use of an anionic polymer at low pH.

B4B9B<7B: APHA. 1992. Standard Methods for the Examination of Water and Waste Water. 19th ed. American Public Health Association, Washington DC. BARNES, D., BLISS P.J., GOULD B.W., and VALLENTINE, H.R. 1986. Water and Wastewater Engineering Sytems. Longman Scientific and Technical, UK.

LI, H.J. and ZHUANG, Y.H. 1999. Catalytic reduction of calcium sulphate to calcium sulphide by carbon monoxide. Industrial and Engineering Chemistry Research, vol. 38, no 1. pp. 3333â&#x20AC;&#x201C;3337.

MA, L., NIU, X., HOU, J., ZHENG, S., and XU, W. 2011. Reaction mechanism and influence factors analysis for calcium sulphide generation in the process of phospho-gypsum decomposition. Thermochimica Acta, vol. 526, no 1â&#x20AC;&#x201C;2. pp. 163â&#x20AC;&#x201C;168.

MARUYAMA, T., HANNAH, S.A., and COHEN, J.M. 1975. Metal removal by physical and chemical treatment processes. Journal of the Water Pollution Control Federation, vol. 47. pp. 962â&#x20AC;&#x201C;975.

Meunier, N., Drogui, P., Montanâ&#x20AC;&#x2122;e, C., Hausler, R., Mercier, G., and Blais, J.F. 2006. Comparison between electro-coagulation and chemicals precipitation for metals removal from acidic soil leachate. Journal of Hazardous Materials, vol. 137, no 1. pp. 581-590.

MIAO, Z., YANG, H., WU, Y., ZHANG, H., and ZHANG, X. 2012. Experimental studies on decomposing properties of desulphurization gypsum in a thermogravimetric analyzer and multiatmosphere fluidized beds.

Industrial and Engineering Chemistry Research, vol. 51, no 15. pp. 5419â&#x20AC;&#x201C;5423.

MIHARA, N., SOYA, K., KUCHAR, D., FUKUTA, T., and MATSUDA, H. 2008. Utilization of calcium sulphide derived from waste gypsum board for metalcontaining wastewater treatment. Global NEST Journal, vol 10, no 1. pp. 101â&#x20AC;&#x201C;107.

NENGOVHELA, N.R., STRYDOM, C.A., MAREE, J.P., OOSTHUIZEN, S., and THERON, D.J. 2007. Recovery of sulphur and calcium carbonate from waste gypsum.

Water SA, vol. 33, no 5. pp. 741â&#x20AC;&#x201C;747.

NING, P., ZHENG, S.C., MA, L.P., DU, Y.L., ZHANG, W., NIU, X.K., and WANG, F.Y. 2011. Kinetics and thermodynamics studies on the decompositions of phospho-gypsum in different atmospheres. Advanced Materials Research, vol. 162, no. 1. pp. 842â&#x20AC;&#x201C;848.

PETERS R.W. and KU Y. 1985. Batch precipitation studies for heavy metal removal by sulfide precipitation. AIChE Symposium Series, vol. 81. pp. 9â&#x20AC;&#x201C;26.

RADZIC A.A. and SMIRNOV B.M. 1985. Reference Data on Atoms, Molecules, and Ions. Vol. 31. Springer-Verlag.

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TOKUDA, H., KUCHAR, D., MIHARA, N., KUBOTA, M., MATSUDA, H., and FUKUTA, T. 02008. Study on reaction kinetics and selective precipitation of Cu, Zn, Ni and Sn with H2S in a single-metal and multi-metal systems. Chemosphere, vol. 73, no 9. pp.1448â&#x20AC;&#x201C;1452

BHATTACHARYYA, D., JUMAWAN, A.B. JR., SUN, G., SUND-HAGELBERG, C., and SCHWITZGEBEL, K. 1981. Precipitation of heavy metals with sodium sulphide: bench-scale and full-scale experimental results. ACSIChE Symposium Series 77, no. 209. pp. 31â&#x20AC;&#x201C;38.

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+0 ,$C//*CC

C

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http://dx.doi.org/10.17159/2411-9717/2015/v115n12a8

Enhancing study practices: are firstyear students â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;?

by L. Woollacott*, S. Boothâ&#x20AC; , and A. Cameronâ&#x20AC;Ą

One of the strategies for trying to reduce attrition among first-year students and for improving their academic performance generally is to include some kind of study skills module in the first-year programme. One of the reasons often given for the relative lack of success of such programmes is the claim that students are â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;. This paper presents a study that investigated this claim by interviewing chemical and metallurgical engineering students in a South African university at the beginning and end of their first year. The basis for evaluating the extent to which studentsâ&#x20AC;&#x2122; practices appeared to change was a set of six categories of practice identified in a related phenomenographic study on the learning practices of the same students. It was evident from the interview data that even where some change in practice had occurred, the extent of change was somewhat disappointing. For those who reported changing their practice, the primary change driver appeared to be underperformance in the mid-year exam. Underperformance prior to that seemed to exert less force and students did not appear to give very serious attention to class or textual input/activities on study practices. â&#x20AC;&#x2DC;Resistance to changeâ&#x20AC;&#x2122; appeared to be implicit in nature and to be more a consequence of overconfidence and the â&#x20AC;&#x2DC;momentumâ&#x20AC;&#x2122; resulting from habit rather than an explicit attitudinal resistance. .! '(%, engineering education, first-year education, resistance to change, study practices, study skills, student retention.

+-('%#)-*'+ Where the levels of attrition among university or college entrants are high, some form of â&#x20AC;&#x2DC;study skillsâ&#x20AC;&#x2122; module in the first-year programme is frequently employed to improve the academic prospects of students. Behind this strategy is the belief that a significant factor contributing to attrition and academic underperformance is that the learning practices and study skills of many entrants are in some ways inappropriate for effective learning at a tertiary level. However, the effectiveness of such learning skills interventions has generally been disappointing. For example, Hattie, Biggs, and Purdie (1996), in a metaanalysis of 51 studies on the effectiveness of learning skills interventions, concluded that the interventions did appear to improve studentsâ&#x20AC;&#x2122; attitudes to learning and also reduced their levels of anxiety, but had minimal effect on improving their study skills.

This apparent â&#x20AC;&#x2DC;resistance to changeâ&#x20AC;&#x2122; has been

.,*,-&+)./-'/)"&+ . /&,,')*&-.%/ *-" .&(+*+ /, * ,/*+-.( .+-*'+,/ Several reasons have been offered for the relative lack of effectiveness of interventions designed to improve the learning practices and study skills of entrants to tertiary education.

Wingate (2006) argues that stand-alone study skills modules are ineffective because â&#x20AC;&#x2DC;learning how to study effectively at university cannot be separated from subject content and the process of learningâ&#x20AC;&#x2122; (p. 457). Others argue that learning practices and study skills are difficult to change because they are inherently stable and that studentsâ&#x20AC;&#x2122; prior experiences at school have developed in them â&#x20AC;&#x2DC;habitual patterns of studyâ&#x20AC;&#x2122; (Entwistle, 1998) or have â&#x20AC;&#x2DC;automated their study habitsâ&#x20AC;&#x2122; (Dembo and Seli, 2004).

This kind of stability appears to persist in many students even when considerable effort is made to deploy â&#x20AC;&#x2DC;powerful learning environmentsâ&#x20AC;&#x2122; intended, among other things,

* School of Chemical and Metallurgical Engineering, University of the Witwatersrand, Johannesburg, South Africa. â&#x20AC; Department of Pedagogical, Curriculum and Professional Studies, University of Gothenburg, Sweden. â&#x20AC;Ą Science Teaching and Learning Centre, University of the Witwatersrand, Johannesburg, South Africa. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015. /$$ //

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noted by several researchers, even in literature (discussed shortly) that reports some degree of success of study skills interventions.

This paper reports the findings of a study that investigated the dynamics associated with students changing their learning practices during their first year at university. The students were entrants to an engineering programme at a South African university in 2008. After a consideration of the literature on the apparent â&#x20AC;&#x2DC;resistanceâ&#x20AC;&#x2122; associated with changing learning practices, the study is described and the findings are presented and discussed.

Enhancing study practices: are first-year students â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;? to improve the learning practices of those students (Brownlee et al., 2001; Vermetten et al., 2002). A number of studies on South African engineering students have also commented on this apparent stability and cited it as a possible reason for the relative lack of change noted in some studentsâ&#x20AC;&#x2122; learning practices (Case and Gunstone, 2002; Cliff, 1996, 1995, 2000; Meyer, 1991; Meyer et al., 1994, 1992; Simelane, 2007).

Another reason given for the relative lack of effectiveness of interventions intended to improve studentsâ&#x20AC;&#x2122; learning practices and study skills is that students are â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;. In this regard, Dembo and Seli (2004) found that some students failed to benefit from study skills modules because they didnâ&#x20AC;&#x2122;t believe they could change, didnâ&#x20AC;&#x2122;t want to change, didnâ&#x20AC;&#x2122;t know what to change, or didnâ&#x20AC;&#x2122;t know how to change. They also noted that some students failed to benefit much from learning skills interventions because they didnâ&#x20AC;&#x2122;t seek help and they didnâ&#x20AC;&#x2122;t attend regularly. Whether this was the result of the other reasons they quoted they did not say.

Yuksel (2006) proposed two additional explanations for studentsâ&#x20AC;&#x2122; resistance to study skills interventions: students didnâ&#x20AC;&#x2122;t believe that the skills being taught had any value or, alternatively, did not consider those skills to be useful with respect to their future careers.

In contrast to the conscious â&#x20AC;&#x2DC;resistanceâ&#x20AC;&#x2122; to study skills interventions evident in the above examples, resistance may also be more unconscious in nature. As pointed out earlier, it is inherently difficulty to change well-established, stable learning practices or study skills. Accordingly, it could be argued that learning practices and study skills are inherently â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122; because of the difficulty associated with changing them. This is strongly supported by recent findings from cognitive and neuroscience research. For example, Clark (2008, 2010) indicates that a high proportion (up to 70%) of adult knowledge is unconscious and automated in nature, and in addition, that dysfunctional, automated, unconscious knowledge can be difficult to unlearn. Furthermore, such dysfunctional knowledge can interfere with a studentâ&#x20AC;&#x2122;s attempts to change that knowledge and to develop new and more appropriate knowledge along with the associated behaviours. On this basis, inappropriate or dysfunctional learning practices and study skills are inherently â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122; even if students are consciously open and committed to changing them.

From this brief review, it appears that changing learning practices and improving study skills that have been developed over many years of secondary schooling is inherently difficult and requires considerable time and commitment both on the part of students and teachers if the effort is to be successful.

/,-#%!/'+/-"./%!+& *),/' /)"&+ ./*+/,-#%.+-, .&(+*+ / (&)-*)., A study was initiated in 2008 to investigate the learning practices of first-year engineering students at a South African university and how these practices changed during their first year at university. In the study, learning practices were taken to be orientations or predispositions to study and learn and to act in learning situations in certain ways and with certain intentions that people have developed as a result of their past experience. The motivation for the study was the high rate of attrition of students entering the school and the possibility

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1200

/$$ //

that problematic aspects of their learning practices and resistance to changing these aspects were significant contributing factors. The premise behind the study was that learning practices affect student attrition by the way they influence the quality of student learning and, consequently, the academic prospects of students; i.e. that problematic features of studentsâ&#x20AC;&#x2122; learning practices contribute to poor academic performance and therefore to attrition by academic failure. The study and its findings are reported in detail by Woollacott (2013).

This paper reports the results of an investigation into the extent to which the studentsâ&#x20AC;&#x2122; learning practices changed during their first year at university and the dynamics associated with such change. The investigation was guided by the following questions. What proportion of students changed their practice? To what extent did they change? If change occurred, when did it happen in the year and what prompted the change? Did the level of practice of a student on entry have a bearing on the extent and nature of change?

What sort of change processes operated during the year? If no change occurred, why was that?

The methodology employed to address these questions was to interview a sample of students from the 2008 cohort at the beginning and end of their first year at university.

Accordingly, how students changed their learning practices was investigated only from the perspective of the students and the findings were based only on what students reported in interviews on the subject. All interviews were semistructured in nature and were based on protocols that were discussed with research colleagues after trial interviews with students.

In order to obtain a qualitatively representative sample of student experience, â&#x20AC;&#x2DC;maximum variation samplingâ&#x20AC;&#x2122; (Green, 2005) was used when selecting students for the study.

Twenty-seven students out of the entering cohort of 156 were selected and were interviewed at the beginning of the academic year and again towards the end of the year. Of these, nine were female.

The interviews at the beginning of the year focused primarily on the nature of the studentsâ&#x20AC;&#x2122; learning practices on entry to university and on establishing, through a phenomenographic analysis (Akerlind, 2005; Green, 2005; Marton and Booth, 1997), the qualitative variation in the practices found among the students. The categories of variation established from this analysis, which is reported in detail by Woollacott (2013), provided an analytical framework for the analysis of the changes in learning practices reported by the students in their second interviews at the end of the year.

The categories of variation used in the analysis are described next, after which the findings of the study are reported and discussed.

"./ (& . '( /#,.%/-'/)"&(&)-.(* ./-"./ .&(+*+ (&)-*).,/' /-"./,-#%.+-,/ The interview data was particularly rich with regard to one type of learning practice, which was termed â&#x20AC;&#x2DC;theory-focused study practiceâ&#x20AC;&#x2122;. Accordingly, this paper focuses only on that practice. Theory-focused study practice is the type of practice where a student, studying on their own, is focused only on understanding and mastering the â&#x20AC;&#x2DC;theoryâ&#x20AC;&#x2122; of the subject they are studying and concerns about tests and examinations are

Enhancing study practices: are first-year students â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;? absent or are at the back of their minds â&#x20AC;&#x201C; i.e. the focus is to learn in order to understand as opposed to learning in order to pass impending tests/exams. Here â&#x20AC;&#x2DC;theoryâ&#x20AC;&#x2122; is referring to â&#x20AC;&#x2DC;bookworkâ&#x20AC;&#x2122; and is taken to mean the conceptual and theoretical knowledge and information presented in course material. This is in contrast to a focus on developing the problem-solving skills associated with that theory. Here, â&#x20AC;&#x2DC;problemâ&#x20AC;&#x2122; is used in a technical sense as commonly used by the students and in mathematics, science, and engineering courses â&#x20AC;&#x201C; i.e. as a question or difficulty that cannot be resolved without some kind of numerical or mathematical manipulation.

Among the students, six qualitatively different categories of theory-focused study practice were identified by the phenomenographic analysis of the transcripts from the first set of interviews. These are summarized in Table I and discussed thereafter.

The most elementary category of theory-focused study practice is information-oriented practice. Here the focus is on assimilating or memorizing information with no particular regard for making sense of it. In the next category â&#x20AC;&#x201C; comprehension-oriented study practice â&#x20AC;&#x201C; the focus is on comprehending the material being studied by simply reading the relevant texts. This does not include any activity other than reading those texts. In consolidation-oriented study practice, the next category, the focus is on reinforcing and consolidating what has been comprehended by using one or more consolidation technique such as making summaries, vocalizing what has been learned, or memorizing concepts or principles. A sub-category of consolidation-oriented practice â&#x20AC;&#x201C; integration-oriented study practice â&#x20AC;&#x201C; involves consolidating and reinforcing comprehended theory further by integrating the learning of theory and the development of problemsolving skills; i.e. problems are attempted explicitly as a means of applying the theory being learned in order to deepen oneâ&#x20AC;&#x2122;s grasp of that theory.

In the four categories of study practice discussed so far, learning is conducted within the framework and structures of the theory as presented to the students. In the next category of study practice â&#x20AC;&#x201C; refinement-oriented practice â&#x20AC;&#x201C; the focus is on deepening personal mastery of that theory by explicitly

looking for new conceptual connections and linkages and, consequently, restructuring oneâ&#x20AC;&#x2122;s understanding of that theory. Techniques used to do this include developing concept maps, elaborating study notes, asking oneself questions about aspects of the theory, or trying to think about the theory from different perspectives. The sixth category â&#x20AC;&#x201C; know-how-oriented practice â&#x20AC;&#x201C; takes this refinement process a step further by explicitly trying to relate theory to real-world situations.

The five categories of study practice form a progression with one category including, but going beyond, the orientations of the previous category in the progression.

Comprehension-oriented practice works with learned information to develop comprehended theory. Consolidationoriented practice works with comprehended theory to develop consolidated theory. Refinement-oriented practice works with consolidated theory to develop a refined grasp of disciplinary knowledge, and know-how-oriented practice works with refined disciplinary knowledge to develop practical knowhow. As such the progression constitutes an increase in the sophistication of the study practice and involves an increase in the sense made of information and theory, and in the degree of consolidation, integration, and refinement of understanding and the relatedness of that theory to the real world.

In the study, it was found that while an individual student may be oriented to exercise several of the categories of practice under different circumstances, the range of practices they might exercise is constrained by their prior experience. Specifically and logically, students cannot be oriented to exercise categories of study practices with which they have had no prior experience. This observation provides a simple basis for characterizing the theory-focused study practice of individual students, namely by indicating the most sophisticated level of practice with which they have had prior experience. This observation was used as a basis for characterizing the studentsâ&#x20AC;&#x2122; learning practice and evaluating the extent to which these changed during their first year at university. So for example, a student could be characterized as having a theory-focused study practice at a consolidation level if their prior experience included a consolidation-

&-. '(*.,/*+/,-#%.+-, /-".'(! ')#,.%/,-#%!/ (&)-*). .,)(* -*'+

1

Information-oriented practices

2

Comprehension-oriented practices

3a

Consolidation-oriented practices

3b

Integration-oriented practices

4

Refinement-oriented practices

5

Know-how-oriented practices

Oriented to learning facts, formulae, or information by assimilating, memorizing, or cramming that information with no particular regard for its meaning or relevance.

Oriented to making sense of course material by reading through it, going through it, or working through it in order to develop personally comprehended theory with no particular regard for consolidating or restructuring the material as it is presented in the course.

Oriented to consolidating or reinforcing personally comprehended theory by using consolidation tools such as vocalizing, memorizing, or summarizing in order to develop personally consolidated theory with no particular regard for refining it beyond the content or structure presented in the course.

Oriented to further consolidating and reinforcing personally comprehended theory by integrating the learning of theory and the development of problem-solving skills so that appropriate problems are selected and worked on for the express purpose of consolidating oneâ&#x20AC;&#x2122;s grasp of the theory.

Oriented to deepening personal mastery of consolidated theory by using refinement tools such as restructuring, self-questioning, elaborating, concept maps, or visualizing in order to develop a personally refined grasp of disciplinary knowledge with no particular regard for how it relates to real-world situations.

Oriented to deepening personal mastery of disciplinary knowledge by relating it to real-world situations in order to, implicitly or explicitly, develop practical know-how.

/$$ //////////

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Enhancing study practices: are first-year students â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;? oriented practice and did not include more sophisticated practices such as integration-, refinement- and know-howoriented practices.

*+%*+ ,/' /-"./,-#%!

The extent of change of each studentâ&#x20AC;&#x2122;s theory-focused study practice during their first year at university was gauged by the degree to which their practice appeared to have shifted from one category of practice to another. Four types of change were evident and were labelled â&#x20AC;&#x2DC;no changeâ&#x20AC;&#x2122;, â&#x20AC;&#x2DC;minor changeâ&#x20AC;&#x2122;, â&#x20AC;&#x2DC;adaptedâ&#x20AC;&#x2122;, and â&#x20AC;&#x2DC;shiftedâ&#x20AC;&#x2122;. â&#x20AC;&#x2DC;No changeâ&#x20AC;&#x2122; speaks for itself. Changes labeled as being â&#x20AC;&#x2DC;minorâ&#x20AC;&#x2122; were ones in which the small degree of change reported by a student was considered to have involved only their adjustment to the teaching and learning environment and not a discernible change in the study practice itself. Changes labelled as â&#x20AC;&#x2DC;shiftedâ&#x20AC;&#x2122; were those where a studentâ&#x20AC;&#x2122;s practice had â&#x20AC;&#x2DC;shiftedâ&#x20AC;&#x2122; from one category of practice to another. Change labelled as â&#x20AC;&#x2DC;adaptedâ&#x20AC;&#x2122; is an in-between category where some change was clearly discernible but did not involve a shift from one category to another; it consisted of discernible change within one category of practice. For example, several students with a consolidation level of practice on entry did not shift to another category but reported that, at the end of the year, they paid more attention to developing understanding than they had done at the beginning of the year.

For convenience the five levels of theory-focused study practice were coded SP1 to SP5 (Study Practice level 1 to 5), which correspond respectively to information-, comprehension-, consolidation/integration-, refinement-, and knowhow-oriented practice respectively. The study practice of several students appeared to lie somewhere between these categories, either because the data was unclear or because some students reported having had some experience at a level of practice more sophisticated than the one at which they tended to operate. In such cases, the researcherâ&#x20AC;&#x2122;s discretion was exercised to represent the actual level of practice as appropriately as possible â&#x20AC;&#x201C; either at the less or

more sophisticated level or as somewhere between.

Of the 27 students, 10 (37% of them) shifted their practice, three students (11% of them) adapted their practice but did not change category, two students (7%) appeared to change in only minor ways, while 12 students (44% of them) did not appear to change their study practices at all.

Interestingly, one student adapted his practice by trying out some of the strategies recommended in class. However, after finding they â&#x20AC;&#x2DC;didnâ&#x20AC;&#x2122;t work for himâ&#x20AC;&#x2122;, he intentionally reverted back to the practice he had used at school.

Figure 1 breaks the results down further to explore the extent to which students who entered university with a particular category of practice changed that practice. The breakdown is presented both in the form of a bar chart and as an accompanying table â&#x20AC;&#x201C; the information in both is the same.

The figure indicates the following. Ten students entered university with relatively unsophisticated study practices â&#x20AC;&#x201C; up to and including comprehension-oriented practice (SP2 and SP1/SP2 categories) â&#x20AC;&#x201C; and had much scope for improving the quality of their practice (they could progress to levels SP3, SP4, or SP5); it was important for them to do so if they were to improve their academic prospects at university. Of these 10, the majority (7 of the 10) shifted their practice, one adapted, but two did not appear to change their practice at all.

However, in all but one case, the extent of change involved only a shift to the next most sophisticated level of practice.

At the other end of the spectrum, nine of the students entered university with relatively sophisticated study practices â&#x20AC;&#x201C; up to the level of refinement-oriented practice and also those with some know-how oriented dispositions (SP4, SP3/SP4, and SP4/SP5 categories) and did not have as much scope for improving their practice (they could only progress to SP5). The majority of these (8 of the 9) did not change their practices or made only minor changes and only one adapted their practice.

Between these two groups of students were those who entered university with an intermediate level of study practice â&#x20AC;&#x201C; practice up to the level of consolidation-oriented practice (SP3 and SP2/SP3 categories). Here, the scope to improve their study practice was still substantial â&#x20AC;&#x201C; they could progress to SP4 and SP5. Of the eight students with this profile, only

* #(./$/ / ' /,-#%.+-,/ *-"/%* .(.+-/,-#%!/ (&)-*).,/'+/.+-(! /)"&+ .%/-".*(/ (&)-*).

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Enhancing study practices: are first-year students â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;?

With regard to the dynamics behind students changing their learning practices, data from only 15 students was available; the other 12 students appeared not to have changed their practice at all. Of the 15 where some degree of change was evident, two had changed little, three had â&#x20AC;&#x2DC;adaptedâ&#x20AC;&#x2122; their practice, and 10 students had â&#x20AC;&#x2DC;shiftedâ&#x20AC;&#x2122; their practice. The findings from the study are as follows. â&#x17E;¤ The extent of change appeared to be limited to crossing from one practice category or subcategory to the next most sophisticated. This was the case with five of the 10 students who shifted their practice. The study practices on entry of four of the 10 students were between two adjacent categories and the change appeared to involve moving more fully into the more sophisticated practice â&#x17E;¤ Most students who realized they needed to be serious about changing their study practice seemed to take about half the academic year to reach this conclusion. Of the 15 students who indicated they had changed their study practice in some way â&#x20AC;&#x201C; minor change, adapted, or shifted â&#x20AC;&#x201C; only five started to do so in the first semester.

Of these, two were making only minor changes to their practice, and two were responding to class input â&#x17E;¤ Few students shifted their study practice as a result of class or textual input on the subject. Of the 13 students who shifted or adapted their practice, only three did so as a result of formal input in class and one as a result of receiving a faculty newsletter on study skills â&#x17E;¤ The primary driver of change in study practice appeared to be the stress created by getting poor grades and the studentsâ&#x20AC;&#x2122; recognition that their current study practices werenâ&#x20AC;&#x2122;t â&#x20AC;&#x2DC;working for themâ&#x20AC;&#x2122; in the sense of not facilitating the achievement of satisfactory grades. Even in the case of the four students who responded to formal input on study practice, two of them appeared to be responsive because their current practice was not â&#x20AC;&#x2DC;working for themâ&#x20AC;&#x2122;. Of the 13 students who adapted or shifted their practice, only three were not pushed by marks pressure to change their study practice. Two of these took their lecturer on trust and started using recommended study strategies. The other made the change through a â&#x20AC;&#x2DC;eureka experienceâ&#x20AC;&#x2122; of discovering the efficacy of using summaries effectively when preparing for a mid-year supplementary mathematics examination â&#x17E;¤ Poor performance in the first semester appeared to be far less of a change driver than poor mid-year marks.

Of the nine students who were pushed towards change by pressure directly or indirectly because their practices â&#x20AC;&#x2DC;were not working for themâ&#x20AC;&#x2122;, only two did so on the basis of poor performance in first semester tests and assignments. For the other seven it appeared to take poor performance in what they perceived to be their â&#x20AC;&#x2DC;majorâ&#x20AC;&#x2122; assessments â&#x20AC;&#x201C; namely, the mid-year examinations â&#x20AC;&#x201C; before poor grades had the impact of pushing them towards change.

The following extract gives other reasons why poor performance in the first semester did not seem to have the impact of poor performance at mid-year. The student in question felt she could still catch up; she was still adjusting to â&#x20AC;&#x2DC;varsity; and she didnâ&#x20AC;&#x2122;t realize that it was her study practice that needed to change. (In the extract, statements by the interviewer are italicized to distinguish them from statements by the students.) â&#x20AC;&#x2DC;OK, I changed when I come back now, the 2nd semester, â&#x20AC;&#x2DC;cuz Iâ&#x20AC;&#x2122;ve seen already â&#x20AC;Ś the way I am studying it was not working. â&#x20AC;Ś There was something serious that needs to be done or else I am just going to end up regretting. Ja. You didnâ&#x20AC;&#x2122;t realize that after the first set of tests after the 1st quarter? Not really. Why was that? I think itâ&#x20AC;&#x2122;s because I used to tell myself that Iâ&#x20AC;&#x2122;m going to catch up ... [But] Iâ&#x20AC;&#x2122;ve been trying to catch up and still itâ&#x20AC;&#x2122;s not working. So now itâ&#x20AC;&#x2122;s like, OK. You did have results at the beginning of 2nd quarter. Ja, I did but I just thought â&#x20AC;Ś Iâ&#x20AC;&#x2122;m just adjusting to varsity life, all those things [laughs] and then I can see that no, itâ&#x20AC;&#x2122;s actually the way that I am studying, itâ&#x20AC;&#x2122;s not really that effective. So it took until mid-year. What made you realize that it wasnâ&#x20AC;&#x2122;t working? â&#x20AC;&#x2DC;Cuz I was still not progressing. By progressing, what were you looking at? Iâ&#x20AC;&#x2122;m looking at passing as a whole, you find that some of the things I am passing, but not â&#x20AC;Ś really that much even though some I was failing like really failing, but now, since I have started practicing these things [the new practices], thatâ&#x20AC;&#x2122;s why I have so much hope and so, so much confidence in myself â&#x20AC;&#x2DC;cuz Iâ&#x20AC;&#x2122;ve seen that itâ&#x20AC;&#x2122;s working [in] the second [semester]. I am actually passing and I thought I was never going to pass like that.

*,)#,,*'+ The limitations of the study findings are fairly obvious. The findings derive only from the studentâ&#x20AC;&#x2122;s perspective and from student reports, and more objective data was not included in the analysis. In addition, the number of students in the study was quite small (27) and only 10 to 13 of these appeared to have changed their learning practice to any discernible degree during their first year at university. Accordingly, the findings are not generalizable and provide only indications. However, the indications are very interesting.

In the first place they are in accord with the literature discussed earlier. The stability of the study practices is clearly evident in that many students tended to continue with the practices they were used to until they came to the realization that these practices were â&#x20AC;&#x2DC;not working for themâ&#x20AC;&#x2122; and some kind of change was necessary if they were to succeed academically. In the study there was no evidence of students being consciously â&#x20AC;&#x2DC;resistantâ&#x20AC;&#x2122; to change in the manner described by Dembo and Seli (2004) and Yuksel (2006). It appears that many students were quite open to changing their study practice once they became aware that this was necessary. What can be said, however, is that these students were consciously resistant to change only in that they were not aware or convinced that change was or might be necessary. This possibility is not mentioned by Dembo, Seli, or Yuksel and so should be added to the list of ways in which â&#x20AC;&#x2DC;conscious resistance to changeâ&#x20AC;&#x2122; can manifest. /$$ //////////

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three shifted, one adapted (and then reverted to his old practice), and four did not appear to change or only made minor changes to their practice.

Enhancing study practices: are first-year students â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;? â&#x20AC;&#x2DC;Unconscious resistance to changeâ&#x20AC;&#x2122;, derived from the difficulty associated with changing oneâ&#x20AC;&#x2122;s practice, was clearly evident among the students. It was partially evident in statements made by students about how difficult it was to change. It was also evident from the observation that when students did attempt to modify their practice the extent of modification was only modest â&#x20AC;&#x201C; change was limited to shifting from the current category of practice to the next most sophisticated category.

There are two significant pedagogical implications of the study findings that stand out: the need to open studentsâ&#x20AC;&#x2122; awareness about alternative study practices and the possibility that they might need to modify their own practice; and the effect of the diversity of student practices on the design of â&#x20AC;&#x2DC;study skillâ&#x20AC;&#x2122; interventions.

It was noted earlier that, despite considerable input in class on the need for students to give serious attention to their study practices, many students appeared to remain unaware or unconvinced that such attention might be necessary. Even when warning indications such as poor grades in firstsemester tests were evident to students, some failed to realize their need to modify their study practice because they attributed the problem to other factors such as â&#x20AC;&#x2122;I am still adjustingâ&#x20AC;&#x2122; or â&#x20AC;&#x2122;I am just behind and can catch upâ&#x20AC;&#x2122;. It was clear from the study that, with the majority of students, class input was not effective in bringing about the necessary shift in awareness. Only the pressure of poor performance in â&#x20AC;&#x2DC;tests that countâ&#x20AC;&#x2122; (such as mid-year exams) appeared to have the necessary â&#x20AC;&#x2DC;powerâ&#x20AC;&#x2122; to generate the needed â&#x20AC;&#x2DC;wake-up callâ&#x20AC;&#x2122; for those students who needed to change their study practices.

These observations have several pedagogical implications. First, teachers need to find effective measures for generating the necessary wake-up call as early in the year as possible. The study findings suggest that without such measures, hearing the wake-up call will probably take about half the academic year for most students who need to hear it and this may very well be too late. Secondly, poor marks in â&#x20AC;&#x2DC;tests that countâ&#x20AC;&#x2122; appear to be the most effective vehicle for conveying that call, and assessments should be designed and scheduled accordingly. Finally, while some input on study skills is needed early in the year (e.g. for those who will pay attention to it), some thought should be given to reviewing this input in class at whatever point in the academic year students begin to be convinced that they need to modify their study practices and are therefore more open to paying serious attention to the input provided.

The study identified three groupings of students with different levels of study skills and different attitudes towards modifying their study practices. The first grouping consists of students with study practices at the comprehension level.

From the study findings, it appears that such students are typically open to or are â&#x20AC;&#x2DC;open to becoming openâ&#x20AC;&#x2122; to developing their learning practices once they become aware of the limitations of their current practice. The comments made earlier, about the need to engineer circumstances that foster the opening of studentsâ&#x20AC;&#x2122; awareness about alternative study practices and their need to modify them, apply to these

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students. In view of the extent of change that students in this grouping must negotiate, it is important that such awareness is developed as soon as possible in the academic year and that appropriate instruction, materials, and student support should be provided early in the year so that these students have available what is needed for them to begin the process of changing their learning practice when they become serious about wanting to do so.

The second grouping of students consists of those with a consolidation level of study practice. Here the pedagogical challenge is somewhat different. The indication from the study is that if these students do make the effort to improve the quality of their learning practice they are likely to be successful in developing to the refinement level of learning practice. The problem with these students lies in the word â&#x20AC;&#x2DC;ifâ&#x20AC;&#x2122;.

Only about-half of the students in the study made the effort to modify their learning practice. It seems that with these students, the level of sophistication of their learning practice is high enough that it can mask their need to develop it further. Accordingly, it is particularly important to provide measures for sensitizing these students to their need for change and development â&#x20AC;&#x201C; to engineer the â&#x20AC;&#x2DC;wake-up callâ&#x20AC;&#x2122; discussed earlier.

The third grouping of students consists of those who enter university with a refinement level of study practice.

Here a different kind of wake-up call is needed because these students do not appear to recognize that there is still room for them to develop their learning practice further â&#x20AC;&#x201C; i.e. to the know-how level. To help students to gain this awareness, formative â&#x20AC;&#x2DC;what ifâ&#x20AC;&#x2122; or â&#x20AC;&#x2DC;think aboutâ&#x20AC;&#x2122; exercises could be incorporated in tutorials or in lectures and possibly in tests as optional questions. The purpose of these formative measures should be made clear to the students; they should be presented as forerunners to â&#x20AC;&#x2DC;higher level, world-relatedâ&#x20AC;&#x2122; questions that will appear in tests/exams later in the year when all students have had a chance to develop their learning practice to the extent needed to address such questions effectively.

'+) #,*'+ The study described in this paper set out to address a number of questions about how, when, and why students modify their study practices. The findings suggest that, with regard to study practices, there is considerable diversity among South African students entering engineering education today.

Many enter with practices at only a comprehension level and must develop their practice to at least a refinement level in order to improve the quality of their learning and their chances of passing. Some enter with a consolidation level of practice which, although more sophisticated in nature, still requires further development to raise the quality of their learning and to improve their chances of performing well academically. However, these students are more â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122; in that it is more difficult for them to become convinced that they do need to pay attention to modifying their study practice. Students who enter with a refinement level of study practice do not have much scope for developing their practice further but can benefit from developing to a know-how level of practice.

The findings with regard to the dynamics of change

Enhancing study practices: are first-year students â&#x20AC;&#x2DC;resistant to changeâ&#x20AC;&#x2122;?

. .(.+)., AKERLIND, G.S. 2005. Learning about phenomenography: interviewing, data analysis and the qualitative research paradigm. Doing Developmental Phenomenography. Bowden, J. and Green, G. (eds). RMIT University Press, Melbourne.

BROWNLEE, J., PURDIE, N., and BOULTON-LEWIS, G. 2001. Changing epistemological beliefs in pre-service teacher education students. Teaching in Higher Education, vol. 6. pp. 247â&#x20AC;&#x201C;268.

CASE, J. and GUNSTONE, R. 2002. Metacognitive development as a shift in approach to learning: an in-depth study. Studies in Higher Education, vol.

27. pp. 459â&#x20AC;&#x201C;470.

CLARK, R.E. 2008. Resistance to change: Unconscious knowledge and the challenge of unlearning. Fostering Change in Institutions, Environments, and People: a Festschrift in honor of Gavriel Salomon. Berliner, D. and Kupermintz, H. (eds). Routledge, New York.

CLARK, R E. 2010. Cognitive and neuroscience research on learning and instruction: recent insights about the impact of non-conscious knowledge on problem solving, higher order thinking skills and interactive cyberlearning environments. http://www.cogtech.usc.edu/publications/clark_2010_nonconscious_learni ng_motivation_icer_9sep2010.pdf

CLIFF, A.F. 1995. A qualitative review of study behaviour before and during the first year of engineering studies. Higher Education, vol. 29. pp. 169â&#x20AC;&#x201C;181.

CLIFF , A.F. 1996. Conducting a program of learning improvement with 'educationally disadvantaged' students in engineering. International Journal of Engineering Education, vol. 12. pp. 165â&#x20AC;&#x201C;171.

CLIFF , A.F. 2000. Dissonance in first year students' reflections on their learning. European Journal of Psychology of Education, vol. 15, no. 1. pp. 49â&#x20AC;&#x201C;60.

DEMBO, M.H. and SELI, H.P. 2004. Students' resistance to change in learning strategies courses. Journal of Developmental Education, vol. 27. pp. 2â&#x20AC;&#x201C;11.

ENTWISTLE, N.J. 1998. Approaches to learning and forms of understanding.

Teaching and Learning in Higher Educationi. Dart, B.C. and BoultonLewis, G. (eds). Australian Council for Educational Research, Melbourne.

GREEN, P. 2005. A rigorous journey into phenomenography: from a naturalistic enquirer standpoint. Doing Developmental Phenomenography. Bowden, J. and Green, G. (eds). RMIT University Press, Melbourne.

HATTIE, J., BIGGS, J., and PURDIE, N. 1996. Effects of learning skills interventions on student learning: a meta-analysis. Review of Educational Research, vol. 66. pp. 99â&#x20AC;&#x201C;136.

MARTON, F. and BOOTH, S. 1997. Learning and Awareness. Lawrence Erlbaum Associates, Mahwah, New Jersey.

MEYER, J.H.F. 1991. Study orchestrations: the manifestation, interpretation and consequences of contextualised approaches to learning. Higher Education, vol. 22. pp. 297â&#x20AC;&#x201C;316.

MEYER, J.H.F., CLIFF, A F., and DUNNE, T.T. 1994. Impressions of disadvantage: II - monitoring and assisting the student at risk. Higher Education, vol.

27. pp. 95â&#x20AC;&#x201C;117.

MEYER, J.H.F., DUNNE, T.T., and SASS, A.R. 1992. Impressions of disadvantage: I - school versus university study orchestration and consequences for academic support. Higher Education, vol. 24. pp. 291â&#x20AC;&#x201C;316.

SIMELANE, Z.F. 2007. Identification and classification of incoming learning behaviours amongst a sample of first year, English second language, engineering students: a case study. University of the Witwatersrand.

VERMETTEN, Y.J., VERMUNT, J.D. and LODEWIJKS, H.G. 2002. Powerful learning environments? How university students differ in their response to instructional measures. Learning and Instruction, vol. 12. pp. 263â&#x20AC;&#x201C;284.

WINGATE, U. 2006. Doing away with 'study skills'. Teaching in Higher Education, vol. 11. pp. 4457â&#x20AC;&#x201C;469.

WOOLLACOTT, L.C. 2013. On the learning practices of first year chemical and metallurgical engineering students at Wits: A phenomenographic study.

PhD thesis, University of the Witwatersrand.

YUKSEL, S. 2006. Undergraduate students' resistance to study skills course.

College Student Journal, vol. 40. pp. 158â&#x20AC;&#x201C;165. â&#x2014;&#x2020; /$$ ////////////////////

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associated with modifying oneâ&#x20AC;&#x2122;s study practice suggest that opening the awareness of students with regard to the possibility that aspects of their learning practices need to change is critical but difficult to engineer. For students who enter with comprehension and consolidation levels of study practice, it appears that the most effective means for engineering the appropriate wake-up call is to implement â&#x20AC;&#x2DC;tests that countâ&#x20AC;&#x2122; early in the academic year so that students who are likely to perform poorly come to this realization as early as possible. (Obviously, care must be taken that such assessments should contribute to their final mark only to the extent necessary for an effective wake-up call to be engineered, and should not count so much that failure in these assessments is demoralizing and cripples their chances of passing the year.) For students who enter with a refinement level of study practice a different kind of sensitization appears to be necessary â&#x20AC;&#x201C; one that is more motivational in nature and facilitates reflection and deepens interest in how the material being learned is relevant to real-world situations.

Although the findings presented in this paper are idiosyncratic to the students involved in this study, it is very likely that the conclusions that have been reached are more widely applicable to entrants to South African engineering education in general.

advanced metals initiative

Ferrous 2016 FERROUS AND BASE METALS DEVELOPMENT NETWORK CONFERENCE 2016 C o n f e r e n c e A n n o u n c e m e n t

7–11 November 2016 · MSC Sinfonia Cruise, Durban-Mozambique-Durban BACKGROUND Through its Advanced Metals Initiative (AMI) the South African Department of Science and Technology (DST) promotes research, development and innovation across the entire value chain of the advanced metals field. The goal of this initiative is to achieve sustainable local mineral beneficiation and to increase the downstream value addition of advanced metals in a sustainable manner. The achievement of this is envisioned to be through human capital development on post-graduate and post-doctoral level, technology transfer, localization and ultimately, commercialisation.

The AMI comprises four networks, each focussing on a different group of metals. These are Light Metals, Precious Metals, Nuclear Materials and Ferrous and Base Metals (i.e. iron, steel, stainless steels, superalloys, copper, brass, etc.).

The AMI FMDN 2015 Conference aims to bring together stakeholders from the mineral sector, academia, steel industry, international research institutions and government in order to share and debate the latest trends, research and innovations, specifically in the areas of energy, petrochemical, corrosion, materials for extreme environments and transport, local mineral beneficiation and advanced manufacturing related to these materials.

Keynote speakers to be invited include international specialists in the fields of ferrous metals, computational materials science, high temperature corrosion and mineral beneficiation.

The Ferrous and Base Metals Development Network (FMDN) of the DST’s Advanced Metals Initiative (AMI) programme will host the AMI’s annual conference in 2016. The conference seeks to share insight into the state of R&D under the AMI-FMDN programmes and explore and debate the following broad themes:

Development of high performance ferrous and base metal alloys for application in the energy and petrochemical industries Development of corrosion resistant ferrous and base metal alloys Development of lightweight and/or durable steels for cost-effective transportation and infrastructure, and Panel discussions on possible future value-adding R&D programmes under FMDN within the South African National Imperatives.

OBJECTIVES

WHO SHOULD ATTEND

Insight into ferrous and base metal materials R&D for application

Stakeholders from the energy, petrochemical, corrosion and transportation industries where ferrous (i.e. iron, steel, stainless steels, superalloys, etc.) and base (i.e. copper, brass, etc.) metals are used in their infrastructure. Also included in this invitation are local and international Higher Education Institutions (HEIs), Government Departments and Science Councils that are involved and/or have interest in R&D in these areas.

in the areas of energy, petrochemical, corrosion, extreme environments, improved processing technologies and advanced alloys for the transport industry in South Africa and globally.

EXHIBITION/SPONSORSHIP Sponsorship opportunities are available. Companies wishing to sponsor or exhibit should contact the Conference Co-ordinator.

our future through science

For further information contact: Head of Conferencing, Raymond van der Berg SAIMM, P O Box 61127, Marshalltown 2107 Tel: +27 11 834-1273/7 ·Fax: +27 11 833-8156 or +27 11 838-5923 E-mail: raymond@saimm.co.za · Website: http://www.saimm.co.za

http://dx.doi.org/10.17159/2411-9717/2015/v115n12a9

Recycling of cemented tungsten carbide mining tool scrap

by C.S. Freemantle*â&#x20AC; and N. Sacks*

The zinc recycling process (PRZ) and acetic acid leaching (AC) were successfully employed to recycle cemented tungsten carbide mining tool scrap for re-use as production powders. The main success of the PRZ process was that it produced powders which were suitable for manufacturing sintered alloys having properties within the commercial benchmark ranges for WC-6 wt% Co mining-grade tools. Although the powders produced from the AC process were deemed unsuitable for manufacturing the same grade of mining tools, the process cannot be viewed as a failure, since the recycled powders are suitable for different commercial applications. The two recycling processes can therefore be used as complementary processes on an industrial scale.

methods can potentially improve the successful usage of recycled materials, leading to less dependence on large quantities of new raw materials. In this way, raw material costs may be reduced and the global demand for production and mining of tungsten becomes less urgent. Successful recycling will also ensure that mining and manufacturing industries dependent on tungsten carbide tools are not adversely affected. A brief review of the recycling of hardmetals will be given first, followed by the methodology and results of the research undertaken.

5 23-4 cemented tungsten carbide, recycling, zinc process, acetic acid leaching, mining tools.

5, ,+0.$6)51(2-46 236,5)5.151'.$415.6,/3 0-564,3/&6

.132-',102.

Cemented tungsten carbides (also known as hardmetals) are used extensively in the mining and manufacturing industries, and account for approximately two-thirds of the worldâ&#x20AC;&#x2122;s tungsten consumption. If present production volumes continue, the worldâ&#x20AC;&#x2122;s tungsten resources could be depleted in 40 years (Ishida et al., 2012). In addition to this mineral depletion, raw material costs are high.

Therefore recycling of tungsten carbide scrap is becoming increasingly important. For the current study two different recycling methods were investigated, namely the zinc recycling process and acetic acid leaching. The aim of the research was to determine whether the two recycling techniques could be used as complementary processes on an industrial scale to recycle cemented tungsten carbide mining tool scrap. The recycled products would then be converted into feedstock powders for the manufacture of new mining tools, only if the recycled powders have properties similar to newly purchased powders, to ensure tool integrity. Although the zinc recycling process is currently being used globally, to the authorsâ&#x20AC;&#x2122; knowledge, the acetic acid leaching technique is not used to produce commercial cemented tungsten carbides. Therefore the assessment and comparison of both recycling

Recycling of cemented tungsten carbide materials is usually energy-intensive and environmentally unfriendly (Edtmaier et al., 2005). According to Paul et al. (1985), cemented tungsten carbide recycling methods can be subdivided into two general categories, namely removal of the binder metal using a selected process, leaving a finely divided carbide matrix behind (skeleton-like, framework structure) or by chemical modification methods which convert the carbides into a different form, for example into oxides.

Numerous methods have been developed to recycle hardmetal scrap materials, namely, acid leaching, electrochemical methods, blasting, oxidation/chemical modification at high temperature, liquid metal infiltration techniques, and hybrid methods (combinations of the aforementioned processes). In the current study two recycling methods were

* School of Chemical and Metallurgical Engineering and DST-NRF Centre of Excellence in Strong Materials, University of the Witwatersrand, Johannesburg, South Africa. â&#x20AC; Pilot Tools (Pty) (Ltd), Johannesburg, South Africa. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015 and revised paper received Oct. 2015.

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Recycling of cemented tungsten carbide mining tool scrap employed to recycle cemented tungsten carbide mining tool scrap, namely acid leaching and zinc recycling. A brief review of each process is given below.

The zinc process is the most widely used recycling process in the cemented carbide manufacturing industry. It is commonly referred to as â&#x20AC;&#x2DC;PRZâ&#x20AC;&#x2122;, an abbreviation for â&#x20AC;&#x2DC;process of recycling with zincâ&#x20AC;&#x2122;. This method has experienced renewed interest since 2005 (when global tungsten prices increased) as it is the most cost-efficient and environmentally friendly recycling method. Prior to 2005, only 20â&#x20AC;&#x201C;25 % of hardmetals were recycled in Europe, but today recycling has reached almost 50% (Karhumaa and Kurkela, 2013). In the PRZ process, the scrap material is sourced, sorted, and then packed into graphite boats or crucibles together with zinc. The furnace is evacuated of air, filled with argon, and heated to temperatures ranging from 750°C up to 960°C, depending on the details of the process such as furnace type, nature of the scrap, etc. (Barnard et al., 1970). Treatment of the carbide with molten zinc at these temperatures results in the zinc and the metal binder (typically cobalt) forming a liquid alloy as the zinc is pulled through the carbide scrap by a powerful vacuum. The zinc is removed by distillation, and the resulting product consists of a mixture of the carbide and the metal binder, in which the bond between the two has been broken (Barnard et al., 1970; Karhumaa and Kurkela, 2013; Trent, 1946). This recycled product is easily broken down by mechanical means to a particle size similar to that of the grain size of the original cemented carbide microstructure.

The zinc vapours are recovered by condensation in a cooler zone of the distillation furnace. The weight ratio of zinc to metal binder used may range from 30:1 to 10:1, with a preferred range of 15:1 or 20:1. The time required for the treatment depends on the size and shape of the scrap material (Barnard et al., 1970).

There are several patents and publications relating to acid leaching technology for cemented carbides. Kinstle and Magdics (2002) described a method of recovering tungsten, vanadium, chromium, and molybdenum metals from carbide metal scrap by treatment with an alkali metal hydroxide in the presence of oxygen at an elevated temperature and pressure for a period of time sufficient to form a watersoluble alkali metal hydroxide. The metals are then recovered from the water-soluble alkali metal salt using chemical means. According to Seegopaul and Wu (1998) cemented carbide materials can be reclaimed by oxidizing scrap into tetragonal and octahedral tungsten trioxide, which is insoluble in water with a neutral pH. This material is digested in an acidic solution that selectively dissolves the cobalt and not the tungsten. Cobalt hydroxide and oxychloride are precipitated by raising the pH to between 6 and 10. The tungsten and cobalt compounds are separated from the slurry and re-dissolved in an aqueous solution with a pH greater than 11. The product is spray-dried and carburized as necessary.

Hydrothermal techniques have also been investigated by several researchers (Kojima, 2005; Reilly, 1983; Ritsko et al., 1982) in which the cobalt binder is extracted by using

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hydrochloric acid at 110°C, and subsequently pulverized using ball milling. Due to its brittleness, the carbide framework remains behind. Oxidation was found to occur more easily on these materials (probably due to activated/fresh surfaces and reprocessing procedures), which degrades the properties of the resulting materials. Phosphoric acid leaching techniques have also been attempted by some authors (Nßtzel and Kßhl, 1979; Vanderpool and Kim, 1991).

Tungstic acid is another method described by Brookes (1990), who investigated a leaching method that produces ammonium paratungstate. Acid leaching, while successful, is known to have a negative environmental impact, and the low pH used typically results in a lack of selectivity during leaching.

!/1530/+46/.-6)51(2-2+2$ Three classes of WC-6 wt% Co materials were studied in this research, namely materials produced from (a) new, unrecycled powders, (b) zinc recycled mining scrap metal powders, and (c) acetic acid recycled powders. The new powders (NP) were produced from a blend of 94 wt% tungsten carbide and 6 wt% cobalt powders, milled in a 600litre production stainless steel mill, using a 3:1 ratio of cemented carbide milling media to powder load, with 13.65 wt% ethanol. The powder was milled to an Mv grain size range of 1.6â&#x20AC;&#x201C;2.0 Îźm, measured using a Microtrac s3500 particle size analyser. After milling, the powders were spraydried under a constant 7 bar pressure using a Niro HC 120 mixed flow spray dryer.

The zinc recycled powders (PRZ) were produced using a commercial PRZ process, in which graphite crucibles containing pure zinc and cemented carbide mining tool scrap components were inserted into a furnace, which was then evacuated of air and filled with argon. The temperature of the furnace was raised to 930°C and held for 24 hours to allow for zinc infiltration. Removal of the zinc was accomplished by a powerful vacuum and distillation process at 960°C over a 36-hour time period, after which the load was gradually cooled to room temperature. The recycled product was then milled and spray-dried using the same production conditions as for the NP. Prior to milling, the PRZ powder composition was adjusted to a 60:40 ratio; 60% zinc recycled scrap powder plus 40% NP. The reason for the dilution is that recycled mining scrap typically contains greater than 6 wt% Co (usually 8â&#x20AC;&#x201C;12 wt% Co on average), thus requiring blending to return the batch composition to 6 wt% Co. The acetic acid recycled (AC) powders were produced from acid-leached, zinc-recycled â&#x20AC;&#x2DC;oversize materialsâ&#x20AC;&#x2122;. The PRZ process often produces recycled products larger than 15 mm in diameter, which are referred to as â&#x20AC;&#x2DC;oversize materialsâ&#x20AC;&#x2122;.

These products have generally been only partially attacked by the molten zinc. It is deemed neither energy- nor productionefficient to subject these oversized products to the milling process described above to produce suitable powders. One alternative is to subject these oversized products to a second cycle of the PRZ process. However, on a commercial scale this is not feasible, as the amount of oversized material produced is small, which would entail storing the recycled product until a production-size batch is ready for processing. The effects of long-term storage on the recycled product are unclear at this stage. Therefore the option of using acetic acid leaching on a

Recycling of cemented tungsten carbide mining tool scrap laboratory scale, as a complementary recycling process, was investigated. The powders produced from this process would also be used for the commercial production of new tools, if deemed suitable. An acetic acid recycling plant, capable of leaching approximately 150 kg of material, was constructed for this study.

The plant operated at atmospheric pressure and 80°C, with an air flow rate of 120 litres per minute. The pH was kept below 4 at all times to maintain cobalt extraction, in accordance with the work of Edtmaier et al. (2005). The recycling process was run for 21 days, after which the acetic acid was extracted, and the recycled product was washed with water repeatedly until the purple hue of the cobalt acetate was removed and the material was clean. The leached scrap was then dried, and crushed in an 80-litre stainless steel ball mill with ethanol, with some new cobalt added to bring the batch composition back to 6 wt % Co. These AC powders were milled to the same Mv grain size range (1.6â&#x20AC;&#x201C; 2.0 Îźm) as the NP and PRZ powders.

All three powders, NP, PRZ, and AC, were examined using a Carl Zeiss field emission scanning electron microscope (FESEM) and the powder morphologies compared. It is well known that the properties of the powders used to produce sintered tools have a significant influence on the production processes used to achieve the final sintered microstructure and material properties, which directly influence the industrial performance of the tools (Walker, Reed, and Verma, 1999). One important powder property is slurry rheology, which is defined as the deformation and flow of the slurry under applied stress or strain (Steffe, 1996). The powderâ&#x20AC;&#x2122;s slurry rheology directly impacts the formation and properties of the spray-dried granules, the density and size distribution of which has a major effect on the ease of compaction and subsequent shrinkage of the pressed compacts (Bertrand, 2003; Walker, Reed, and Verma, 1999; Walker and Reed, 1999). A detailed analysis of the slurry rheology of the NP and PRZ powders was presented in a previous publication (Freemantle and Sacks, 2015). In the current research, the slurry rheology of the AC powders was investigated and compared to that of the NP and PRZ powders.

Slurry rheology tests were performed using a Brookfield R/S Plus rheometer equipped with a Pt-100 thermocouple and temperature control jacket regulated by a Lauda Eco RE-420 temperature control bath. A CC40 coaxial cylinder spindle geometry was used for all experiments. The temperature of the slurry was held constant at 25°C and the slurries were allowed to equilibrate to temperature while gently agitated using an IKA Eurostar 40 digital mixer equipped with a nonbubble generating turbine, inside a temperature control bath; after which 71 ml of sample was extracted from the mixing

cup and rheologically tested. Shear stress as a function of shear rate was measured over 120 seconds, during which the spindle accelerates from 1 s-1 to 500 s-1 during the first 60 seconds, and then decelerates to zero, at the same rate, in the final 60 seconds. Using the plot of shear stress against shear rate, approximate yield stress values were extrapolated from the y-intercept of the straight-line graphs of the spray-dried slurries, as for the Bingham plastic method (Darbouret et al., 2005; Lewis, 2000). To further understand the rheology results, the zeta potential of all three powders was tested using a Malvern Nano-ZS Zetasizer at 25°C. To assess the influence of the two recycling methods on the final sintered material properties, the spray-dried, new (NP), and recycled powders (PRZ and AC) were compacted into test pieces and sintered using commercial production methods. Comparisons were made to benchmark values of sintered alloys manufactured using new, unrecycled powders.

Cylindrical test pieces of 10 mm diameter were uniaxially compacted using a Fette MP-250 hydraulic press, which resulted in a 20% shrinkage. The green compacts were sintered at 1430°C in an Ultratemp sinter-HIP furnace for 75 minutes. During the last 20 minutes of sintering, the pressure was increased to enable hot isostatic pressing. The sintered test pieces were then subjected to standard quality control tests used during commercial production. Sintered sample densities were determined using the Archimedes principle on a Shimadzu AY120 scale equipped with an automatic density suspension and reporting system. The magnetic saturation of the sintered samples was measured using a Setaram 6461 cobalt magnetic saturation machine, equipped with a Sigmameter digital controller and a Scout Pro SPU402 digital balance. Magnetic coercivity of the sintered samples was measured using a Dr. Foerster-Koerzimat coercimeter.

Vickers hardness was measured using a Mitutoyo AVK-CO hardness tester with an indenting load of 30 kg force applied to the sample for 10 seconds.

54'+146/.-6-04,'4402.

The particle size distributions and zeta potential values of each powder slurry are reported in Table I. The mean volume average particle size of the NP powder slurry is 1.43 Âľm, compared to 1.89 Âľm and 1.65 Âľm for the PRZ and AC powders respectively. Despite having the finest mean volume average particle size, the NP powder has the highest D10 value and the lowest D90 value, indicating that the particle size distribution of this powder is narrower compared to the PRZ and AC powders. This is illustrated in Figure 1. The AC powder possessed the finest particles with D10 approaching 0.4 Âľm, as well as coarse particles, which approached the maximum size (D90) of the PRZ particles, giving the AC

2 -53 NP PRZ AC

% )#

* 6% )#

6% )#

6% )#

51/6&215.10/+6%) #

1.43 Âą 0.004 1.89 Âą 0.007 1.65 Âą 0.348

0.53 Âą 0.002 0.47 Âą 0.004 0.41 Âą 0.061

1.23 Âą 0.002 1.57 Âą 0.013 1.22 Âą 0.078

2.59 Âą 0.006 3.79 Âą 0.010 3.31 Âą 0.334

-0.4 Âą 18.4 -16.3 Âą 19.7 -19.5 Âą 19.7

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Recycling of cemented tungsten carbide mining tool scrap powder the broadest overall particle size distribution. The FESEM micrographs in Figure 2 corroborate this, showing that > 3 Âľm particles were present in both PRZ and AC powders, while the NP powder particles reflect the narrower distribution range. Figure 2(c) shows that the AC powder contained many extremely small particles, which is clearly indicated in the overall particle size distribution curves (Figure 1) from which it can be seen the AC slurry contained a notable fraction of material less than 0.2 Âľm in diameter.

The zeta potential (Table I), which represents a slurryâ&#x20AC;&#x2122;s stability and tendency to agglomerate, indicated that the most unstable (close to zero zeta potential) slurry was the NP powder, while the PRZ and AC powders showed more negative zeta potentials, which implies greater dispersion in suspension. Figure 3 shows the shear stress versus shear rate graph for the various slurries, in which apparent viscosity (in Pa.s) is given by the gradient of each graph. NP slurries exhibited a higher viscosity than the AC and PRZ slurries, which means increased capability of producing dense

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granules when spray-dried; ideal for the compaction of green components prior to sintering (Freemantle and Sacks, 2015; Walker and Reed, 1999).

The PRZ slurry recorded the lowest shear response because of its coarser particle size distribution, and consequently a lower volume per cent solids (due to a lower total surface area of the larger particles). The size of the particulates within a slurry dominates slurry rheology because of the exponentially increasing surface area with decreasing particle diameter and a corresponding exponential increase in slurry viscosity (Freemantle and Sacks, 2015; He et al., 2004; Sun et al., 2010; Zhang et al., 2014). This, combined with the charge repulsion of the predominantly

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Recycling of cemented tungsten carbide mining tool scrap negatively charged suspended particles within the slurry (as indicated by the zeta potential in Table I), reduced the viscosity of the PRZ slurry further. The AC slurry has a similar zeta potential to the PRZ slurry, and thus the presence of coarse particles (Mv) could lead one to expect the AC slurry to have a shear response close to that of PRZ. However, this was not found, and instead the shear response was close to that obtained for the NP slurry. This behaviour was attributed to the large number of extremely fine particulates, which greatly increased the surface area of the AC slurry (see Figure 2c) and hence the effective volume per cent solids, thereby increasing the slurry viscosity, despite the negative zeta potential.

The yield stress of each slurry was extrapolated by using the y-intercept of the straight-line graphs in Figure 3, in accordance with the Bingham-plastic model (Freemantle and Sacks, 2015; He et al., 2004, 2006; Turian, 1997). Yield stress is a dominant factor in determining whether spraydried granules will emerge as solid or hollow particles (Bertrand et al., 2003; Walker and Reed, 1999). Previous

work found that a yield stress of approximately 10 Pa resulted in solid granules, while values far below 10 Pa yielded granules with internal voids. The AC powder (yield stress of 7.6 Pa) and the NP powder (yield stress of 9.2 Pa) both resulted in predominantly solid granules, while the PRZ powder (yield stress of 0.83 Pa) resulted in granules having large internal voids. Ideal, dense spray-dried granules are known to produce tools of a higher standard, compared to tools produced from powders with a high internal porosity (Eckhard and Nebelung, 2011). Hence, the NP and AC slurries produce ideal powders, while the PRZ slurries require operational adjustment to produce suitable powder granules.

The sintered properties of the materials are listed in Table II, and the FESEM images of the microstructures are shown in Figure 4. The benchmark values for the commercially accepted property ranges for a WC-6wt%Co mining tool grade are also listed in Table II. As expected, the NP alloy is within the benchmark specifications, but with a slightly higher than ideal coercivity due to the fine grain size resulting from overmilling. The dependence of magnetic coercivity on grain size

Table II

Material properties of the sintered alloys Grade

NP PRZ AC Benchmark

Magnetic saturation (wt% Co)

Coercivity (Oe)

Vickers hardness (HV30)

Density (g/cc)

Porosity rating*

5.86 Âą 0.04 5.52 Âą 0.19 6.56 Âą 0.10 5.2 - 6.1

158.7 Âą 1.5 133.3 Âą 1.5 98.0 Âą 2.0 120 - 160

1433 Âą 15 1424 Âą 8 1282 Âą 7 1350 - 1450

14.85 Âą 0.01 14.97 Âą 0.03 14.88 Âą 0.02 14.80 - 15.00

<A02 B00 C00 <A02 B00 C00 A02 B00 C00 A02 B00 C00

* ISO standard 4505, 1978.

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Recycling of cemented tungsten carbide mining tool scrap and its use in quality control is a well-documented phenomenon in cemented carbides (Love et al., 2002; Upadhyaya, 1998; Vekinis and Bartolucci-Luyckx, 1987).

The fine-grained WC microstructure of the NP material is visible in Figure 4a. The PRZ alloy properties were within all the benchmark ranges. The PRZ alloys had a coarser microstructure than the NP alloy, but finer than the AC alloy, with a few isolated large WC grains. The AC alloy properties did not meet most of the benchmark values; they had an unacceptably high magnetic saturation value, low coercivity and Vickers hardness, but an acceptable density. Each of the sintered compacts had A02 porosity or less (which is acceptable commercially), and no B-type porosity or free carbon present.

The magnetic saturation of the AC alloy was high due to iron contamination originating from the repeated milling cycles (in stainless steel mills) to which the powder was exposed during its material lifespan. The first series of milling cycles were during production of the new alloy (before recycling), then the scrapped tool was subjected to the zinc recycling process which included crushing and milling to break down the recycled product, from which the oversize material was extracted and subjected to acid leaching, after which the recycled product was milled to the required production grain size and further homogenized with the addition of extra cobalt powder to achieve the required composition. The coercivity was low for two reasons, namely the presence of too much magnetic material (Co and Fe), and the coarse sintered grain size of the alloy. The large number of very fine (< 0.5 Âľm) grains in the green compact, which have a large surface area and a tendency to react and dissolve, were consumed by the coarser grains during liquidphase sintering, as per Ostwald ripening. This process resulted in the coarse-grained microstructure depicted in Figure 4c, which is directly responsible for the low Vickers hardness. The AC alloy had an acceptable density and porosity (A02), which is attributed to the predominantly solid powder granules produced from the slurries.

Based on the sintered material properties, the PRZ powders are suitable to be used for the production of the specified mining-grade tools, but the AC powders are unsuitable for this specific mining tool application. However, based on the sintered properties, the AC powders may be used for alternative applications, e.g. components that require high fracture toughness, where the coarser grained hardmetals are generally used. Benchmark ranges for existing hardmetal grades include a Vickers hardness of 1150â&#x20AC;&#x201C;1290 HV30 and a coercivity of 80â&#x20AC;&#x201C;120 Oe. The composition of the AC powders could be adjusted as necessary to increase the cobalt content, to produce even tougher grades that are suitable for applications such as milling media, shims, and possibly coal and hard-rock mining (Morrison, 2015).

The PRZ process has a high recovery rate, produces powders with low impurity levels, and is an overall environmentally friendly process. The Zn may be re-used for multiple recycling runs before requiring replacement. However, its disadvantages include high electricity consumption; the

â&#x2013;˛

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material chemistry and composition can change through multiple recycling runs; and the material to be recycled does not always break down into powder in the first recycling run (Barnard et al., 1970; Karhumaa and Kurkela, 2013). The latter phenomenon was observed in the current study where coarse, oversize particles were produced from partial Zn infiltration. This would require a second recycling run (or more) to reduce it to useable feedstock for manufacturing, thereby increasing powder consumption and production costs. Despite the negative aspects, it is a widely used technique. From their work, Karhumaa and Kurkela (2013) predicted that the zinc recycling process will gain market share in the future as they believe that it has not yet realized its full potential.

The advantages of the acetic acid leaching process are that it can be conducted at low temperatures and pressures, and selectively leaches out the cobalt binder from between the tungsten carbide grains. A further advantage is that the acetic acid can be regenerated by reclaiming the cobalt, using oxalic acid addition to produce cobalt oxalates (which can be converted back into cobalt) and leaving the acetic acid behind. One of the main disadvantages of the leaching process used in the current study was the significant time period (21 days) required to produce the recycled product.

While the leaching process can be accelerated by, for example, using pure oxygen, instead of air, and increasing the pressure, this would increase the overall production costs (Edtmaier et al., 2005). Based on the current study, the main advantage in employing the current acetic acid leaching process is that it can be used in combination with the PRZ process, where its primary function would be to recycle the oversize byproduct of the PRZ process. This byproduct usually emerges from the PRZ process in a porous, semidecomposed state, and would be easier to recycle than â&#x20AC;&#x2DC;pureâ&#x20AC;&#x2122; scrap metal. Using low energy input, the supplementary acetic acid process could convert the oversize material into useable powder without having to perform a second run in the zinc recycling plant, which is very costly.

2.,+'402.4 The zinc recycling process (PRZ) and the acetic acid leaching (AC) technique were successfully employed to recycle hardmetal mining tool scrap for re-use as production powder.

The main success of the PRZ process was that it produced powders that can be used to manufacture sintered alloys having properties within the commercial benchmark ranges for WC-6wt% mining-grade tools. Although the powders produced from the AC process were deemed unsuitable for manufacturing the same grade of mining tools, the process cannot be viewed as a failure, since the recycled powders are suitable for different commercial applications. Throughout the study comparisons were made between the two types of recycled powders and the results compared to the properties of newly purchased powder (NP). The NP powders produced the narrowest grain size distribution during milling, had the least â&#x20AC;&#x2DC;stableâ&#x20AC;&#x2122; (i.e. most agglomerating) zeta potential, and highest slurry viscosity and yield stress, which ultimately led to ideal, dense powder granules after spray-drying; highly suited for optimal compaction behaviour. The PRZ and AC powders had coarser grain sizes than the NP powders, with broader particle size distributions. Both recycled powders also

Recycling of cemented tungsten carbide mining tool scrap had negative zeta potentials and were more dispersed within the slurry. The PRZ process produced hollow granules, requiring further slurry optimization to produce the correct granules for further production. The fraction of extremely fine grains in the AC powder increased the slurry viscosity and yield stress, producing high-quality solid spray-dried granules ideal for compaction.

, .2 +5-$5)5.14 The authors wish to acknowledge the financial and technical support received from Pilot Tools (Pty) Ltd, the Department of Science and Technology, and the National Research Foundation, South Africa.

5 535.,54

LEWIS, J.A. 2000. Colloidal processing of ceramics. Journal of the American Ceramic Society, vol. 83, no. 10. pp. 2341â&#x20AC;&#x201C;2359.

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Journal of Alloys and Compounds, vol. 489, no. 2. pp. 465â&#x20AC;&#x201C;468.

MORRISON, J. 2015. Director, Pilot Tools Pty Ltd, South Africa. Personal communication.

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Metal Powder Report, vol. 45, no. 2. pp. 131â&#x20AC;&#x201C;132.

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Hydrometallurgy, vol. 104, no. 2. pp. 178â&#x20AC;&#x201C;185.

EDTMAIER, C., SCHIESSER, R., MEISSL, C., SCHUBERT, W.D., BOCK, A., and SCHOEN, A. 2005. Selective removal of the cobalt binder in WC/Co based hardmetal scraps by acetic acid leaching. Hydrometallurgy, vol. 76, no. 1-2. pp. 63â&#x20AC;&#x201C;71.

FREEMANTLE, C.S. and SACKS, N. 2015. The impact of zinc recycling on the slurry rheology of WCâ&#x20AC;&#x201C;6wt.% Co cemented carbides. International Journal of Refractory Metals and Hard Materials, vol. 49. pp. 99â&#x20AC;&#x201C;109.

HE, M., WANG, Y., and FORSSBERG, E. 2004. Slurry rheology in wet ultrafine grinding of industrial minerals: a review. Powder Technology, vol. 147, no. 1-3. pp. 94â&#x20AC;&#x201C;112.

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KOJIMA, T., SHIMIZU, T., SASAI, R., and ITOH, H. 2005. Recycling process of WC-Co cermets by hydrothermal treatment. Journal of Materials Science, vol. 40, no. 19. pp. 5167â&#x20AC;&#x201C;5172.

F i r s t A n n o u n c e m e n t & C a l l f o r P a p e r s

The Southern African Institute of Mining and Metallurgy in collaboration with the SAIMM Western Cape Branch is hosting the

Hydrometallurgy Conference 2016 KEYNOTE SPEAKERS

â&#x20AC;˘ K. Osseo-Asare â&#x20AC;˘ M. Nicol â&#x20AC;˘ F. Crundwell â&#x20AC;˘ M. Reuter

1â&#x20AC;&#x201C;3 August 2016 ¡ Cape Town

Metals play a significant role in industrialisation and technological advancements. Do you ever wonder then what life would be like without metal resources?

The depletion of natural rich ore deposits coupled with a fall in grade, a decline in productivity, rising operational and energy costs, concerns on sustainability and environmental impact of mining and metal related activities have been affecting the mining and metals industry in the recent past. Unless innovative methods that look at the smart use and recovery of metals from metal resources are developed, the world will be faced by a metal supply risk that will impact on future economic growth and technological development.

The SAIMM Hydrometallurgy Conference, 2016, will bring together internationally and locally recognized experts, industries, R&D establishments, academia as well as students to explore how future metal demands can be met through modern hydrometallurgical technologies that can: Assist in sustainable metal extraction Lower energy costs Minimise the impact on the environment

The conference will be of value to: Hydrometallurgical plant managers and metallurgists Equipment and reagent suppliers to the hydrometallurgical industry Hydrometallurgical technology development companies Mining industry consultants Research and academic personnel

SPONSORSHIP Companies wishing to sponsor or exhibit should contact the Conference Co-ordinator.

TOPICS The conference will include but not be limited to the following topics: Research and development in hydrometallurgy (novel and optimised technologies) Processing of metallurgical and post-consumer waste Removal of metals from effluent streams Novel equipment and reagents in hydrometallurgical processing Optimisation of energy use and energy recovery Water management and utilisation in hydrometallurgical plants

For further information contact: Conference Co-ordinator, Yolanda Ramokgadi SAIMM â&#x20AC;˘ Tel: +27 (0) 11 834-1273/7 E-mail: yolanda@saimm.co.za â&#x20AC;˘ Website: http://www.saimm.co.za

http://dx.doi.org/10.17159/2411-9717/2015/v115n12a10

Titanium carbideâ&#x20AC;&#x201D;silicon nitride reactions at high temperature

by N. Can* and R. Hurman Eric*

The kinetics and mechanism of the chemical interaction between silicon nitride and titanium carbide were investigated using thermogravimetric analysis (TGA). The samples were reacted isothermally at temperatures between 1600°C and 1700°C under nitrogen and argon atmospheres. The extent and rate of reaction increased with increasing temperature under both atmospheres; however, both the extent and rate were higher under argon. Silicon nitride, in the presence of titanium carbide, was thermally stable under nitrogen and the reactions were confined to Si3N4/TiC and TiC/N2 interfaces. Under argon atmosphere silicon nitride dissociated completely to liquid silicon and nitrogen gas within about four hours of reaction time, depending on temperature, and a different reaction mechanism prevailed.

The kinetics of interaction between silicon nitride and titanium carbide under nitrogen atmosphere was found to be controlled by the rate of diffusion of nitrogen into the titanium carbide/carbonitride phase. Under argon atmosphere the rate was found to be controlled by the rate of dissociation of silicon nitride. For both cases the mechanisms of reactions were determined in detail and then modelled.

silicon nitride, composite materials, densification, titanium carbide.

Silicon nitride is among the new-high technology materials. It is usually synthesized by reacting silicon with nitrogen. The product is a ceramic powder, and with sintering and densification the structural ceramic is obtained. Resistance to thermal shock, hightemperature creep, erosion, and corrosion make silicon nitride attractive for engine components and cutting tools (Gnesin et al., 1978; Zilberstein and Buljan, 1984).

The main problem in production of silicon nitride is in the sintering and densification.

Silicon nitride is very difficult to sinter to high densities (Jack, 1976). Many additives have been used as sintering aids, many of which are detrimental to the unique properties of silicon nitride, especially for high-temperature applications (Smith and Quackenbush, 1980; Govila, 1985; Kriz, 1983). Therefore, instead of monolithic silicon nitride, composite materials based on silicon nitride have been investigated. In that respect, mixing silicon nitride powder with titanium carbide powder will not only assist densification but also

The reactions between silicon nitride and titanium carbide in the powder compact under N2 and Ar atmospheres at temperatures of 1600°C, 1650°C, and 1700°C were investigated isothermally by thermogravimetric analysis (TGA).

Very high purity Si3N4 powder with less than 10 ppm Fe and 2 ppm Ca+Mg as impurities, 1 Îźm average size, was mixed with very high purity TiC powder with 6 ppm Fe and 2 ppm Ca as impurities (both supplied by Aldrich Chemical Company, Wisconsin, USA) under methanol with an agate mortar and pestle. The very low impurity levels were not

* School of Chemical and Metallurgical Engineering, University of the Witwatersrand, Johannesburg. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015 and revised paper received Oct. 2015.

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enhance the properties further by combining the benefits of carbides and nitrides (Mah, Mendiratta, and Lipsitt, 1981). Si3N4-TiC composite materials are suitable for wear and metal-cutting tool applications (Baldoni and Buljan, 1988).

Successful composite development requires a detailed understanding of the chemical interactions between components of the composite materials. Chemical reactions between the matrix phase and dispersed particles during the sintering stage may alter the properties relevant to performance in severe environments such as high-speed metal removal (Buljan and Zilberstein, 1987).

However, little is known about the fundamental mechanistic of the reactions between silicon nitride and titanium carbide that assist property improvement. Thus, the purpose of this paper is to report on the investigation related primarily to the mechanism of the reactions between Si3N4 and TiC at temperatures between 1600°C and 1700°C.

Titanium carbideâ&#x20AC;&#x201D;silicon nitride reactions at high temperature considered to have any effect on the reactions. The average particle sizes of the TiC powders were 3, 5, 50, and 100 Îźm.

After mixing Si3N4 and TiC powders at certain volume per cent ratios (20, 30, and 40 vol% TiC, balance Si3N4), the powder mixtures were pressed into disc shapes. The green density of the compact was kept constant at approximately 60% of the ideal density based on the linear rule of mixtures by applying constant uniaxial pressure of 5 t. The approximate dimensions of the pellets were 10 mm diameter and 5 mm thickness. The kinetics of the reactions between Si3N4 and TiC were investigated by measuring the weight change upon reactions taking place in the powder compact at constant temperatures and different time intervals using TGA. The TGA set-up consisted of gas cleaning and regulating facilities, a vertical-tube furnace with six lanthanum-chromite heating elements parallel to the recrystallized alumina work tube axis, and a balance positioned at the bottom of the furnace assembly and linked to a computer for continuous weight change measurements. Although this set-up was suitable for continuous weight change measurements, the drift of the balance caused some experimental error.

Therefore, in addition to continuous weight loss measurements, intermittent weight change measurements were carried out by an outside balance.

Sample pellets were charged into the furnace and reacted under flowing N2 or Ar gas streams at a flow rate of 800 ml/min at atmospheric pressure. Experiments were carried out at the temperatures mentioned earlier. Samples were then lowered to the cool end of the furnace tube and quenched by the incoming stream of the gas.

The maximum reaction time for each set of experiments was selected in such a way that after the longest holding time there was no weight change; in other words the curve of percentage reaction completed versus reaction time levelled off. This maximum holding time for any set of experiments under nitrogen atmosphere was 16 hours. Nevertheless, an identical experimental run for each set of experiments was performed up to 36 hours to check if weight changes would occur. All the experiments were performed twice, and if more than 10% difference in mass loses was found the experimental system was checked for leaks by additional carbon blank runs. Normally, carbon blank runs were done after every 15 experiments for a period of two hours to ensure a sound operating system.

(4?@3;0?.@8!8>?3@>49>@ 98@68?0@>;@79.76.9>?

2;88= .?@<?97>=;:8@=:@>4?@,= (= - +@8!8>?3@ 98@82?7=?8 C C2 C3 C4 C5 CN CN2 C2N C2N2 C4N2 CNN Si2N

-<!8>9..=:?@2498?8 N N2 NCN Ti Si Si2 Si3 SiC SiC2 Si2C SiN

C Ti TiC TiN Si

SiC Si3N4 TiSi TiSi2 Ti5Si2

Poster (1988) has proposed that TiC and TiN can form TiC1-xNx solid solution at high temperatures by the following reaction: (1-x)TiC(s) + x TiN(s) = TiC1-xNx (s)

[3]

Since the change in lattice parameter of the solid solution obeys Vegardâ&#x20AC;&#x2122;s law (Goldschmidt, 1967) TiC1-xNx solid solution was assumed to behave ideally in this investigation.

The standard free energy of formation of TiC1-xNx ideal solid solution may be calculated by the following equation: G°f <TiC1-xNx> = (1-x) G°f <TiC> + x G° <TiN> + RT {xln(x) + (1-x) ln (1-x)} [4] When the possibility of formation of TiC1-xNx solid solution is considered, Equations [1] and [2] become xSi3N4(s) + 4TiC(s) = 3xSiC(s) + 4TiC1-xNx(s) + x C(s) [5]

[6]

The stability regions of Equations [1], [2], [5], and [6] are illustrated in Figure 1. Clearly, reactions [5] and [6] are thermodynamically more stable than reactions [1] and [2] for the temperature range of the study. Therefore, formation of

?86.>8@9:0@0=87688=;: The actual reactions between Si3N4 and TiC are complicated.

Therefore, preliminary thermodynamic calculations were carried out in the Si-Ti-C-N system with respect to pure species in standard state to understand the chemical interactions in the composite during sintering. Table I shows possible reaction products after reaction of Si3N4 and TiC, including unreacted species.

Standard free energy changes of possible reactions were studied at temperatures between 1300°C and 2000°C by using a thermodynamic program, Thermo V2.03 (Mintek, South Africa) based on a free energy minimization technique.

Only two reactions have been considered due to lower standard free energy change values: these are: Si3N4 (s) + 4TiC(s) = 3SiC(s) + 4TiN(s) + C(s)

[1]

Si3N4 (s) + 3TiC(s) = 3SiC(s) + 3TiN(s) + ½N2 (g)

[2]

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Titanium carbideâ&#x20AC;&#x201D;silicon nitride reactions at high temperature

[7] The maximum possible weight loss in Equation [7] is obtained from the stoichiometry of reaction [6] assuming a maximum possible attainable value of 1.0 for the factor â&#x20AC;&#x2122;xâ&#x20AC;&#x2122;.

Then the maximum possible weight loss will be equal to 1/6(WTiC)(MN2/MTiC), where WTiC is the mass of TiC in the sample powder compact, and MN2 and MTiC are the molecular masses of the N2 gas (which leaves the sample and causes weight loss) and TiC respectively.

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According to the kinetic results obtained, the most significant factor influencing the reaction rate and extent of reaction under nitrogen atmosphere was found to be temperature, with about five times increase between 1600°C and 1700°C as illustrated in Figure 2. The effect of temperature increase from 1600C° to 1650°C on the reaction rate and extent of reaction is not as significant as temperature increase from 1650°C to 1700°C. This can be attributed to a decrease in the thermal stability of silicon nitride because the equilibrium nitrogen pressure above silicon nitride is one atmosphere at 1900°C; its normal dissociation temperature. Therefore, partial dissociation of silicon nitride significantly increases the reaction rate.

Percentage reaction completed versus time curves at temperatures of 1600°C and 1650°C showed a marked slowdown in the reaction rate after approximately one hour of reaction time (based on slopes of the curves in Figure 2).

This change in the rate of the reaction is most probably due to the nature of the solid-solid reactions where reaction products form a diffusion barrier (Zilberstein and Buljan, 1984). However, for reactions at 1700°C, formation of this diffusion barrier takes longer, and the reason for this may be the presence of liquid silicon due to partial dissociation of silicon nitride as found in this study. The presence of liquid silicon (even if it exists temporarily under nitrogen atmosphere) enhances reactions by increasing the rate of diffusional mass transfer of nitrogen and carbon through the liquid phase in comparison to their diffusion in tightly bound solid phases such as silicon carbide and titanium carbonitride.

The kinetic curves for three different volume percentages of TiC in the initial pellet reacted under similar conditions are given in Figure 3. As can be seen, the increase in volume concentration of TiC increases the reaction rate and the extent of reaction. Since the amount of Si3N4 was always higher

than the stoichiometric amount dictated by Equations [5] and [6], saturation of the reaction with increasing TiC content is not expected. An increase in TiC content in the prepared samples increases the surface area where there is direct contact between Si3N4 and TiC particles, and consequently increases the reaction rate. At 1700°C the extent of reaction increases three times when the volume concentration of TiC increases from 20 to 40 vol%. Therefore, concentration of TiC constitutes the second largest effect (after temperature) on the reaction kinetics between Si3N4 and TiC. This indicates that reactions between Si3N4 and TiC occur on the contact points or interfaces, which is common for solid-solid interactions.

In order to elucidate the effect of particle size on the reaction kinetics, the particle size of the silicon nitride was kept constant and titanium carbide particle sizes were increased from 5 Âľm to 100 Âľm. The results are shown in Figure 4. The effect of increasing particle size of TiC on the rate and extent of reaction was not very pronounced during the first 30 minutes, after which there is a large decrease in reaction rate and extent when the TiC particle size is increased to between 50 and 100 Âľm.

Changing the particle size of TiC from 50 ¾m to 5 ¾m doubled the extent of reaction. It seems that particle size is less critical for the extent and rate of the reaction than temperature and volume concentration of TiC. Figure 5 compares the XRD patterns that were obtained from 30 vol% TiC reacted under N2 atmosphere at 1600°C for different retention times. It is clear that the primary peaks of silicon nitride exist even after twelve hours of reaction time, and silicon carbide formation becomes noticeable after four hours of reaction. The position of the titanium carbide peak on the XRD pattern has been marked, as shown in Figure 5,

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titanium carbonitride is thermodynamically more favourable than formation of TiN as a reaction product. At temperatures between 1600°C and 1700°C the difference in calculated standard free energy change of reactions [5] and [6] is very small, thus the kinetics will play a major role. However, if N2 pressure is increased in the system (such as hightemperature gas pressure sintering), reaction [5] will be the main reaction in the system.

Kinetic analyses in the Si3N4-TiC system were carried out in N2 and Ar atmospheres in the temperature range of 1600°C and 1700°C and the weight losses were observed.

Therefore, it was assumed that Equation [6] is the dominant reaction in the system. Observed weight losses were converted into the per cent reaction completed values as follows:

Titanium carbideâ&#x20AC;&#x201D;silicon nitride reactions at high temperature

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and as the retention time increases, titanium carbonitride formation is reflected by the gradual shift from the indicated titanium carbide peak position to higher 2Ө° values, toward the hypothetical titanium carbonitride peak. The shape (broadness) of the titanium carbide peaks may indicate the existence of a wide range of composition within the reacted powder mixture. Since the starting powder contains a fairly narrow size range of titanium carbide particles, the peak broadening and shift can only be attributed to the formation of titanium carbonitrides. The maximum â&#x20AC;&#x2DC;xâ&#x20AC;&#x2122; value in TiC1-xNx was found to be 0.67 under nitrogen atmosphere. The â&#x20AC;&#x2DC;xâ&#x20AC;&#x2122; value was derived as follows. Titanium carbide and titanium nitride have simple cubic crystal structures that are identical to the NaCl structure. Therefore, the TiC1-xNx peaks in the XRD patterns lie between the positions of the titanium carbide and titanium nitride peaks. The shift of TiC1-xNx peaks from (2 0 0) and (1 1 1) planes was measured by taking into account the angular distance between titanium carbide and titanium nitride peaks from the same crystallographic planes. After calculation of each shift from its respective plane, the â&#x20AC;&#x2DC;xâ&#x20AC;&#x2122; value that represents titanium carbonitride composition was deduced by taking the average of those two values. The â&#x20AC;&#x2DC;xâ&#x20AC;&#x2122; values were also checked by SEM point analysis. The error in the calculations and measurement of the â&#x20AC;&#x2DC;xâ&#x20AC;&#x2122; was approximately 4 per cent.

eight to ten hours to reach 100 per cent at 1650°C and 1600°C respectively.

The effect of changing TiC concentration on the extent and rate of the interactions under Ar atmosphere is depicted in Figure 7. During the first hour, the reaction between Si3N4 and TiC under Ar atmosphere at 1700°C is not affected by changing TiC concentration. In the later stages of the reaction, however, decreasing TiC concentration increases the percentage reaction completed. Since the reaction rate depends predominantly on the dissociation of Si3N4 under Ar atmosphere, this dissociation reaction takes place at a higher rate (see Figure 8) in the earlier stages of the interactions and obscures the effect of TiC concentration. The silicon-rich phase is produced as a dissociation product of Si3N4. This

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The nature of the interactions between Si3N4 and TiC changed drastically when the experiments were carried out under Ar atmosphere. Si3N4 is not stable under Ar atmosphere in the presence of TiC and dissociates into liquid silicon and nitrogen. Therefore, the later stages of the interactions in the system involve to a large extent interactions with the liquid phase, which is rich in silicon.

The effect of temperature on the extent and the rate of reaction between silicon nitride and titanium carbide is illustrated in Figure 6. As in the case of reactions under nitrogen atmosphere, increasing temperature increases the extent and the rate of the reaction. At 1600°C and 1650°C the extent of reaction increases gradually, whereas for samples reacted at 1700°C there is a sharp increase in the rate and extent of reaction initially (0 to 120 minutes of reaction time). This can be attributed to the decreasing stability of silicon nitride with increasing temperature and, consequently an increase in the liquid silicon-rich phase. The extent of reaction at 1700°C reaches almost 100 per cent after six hours of reaction time, indicating that almost all of the silicon nitride in the powder compact dissociated, whereas it takes

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Titanium carbideâ&#x20AC;&#x201D;silicon nitride reactions at high temperature phase can also contain some dissolved Ti, C, and N. During the later stages, the interactions occur by reaction of the remaining TiC with the Si-rich phase. Decreasing TiC concentration seems to increase the extent of chemical reactions with this intermediate phase. However, differences in percentage reaction completed are small.

Figure 8 compares the XRD patterns that were obtained from 30 vol% TiC reacted under Ar atmosphere at 1650°C for different retention times. The peaks representing silicon nitride phase in the XRD pattern disappeared after four hours of reaction under Ar atmosphere, i.e. almost all of the Si3N4 dissociated within four hours. The increase in the amount of SiC, which may be noted from the increasing intensity of the (111) plane of the β-SiC diffraction peak, was much less in N2 atmosphere than in Ar atmosphere. This also confirms that silicon nitride dissociates much faster in an Ar atmosphere and reaction between liquid silicon and TiC occurs at a much higher rate than the reactions with Si3N4 and TiC (both reactions produce SiC). The sharp shift in the diffraction peak of titanium carbide is also noticeable in Figure 8. The maximum â&#x20AC;&#x2DC;xâ&#x20AC;&#x2122; value of the titanium carbonitride phase under argon atmosphere was calculated as 0.78.

from the formation of the TiC1-xNx phase diffuse through the gas/TiC interface or Si3N4/TiC reaction interface to the surface of the titanium carbonitride phase and are deposited there until they eventually react further to form SiC. As the reaction proceeds further (Figure 11) in N2 atmosphere, reaction product layers form between the reaction interfaces. The SiC phase forms between the Si3N4 and TiC1-xNx phases and grows by solid state diffusion of carbon atoms through SiC reaction product layer to the SiC/Si3N4 reaction interface. Some of the nitrogen gas, either from direct reaction of TiC and Si3N4 or reaction of carbon and Si3N4, leaves the system and causes weight loss. The reaction interface between TiC1-xNx /TiC penetrates toward the centre of the particle to consume unreacted TiC matrix by simultaneous diffusion of carbon and nitrogen atoms.

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Considering the results of the preliminary thermodynamic, TGA, and X-ray diffraction analyses, a unique reaction mechanism for the system Si3N4-TiC can be proposed. The nature of the reaction in the Si3N4-TiC system depends strongly on the partial pressure of nitrogen gas in the system, thus two reaction mechanisms in the ceramic composite during sintering stage are proposed.

The situation just before the reaction between Si3N4 and TiC in in a N2 atmosphere is shown in Figure 9. TiC particles are irregular in shape with average particle size of 3 Âľm, and Si3N4 particles are round with 1 Âľm average particle size.

Nitrogen gas occupies the voids between the particles.

The initial stage of the reactions in N2 atmosphere (Figure10) commences by the direct contact of Si3N4 and TiC particles as well as N2 reaction with TiC particles at the gas/TiC interface. Direct reaction between Si3N4 and TiC takes place by Equation [6], in which nitrogen atoms diffuse from the Si3N4 matrix to the TiC matrix to form the thermodynamically stable TiC1-xNx phase and rejected carbon atoms from the TiC matrix react with Si3N4 to form SiC. Similarly, at the gas/TiC interface, nitrogen atoms from the gas phase diffuse through the TiC matrix and form TiC1-xNx. Carbon atoms

Titanium carbideâ&#x20AC;&#x201D;silicon nitride reactions at high temperature Since Si3N4 is not thermodynamically stable in an Ar atmosphere within the experimental temperature range, it will dissociate into Si (l) and N2 (g). Therefore, Equation [6] will be the main reaction in the Si3N4 -TiC system during sintering in Ar atmosphere. Similar to the reactions in N2 atmosphere, interaction between Si3N4 and TiC starts at the direct contact surfaces between the particles, in which nitrogen atoms diffuse to the TiC matrix to form TiC1-xNx and carbon atoms from this reaction simultaneously diffuse through the reaction product layers and react with Si3N4 to form SiC (Figure 12). Reactions in the Si3N4 -TiC system enhance the dissociation of Si3N4 and thus liquid silicon and N2 gas cover the TiC particles.

In the later stages of the reaction (Figure 13), silicon nitride particles become irregular due to dissociation. The partial pressure of N2 gas within the powder compact is equal to the equilibrium partial pressure of N2 gas above Si3N4 particles. Reactions in the system proceed similar to reactions in N2 atmosphere through diffusion of nitrogen atoms to the reaction interface between TiC1-xNx and unreacted TiC, and carbon atoms that are rejected from TiC diffuse through the reaction product layers to the Si (l)/SiC reaction interface or undissociated Si3N4/SiC reaction interface.

-;:7.68=;:8 High-temperature interactions between Si3N4 and TiC in N2 and in Ar atmosphere are governed mainly by the reaction:

The reaction products consist of β-SiC and TiC1-xNx in N2 atmosphere, as well as liquid silicon in Ar atmosphere. Si3N4 is not stable in Ar atmosphere and completely dissociates into liquid silicon and nitrogen, and interactions between Si3N4 and TiC increase the dissociation rate of Si3N4. After the reactions in Ar atmosphere, the matrix phase consists of liquid silicon and SiC and all the TiC particles are converted into TiC1-xNx by reaction with nitrogen. However, in N2 atmosphere, even after prolonged reaction periods, Si3N4 is the stable phase in the system and forms the matrix. The reaction rate and extent in Ar atmosphere are considerably higher than in N2 atmosphere because of the involvement of liquid silicon as an intermediate phase. The overall reaction between Si3N4 and TiC involves a direct chemical reaction at the reaction interface, and when the reaction product layers cover the particles, reactions are controlled by the diffusion of carbon and nitrogen atoms though the reaction product layers.

The kinetics of interactions between silicon nitride and titanium carbide was analysed in detail, resulting in a complex and lengthy mathematical model involving contracting-volume model equations as well as non-steadystate diffusion equations. The details of the kinetic modelling are beyond the scope and subject of this paper. However, it can be mentioned that the effective nitrogen diffusion coefficient was found to change between 2.28Ă&#x2014;10-13 and 6.29Ă&#x2014;10-14 cm2/s. The apparent activation energy for reactions under nitrogen atmosphere was 495.5 kJ/mol. The specific rate constant for reactions under argon atmosphere was calculated to change from 1.45Ă&#x2014;10-7 to 8.96Ă&#x2014;10-8 cm/s.

The apparent activation energy was 432.0 kJ/mol.

?5?<?:7?8 BALDONI, J.G. and BULJAN, S.T. 1988. Ceramics for machining. Ceramic Bulletin, vol. 67, no. 2. pp. 381â&#x20AC;&#x201C;387.

BULJAN, S.T. and ZILBERSTEIN, G. 1987. Microstructure development in Si3N4 based composites. Material Research Society Symposium, vol. 78. pp. 273â&#x20AC;&#x201C;281.

DUWEZ, P. and ODELL, F. 1950. Phase relationships in the binary systems of nitrides, carbides of zirconium, columbium, titanium, and vanadium.

Journal of the Electrochemical Society, vol. 97, no. 10. pp. 299â&#x20AC;&#x201C;304.

'=/6<?@1 @$@,74?39>=7@<?2<?8?:>9>=;:@;5@=:=>=9.@8>9/?@;5@<?97>=;:8 ?> ??:@,=*+ 9:0@(=-@8!8>?3@=:@ <@9>3;824?<?

GNESIN, G.G., OSIPOVA, I.I., YAROSHENKO, V.P., and RONTAL, C. 1978. Optimization of the properties of a tool material based on silicon nitride. Journal of Metallurgical Ceramics, vol. 17, no. 2. pp. 124â&#x20AC;&#x201C;127.

GOLDSCHMIDT, H.J. 1967. Interstitial Alloys. Butterworth, London.

GOVILA, R.K. 1985. Strength characterization of yttria-doped sintered silicon nitride. Journal of Material Science, vol. 20. pp. 4345â&#x20AC;&#x201C;4353.

JACK, K.H. 1976. Sialons and related nitrogen ceramics. Journal of Material Science, vol. 11. pp. 1135â&#x20AC;&#x201C;1158.

KRIZ, K. 1983. The fracture behavior of hot-pressed silicon nitride between room temperature and 1400°C. Progress in Nitrogen Ceramics. pp. 523â&#x20AC;&#x201C;28.

MAH, T., MENDIRATTA, M.G., and LIPSITT, H.A. 1981. Fracture toughness and strength of Si3N4-TiC composite. Ceramic Bulletin, vol. 60, no. 11. pp. 1229â&#x20AC;&#x201C;1240.

Poster, H. 1988. Titanium-carbonitride-based hard alloys for cutting tools.

Material Science Engineering, vol. A105/106. pp. 401â&#x20AC;&#x201C;409.

SMITH, J.T. and QUACKENBUSH, C.L. 1980. Phase effects in Si3N4 containing Y2O3 or CeO2. Bulletin of the American Ceramic Society, vol. 59, no. 5. pp. 529â&#x20AC;&#x201C;537.

'=/6<?@1*@$@,74?39>=7@<?2<?8?:>9>=;:@;5@.9>?<@8>9/?@;5@<?97>=;:8@=:@>4? ,=*+ (=-@8!8>?3@6:0?<@ <@9>3;824?<?

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ZILBERSTEIN, G. and BULJAN, S.T. 1984. Characterization of matrix reactions in Si3N4-TiC composites. Advances in Materials Characterization II, Material Science Research. New York College of Ceramics, Alfred, New York. Vol. 17. pp. 389â&#x20AC;&#x201C;401. â&#x2014;&#x2020;

http://dx.doi.org/10.17159/2411-9717/2015/v115n12a11

Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes: prospects for acid mine drainage (AMD) treatment

by M.O. Daramola*, B. Silinda*, S. Masondo*, and O.O. Oluwasina*â&#x20AC;

This article presents the outcome of a preliminary investigation INTO the application of polyethersulphone (PES)-sodalite (SOD) mixed-matrix membranes for acid mine drainage (AMD) treatment. PES-SOD membranes loaded with different amounts of SOD particles were fabricated using the phase inversion method, and evaluated for AMD treatment. The morphology, phase purity, and surface properties of the SOD particles and the membrane were checked using scanning electron microscopy (SEM), X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy, respectively. In addition, the mechanical strength of the membranes was evaluated using a texture analyser. Separation performance (metal ion rejection) of the membranes and the effect of SOD loading on the membrane performance during AMD treatment were also studied. The cations in the AMD (feed stream) and the permeate stream were determined quantitatively using atomic absorption spectrophotometry (AAS). The results of the investigation reveal that mechanical strength (Youngâ&#x20AC;&#x2122;s modulus and tensile strength) of the membrane was enhanced at increasing SOD loading. In addition, the membrane flux increased at increasing SOD loadings and the selectivity of the membrane towards Mn2+, Pb2+, Cu2+, Al3+, and Mg2+ also increased. The highest membrane rejection of 57.44% was recorded for Pb2+, and the membrane displayed a rejection of 6% towards Mn2+. All the PES-SOD membranes displayed better performance compared to an equivalent unloaded PES membrane. As far as we know, this is the first report on the application of PES-SOD mixed-matrix membranes to AMD treatment. However, optimization of the synthesis protocol and operational conditions is needed to improve the performance of the membrane.

A&%?=9: mixed matrix membranes, polyether sulphone, acid mine drainage, sodalite.

>@=?958@;?> Environmental pollution is better prevented than remediated, but most often prevention is difficult. The industrial revolution has had adverse consequences as well as benefits. For example, countries with past and current mining activities are facing challenges of environmental pollution due to acid mine drainage (AMD). The mining sector in South Africa is one of the main driving forces of the countryâ&#x20AC;&#x2122;s economy. Despite the positive benefits, the serious impact of mining activities on the environment resulting from AMD cannot be over-emphasized (Hughes and Gray 2013). Acid mine drainage has significant effects on environmental sustainability and water security (Evangelou, 1998).

0 +-B11(BB

* School of Chemical and Metallurgical Engineering, Faculty of Engineering and the Built Environment, University of the Witwatersrand, Wits 2050, Johannesburg, South Africa. â&#x20AC; Department of Chemistry, Federal University of Technology, Akure, Nigeria. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received May 2015 and revised paper received Aug. 2015.

B

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AMD is produced by oxidation of sulphide minerals, mostly iron sulphides. This could be natural through the breaking down of sulphides by bacteria, as well as through anthropogenic activity, which is mining (Akcil and Koldas, 2006). Oxidation of sulphides produces sulphuric acid, which in turn leaches out a range of metals from rock and other metal-containing materials. This makes AMD potentially dangerous to the environment, since is not only highly acidic, but also contains high metal concentrations (Singh, 1987).

Research and development has been channelled towards source control and mitigation of AMD. Since oxygen and water are required for the formation of AMD, source control is targeted at preventing oxygen and/or water from contacting the sulphide-bearing rock so as to prevent oxidation reactions from producing AMD (Kuyucak 2002; Johnson and Hallberg, 2005; Luptakova et al., 2010; Egiebor and Oni, 2007). Preventing the formation and migration of AMD from its source is not easy. Thus, research activities are now focusing on collection, treatment, and discharge of treated AMD. Treatment techniques can be divided into two categories: active and passive treatments (Johnson and Hallberg 2005). This has been discussed extensively by many authors (Moses et al., 1987; Skousen et al., 1998; Johnson and Hallberg, 2005; Kalin et al., 2006; Egiebor and Oni 2007; RĂśtting et al., 2011). These days, various methods are employed for the treatment of AMD. Lime (Ca(OH)2 or limestone (CaCO3) treatment is carried out to precipitate the sulphate as gypsum and heavy metals as

Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes hydroxides (Lyew et al., 1994; Hedin et al., 1994; Dempsey and Jeon, 2001; Sibrell and Watten, 2003; Santomartino and Webb, 2007). This has a disadvantage because of the great quantities of gypsum sludge contaminated with metals that are produced, and the high operating costs for disposal (Johnson and Hallberg, 2005). Another method that is commonly used is two-step neutralization and ferrite formation, in which magnesium oxide or calcium carbonate is used for the first neutralization step to raise the pH to around 4.8 to produce low-solubility heavy metal hydroxide sludge (Igarashi et al., 2006; Herrera et al., 2007). The second stage employs sodium hydroxide to bring the pH to 8.5 to precipitate ferrous and ferric hydroxides together with the remaining heavy metals (Al-Zoubi et al., 2010). Biological treatment, which involves the use of sulphate-reducing bacteria, removes metals from AMD. This involves the use of various carbon-containing substances (such as manure, wood chips, food waste) to reduce sulphate to sulphide and form a metal sulphide precipitate (Tuttle et al., 1969; Wakao et al., 1979; Wildeman and Laudon, 1989; Ueki, 1991; Dvorak et al., 1992). The addition of the organic materials generates hydrogen sulphide which elevates the reaction temperature, which in turn decreases the effectiveness of the method (Dvorak et al., 1992; Barnes et al., 1992).

Furthermore, cation exchange processes have been proposed for the removal of toxic metals from AMD. However, the operating cost of the process is higher than the value of the metals recovered, and the exchange technology cannot cope well with the vast volumes of AMD discharge (Riveros, 2004; Al-Zoubi et al., 2010).

Recently, the application of membranes to treat AMD by selectively separating the heavy metals has been proposed and tested (Al-Zoubi et al., 2010; Jacangelo et al., 1997; Hilal et al., 2007; Escobar et al., 2000). A membrane is a barrier that selectively allows the desired molecule to permeate while undesirable molecules are retained (see Daramola et al., 2012, 2010 for detailed information on membranes and their classifications). Separation of mixtures by membranes can be carried out more efficiently and at lower energy consumption compared to distillation columns or absorbers (Ulbricht, 2006; Daramola et al., 2012). In addition, membrane technology is highly flexible, and the process can be adapted in response to changes in volumes and concentration of the mixture to be separated (Ulbricht, 2006). Furthermore, application of membrane systems in AMD treatment could reduce the usage of chemicals and sludge production, thereby making the treatment process environmentally benign. In the study by Al-Zoubi et al. (2010), three commercial membranes, namely nanofiltration (NF), ultrafiltration (UF), and reverse osmosis (RO) membranes, were tested for AMD treatment and the results yielded about 98% metal ions rejection. However, for effective treatment of AMD for safe disposal using the aforementioned membranes, two or three stages involving two or three of the membranes would be required, translating into additional capital and operating costs. To avoid this situation, a single-stage treatment of AMD using mixed matrix membranes is proposed in this article.

Mixed matrix membranes (MMMs) are composite membranes containing zeolite crystals within the matrix of the polymer membranes. The presence of crystals within the

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polymer chains improves separation performance, mechanical strength, and thermal stability of polymeric membranes.

Advantages of MMMs over pure polymeric membranes include desirable mechanical properties, economical processability, unique structure of the dispersed inorganic phase, and good surface chemistry. However, the chemical structure of the inorganic fillers, type of inorganic fillers, and surface chemistry are mitigating factors to obtaining high-quality MMMs (Vu and Koros, 2003). In this study, synthesis and performance evaluation of poyethersulphone(PES)-sodalite mixed matrix membranes for AMD treatment are reported.

Sodalites are zeolites possessing a framework with cubic symmetry structure, consisting of vertex linking of AlO4 and SiO4 into four- and six-membered oxygen rings (Breck, 1974). Different types of sodalite can be synthesized for different applications because they can accommodate a wide range of cations as a result of framework flexibility (Breck, 1974). This could be exploited in the treatment of AMD, since AMD consists of dissolved substances (e.g. heavy metals) that are cationic or anionic in nature. Therefore, the sodalite particles could accommodate these substances during selective treatment of AMD. In a recent study, the separation performance of supported sodalite/ceramic membrane for seawater desalination was reported and ultra-pure water was produced from seawater (Khajavi et al., 2010). Considering the outstanding performance of this membrane for water treatment (Khajavi et al., 2010, 2007, 2008), it is expected that using sodalite (SOD) as fillers in PES to fabricate PES-SOD mixed matrix membranes might result in a membrane with reasonable performance, in terms of water fluxes and selectivity, for AMD treatment. Against this background, the results of the preliminary investigation on the synthesis and application of PES-SOD mixed matrix membranes for acid mine drainage treatment are documented in this article.

- 4A=;6A>@<7B

Solvent (N,N-dimethylacetamide, 97%), polyethersulphone (PES), sodium silicate, sodium aluminate, and sodium hydroxide were purchased from Sigma-Aldrich South Africa.

Deionized water was prepared in-house. AMD samples were directly sourced from a small stream at the mine dumps in Dobsonville in Gauteng Province, South Africa. All chemicals were used as supplied without any further purification.

Hydroxysodalite (SOD) crystals were prepared via hydrothermal synthesis using sodium metasilicate, sodium hydroxide pellets, anhydrous sodium aluminate, and deionized water. These materials were mixed together in a polytetrafluoroethylene (PTFE) bottle and stirred for 1 hour on a magnetic stirrer to yield a homogeneous mixture of molar composition ratio 5SiO2:Al2O3:50Na2O:1005H2O. Approximately 45 mL (or 48 g) of the vigorously mixed precursor solution was poured into a Teflon-lined stainless steel autoclave and subjected to hydrothermal synthesis at 413 K for 3.5 hours as described by Khajavi et al. (2010). At the end of the hydrothermal synthesis, the as-prepared SOD crystals were washed thoroughly with deionized water until

Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes the pH of the water was neutral. The washed crystals collected on filter paper were dried overnight at 373 K in an oven.

A homogeneous mixture for the fabrication of each membrane was prepared by measuring specific amounts of SOD crystals, polymer, and solvent with the ratio of SOD/PES to solvent in the mixture maintained at 1:9 throughout the syntheses. The amount of the PES was kept at 0.40 g throughout while the quantities of SOD particles and solvent were varied. Consequently, the weight percentages of the SOD crystals in the synthesized PES-SOD membranes were 5 wt.%, 10 wt.%, and 15 wt.%. Membranes were fabricated by hand-casting the homogeneous mixture on a glass plate using â&#x20AC;&#x2DC;DR BLADEâ&#x20AC;&#x2122;. Reproducibility of synthesis was ensured by fabricating two batches under the same conditions, but at different times and locations. In addition, pure PES membrane (with 0 wt.% SOD) was synthesized for comparison. Figure 1 depicts the steps involved in the synthesis of the membranes.

The morphology and crystallinity of the synthesized SOD crystals were checked with scanning electron microscopy (SEM) using energy-dispersive X-ray spectroscopy (EDS) (Phillips XL 20), and X-ray diffractometry (XRD) (Bruker D8 advance X-ray diffractometer) using CoKι radiation (Ν=0.179 nm) at a scan rate of 0.25 seconds per step and a step size of 0.02°, respectively. Further confirmation of the purity of the SOD crystals was obtained using Fourier transform infrared (FTIR) spectroscopy, conducted with a Bruker IFS spectrometer using KBr pellets as background.

Furthermore, the morphology of the fabricated mixed matrix membranes was examined using SEM.

The performance of the membranes during AMD treatment was evaluated using a cross-filtration set-up depicted in Figure 2. Filtration tests were conducted at a feed temperature of 298 K and a pressure of 1.1 bar, using the membrane of effective permeation area 45 cm2. Atomic absorption spectrophotometry (AAS) was used to determine the concentration of various metal ions in the AMD before treatment (feed stream) and after treatment (permeate and retentate streams). The concentration of the metal ions in raw AMD as per the AAS analysis is summarized in Table I. The pH of the raw AMD obtained from the pH meter (model: HI 2550 pH/ORP and EC/TDS/NaCl meter) was 2.28. The membrane flux and the rejection (expressed in percentage) of the metal ions were obtained using Equation [1] and Equation [2]), respectively: [1] where Qp is the permeate mass flow rate (g/min), Jp is the permeate flux (g.cm-2.min-1), and A is the effective membrane area (cm2).

[2] where Ri is the percentage rejection of component i (%), and Cf and Cp are the concentrations of component i in the feed and permeate streams (mg/L), respectively.

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Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes

<@;?>;8B8?64?:;@;?>B?3B@2AB +,B5:A9B;>B@2;: :@59& Cation

Concentration (mg.L-1) pH= 2.28

Cu2+ Zn2+ Fe3+ Pb2+ Mn2+ Al3+ Mg2+

15.98 86.47 833.0 4.300 51.58 1370 848.8

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The morphology of the synthesized particles is shown in the SEM image in Figure 3(a). Figure 3(b) and Figure 3(c) confirm the crystallinity and the purity of the synthesized SOD crystals. The typical cubic shape of the SOD crystal is visible in Figure 3(a), confirming the formation of SOD crystals during the synthesis. Other morphological shapes such as nano-rod crystals were observed alongside the cubic SOD crystals in Figure 3(a). The same observation has been reported in the literature (Kundu et al., 2010). Figure 3(b) reveals the formation of pure SOD crystals when compared to standards developed by the Joint Committee on Powder Diffraction Standards (http://www.icdd.com), and the EDS analysis of the SOD crystals showed a Si/Al ratio of 1â&#x20AC;&#x201C;1.5, indicating a SOD framework. The FTIR patterns depicted in Figure 3(c) confirm the appearance of all characteristic vibrational bands of SOD crystals. The strong broad band centred at approximately 1000 cm-1 could be attributed to the asymmetric stretching vibration of T-O-T (T=Si, Al). The symmetric stretching vibration of T-O-T is vividly shown around 740 and 660 cm-1. The results obtained from the FTIR analysis of the SOD are consistent with the literature (Yao et al., 2006; Breck, 1974).

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Figure 4 shows that SOD crystals were well distributed within the matrix of the polymer and that the ratio of the fractional free volume (FFV) of the polymer to the amount of sodalite particles within the polymer matrix decreased at increasing SOD loading. The observed difference between the loaded membranes and the unloaded polymeric membrane can be seen by comparing Figure 4(a) with Figures 4(b)-(d). The presence of embedded SOD is clear from Figure 4(b)â&#x20AC;&#x201C;Figure 4(d), while there are no SOD particles in Figure 4(a). The presence of embedded SOD crystals in the PES confirms successful fabrication of a PES-SOD mixed matrix membrane.

The results of the mechanical property evaluation using a TA.XT Plus texture analyser at ambient temperature are depicted in Figure 5. The tensile strength and the Youngâ&#x20AC;&#x2122;s modulus of the synthesized membranes increased with increasing SOD loading. This is consistent with the literature (Shen and Lua, 2012). The 15 wt.% loaded membrane displayed the largest tensile strength of 10.62 MPa, an

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Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes increase of about 213% compared to that of the PES membrane (0 wt.% SOD loaded membrane). This observation further confirms the enhancement of the mechanical strength of polymer membranes with the addition of fillers, and the increase in strength with increasing filler loading (Wei et al., 2014). A slight increase in the Youngâ&#x20AC;&#x2122;s modulus for 15 wt.% SOD loaded membrane compared to those for 5 wt.% and 10 wt.% loaded membranes could be attributed to the ineffective dispersion method adopted in the synthesis of the membranes. At higher particle loadings, agglomeration of the particles may occur within the polymer matrix, causing a slight decrease in the Youngâ&#x20AC;&#x2122;s modulus (Wei et al., 2014; Shen and Lua, 2012; Yu et al., 2013). However, this could be avoided if an effective dispersion method is used for the synthesis of the membranes (Daramola et al., n.d.).

The AMD sample contained high concentrations of iron, aluminium, and magnesium ions, and moderate concentrations of copper (Cu2+), zinc (Zn2+), lead (Pb2+), and manganese (Mn2+) ions (see Table I). The high Fe3+ concentration could be attributed to continuous oxidation of Fe2+ to (Fe3+) as a result of a pH lower than 3 (Stumm and Morgan, 1996). The AMD sample was considered hard since the concentration of magnesium ions (848.78 mg/L) was greater than 120 mg/L (Al-Zoubi, et al., 2010).

The performance of each membrane was evaluated at a pump speed of 12 revolutions per second. The concentrations of metal ions and the pH of the permeate sample from each membrane were determined using AAS and a pH meter, respectively. Figure 6 shows the pH results of the permeate sample for each membrane after the treatment. A small increase in the pH from 2.28 for the feed sample to 2.50

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(about 9.65% increase) was observed for the permeate samples from the four membranes after the treatment. The small change in the pH could be attributed to a smaller rejection of Fe3+ during the AMD treatment, because the presence of Fe3+ lowers pH (Stumm and Morgan, 1996), and a higher rejection of Fe3+ is expected to increase the pH. In

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Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes

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addition, an increase in the pH was observed at increasing SOD loading, implying that the performance of the PES-SOD membranes was enhanced with greater SOD loading.

Figure 7 shows that the permeate flux of the membranes increased at increasing SOD loading (0 wt.% to 15 wt.% loading), reached a maximum of 1.85 g.cm-2.min-1 at 10 wt.% loading, and then decreased to 1.43 g.cm-2.min-1 at 15 wt.% loading. The observed increase in the membrane flux of the PES-SOD membranes when compared to that of the PES (0 wt.% loading) membrane could be attributed to the presence of the SOD crystals and the hydrophilic nature of the crystals. In addition, the kinetic diameter of water molecules (2.65 Ă&#x2026;) and the average cage dimension of the SOD particle (2.6 Ă&#x2026;) are comparable, implying that the SOD particles provide additional permeation channels for the water molecules in the PES-SOD when compared to the membrane flux of the unloaded PES membrane.

The water transport mechanism in porous hydrophilic membranes has been described by a sorption-diffusion mechanism and preferential sorption capillary flow (PSCF) model (Sourirajan, 1963). According to the sorption-diffusion mechanism, water molecules preferentially adsorb to the hydrophilic membrane surface, diffuse through the membrane pores, and desorb from the membrane. The PSCF model describes transport of water through such membranes as occurring by hydrogen bonding, during which water molecules are attracted by the hydrogen bonds within the membrane and permeate through the membrane pores.

Indeed, the separation efficiency of membranes depends on their surface properties (hydrophilicity or hydrophobicity) and pore dimensions (with respect to the molecular size of the adsorbates). The permeation of water molecules through the synthesized PES-SOD membranes is therefore expected to be governed by the PSCF model because cages of SOD crystals are occluded with water, indicating that the transport of water molecules through the crystals could occur by hydrogen bonding. On the other hand, the observed decrease in the membrane flux at higher (15 wt.%) SOD loading could be attributed to membrane fouling due to the retention of increased numbers of particles from the AMD. However, it is noteworthy to mention that the AMD sample was pre-treated to remove the suspended particles before the filtration tests.

Interestingly, the 15 wt.% loaded membrane did not lose its selectivity, indicating few or no defects in the membrane.

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Furthermore, the performance of the PES-SOD membranes was evaluated using selectivity of the membrane to the metal ions. Figure 8 depicts the percentage rejection of each metal ion by the membranes as a function of the SOD loading. Lead (Pb2+) was the most rejected of all the metal ions with a maximum rejection of 57.44%. This is expected because the kinetic diameter of Pb2+ is 2.66 Ă&#x2026; (Salam et al., 2012) and the average cage dimension of the SOD particles is 2.6 Ă&#x2026; (Breytenbach et al., 2007). Therefore, more Pb2+ was retained by the membrane, thereby resulting in high selectivity of the membrane for Pb2+. Rejection of magnesium (Mg2+) increased from about 20% to about 50% with increasing SOD loading. However, to soften the AMD, a higher rejection of Mg2+ is required. Mn2+ was the least rejected metal ion with a rejection from 1% to 6%. The maximum percentage Cu2+ rejection of 17.6% displayed by the membranes was not very encouraging. This performance could be attributed to the smaller kinetic size of the Cu2+ (about 1.44 Ă&#x2026;) compared to the average pore dimension of SOD crystals (Breytenbach et al., 2007). Cu2+ could be easily filtered through the embedded SOD particles. It is evident from the results that none of the metals ions in the AMD sample was well rejected with the synthesized membranes.

However, modifications to the membranes by functionalizing the SOD particles and optimizing the synthesis protocol could dramatically enhance the performance of the PES-SOD membranes. Additionally, process conditions during the treatment of AMD with the membranes could be optimized to enhance the flux and selectivity of the membranes.

?>875:;?> Results of a preliminary investigation of the application of PES-SOD mixed matrix membranes to AMD treatment are reported for the first time. The synthesis protocol adopted resulted in the fabrication of selective and reproducible PESSOD mixed matrix membranes. Three different PES-SOD mixed matrix membranes were fabricated with different SOD loadings, as well as a pure polymeric membrane for comparison. The experimental results showed that the performance of a pure polymeric membrane (selectivity and flux) is enhanced by loading SOD crystals within the matrix of the PES polymer. Results of the performance evaluation of

Polyethersulphone-sodalite (PES-SOD) mixed-matrix membranes

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the membranes for AMD treatment revealed the best water flux at 10 wt.% SOD loading and a pump speed of 12 revolutions per second. The PES-SOD loaded with 15 wt.% SOD crystals displayed the best selectivity towards Pb2+ (57.44% rejection). The results from this study have shown the potential for application of PES-SOD membranes in the treatment of AMD. However, optimization of the synthesis protocol for the fabrication of the membrane and process conditions might be required to enhance the performance of the membranes for AMD treatment. Nevertheless, the results documented in this article could pave the way for further research and development in this area.

8 >?%7A9/A6A>@: M.O.D. acknowledges Professor F. Kapteijn and Professor J. Gascon of the Delft University of Technology, The Netherlands, for the opportunity to gain from their wealth of experience in the membrane field. The authors also acknowledge Dr D. Nkazi for assisting with the collection of the AMD sample. This work emanated from the results of the 4th year BSc (Eng) chemical engineering research project conducted by BS and SM.

A3A=A>8A:

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http://dx.doi.org/10.17159/2411-9717/2015/v115n12a12

The accuracy of calcium-carbonatebased saturation indices in predicting the corrosivity of hot brackish water towards mild steel

by A. Palazzo*, J. van der Merweâ&#x20AC; , and G. Combrinkâ&#x20AC;Ą

(,;>/8<8 Industry has always relied on waterâ&#x20AC;&#x2122;s inherent ability to inhibit mild steel corrosion by virtue of its levels of calcium hardness and total alkalinity.

This research seeks to verify the application of this principle to brackish water used in industrial systems at moderately elevated temperatures. A brief review is first given of the conventional calcium-carbonate-based scale or corrosion predictive indices. Laboratory corrosion tests were performed at various levels of calcium hardness and total alkalinity, resulting in the generation of an empirically derived nonlinear regression model. The newly developed model and the existing indices were then compared statistically in predicting the corrosivity of brackish water in contact with mild steel at 45ÂşC. The accuracy, broader application, and relevance of the indices are also discussed. =, >:58 saline water, brackish water, cooling, corrosion prediction, computer modelling, Langelier Saturation Index, Ryznar Stability Index, mild steel, calcium carbonate saturation.

RSI (Ryznar Stability Index) = 2(pHs) - pH [2] PSI (Puckorius Scaling Index) = 2(pHeq) - pH [3] Puckorius uses an equilibrium pH for this index rather than the actual cooling water pH. The index applies for temperatures up to 93°C. pHeq = 1.465 Ă&#x2014; log10 (total alkalinity) + 4.54 [4]

Between 1960 and the mid-1990s the Langelier Saturation Index (LSI) (Equation [1]) (Langelier, 1936) attracted adverse commentary from the municipal potable water community. It was stated that the LSI had no correlation with corrosion rate (Stumm, 1960; Larson and Sollo, 1967; Singley, 1981; Schock, 1984; Piron et al., 1986; Pisigan and Singley, 1987), and based on the empirical evidence it was suggested that the use of the LSI for corrosion prediction should be abandoned (AWWARF and DVGW, 1996). The same sentiment applied to the Ryznar Stability Index (RSI) (Ryznar, 1944) (Equation [2]) and the various other â&#x20AC;&#x2122;corrosion prediction indicesâ&#x20AC;&#x2122; that emerged during this period and that were also grounded on the same principle: â&#x17E;¤ Momentary Excess (ME) (Dye, 1958) â&#x17E;¤ Calcium Carbonate Precipitation Potential (CCPP) (Merrill and Sanks, 1978) â&#x17E;¤ Aggressiveness Index (AI) (Millette et al., 1980) â&#x17E;¤ Driving Force Index (DFI) (Rossum and Merrill, 1983).

LSI (Langelier Saturation Index) = pH - pHs [1] where the variables and their range of applicability are as follows:

Total alkalinity: mg/l CaCO3.

RSI or PSI values 6 and higher indicate increasingly severe corrosive tendencies, whereas values 6 and lower indicate more CaCO3 scaling tendencies.

The PSI (Puckorius and Brooke, 1990), calculated using Equations [3] and [4], is a refinement of the RSI, in which an empirical alkalinity function is derived to modify the calculated pH of saturation for calcium carbonate (pHs). In large industrial and power station cooling systems, either the LSI of PSI is still used to control acid feed or the cycles of concentration for calcium carbonate scale

* Buckman Africa (Pty) Ltd, Hammarsdale, South Africa and part-time MSc student at the School of Chemical and Metallurgical Engineering, Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, South Africa. â&#x20AC; University of the Witwatersrand, Johannesburg, South Africa . â&#x20AC;Ą University of Johannesburg, South Africa. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received July 2014 and revised paper received Aug. 2015.

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pH: measured pH (7.0â&#x20AC;&#x201C;9.5), temperature: 25â&#x20AC;&#x201C;80°C, total dissolved solids <800 mg/l. pHs: the pH at which the cooling water will be saturated. This value is calculated based on the solubility product for calcite, the second dissociation constant for carbonic acid and calcium concentrations, and total alkalinity of the cooling water Positive LSI values indicate â&#x20AC;&#x2DC;oversaturationâ&#x20AC;&#x2122; and a tendency for a protective CaCO3 coating to form, whereas negative values indicate the tendency to dissolve an existing CaCO3 coating.

The accuracy of calcium-carbonate-based saturation indices control. This supports their continued role in predicting the impact of water-soluble species on industrial water systems.

Early research (Larson and Skold, 1957) confirmed that the precipitation/dissolution of calcium carbonate is not the only water quality parameter relevant to the corrosion of distribution systems. Other factors such as the ratios of anions, flow velocity, pH, and calcium concentration also contribute to corrosion rates, but perhaps the best researched is the Larson and Skold Index, also known as the Larson Ratio (LR) (Larson and Skold, 1957, 1958) (Equation [5]).

This index includes the corrosive effects attributable to the chloride and sulphate concentrations.

Larson-Skold Index, Larson ratio (LR) or Corrosivity Index (CI) = ([Cl-] + [SO42-]) / ([HCO3-])

[5]

where [Cl-], [SO42-] and [HCO3-]: meq/litre of chloride, sulphate, and total alkalinity respectively.

The water studied approximated the quality of the Great Lakes waters of North America. The higher the index the more corrosive the water.

Feigenbaum et al. (1978) demonstrated poor correlation between the already-mentioned calcium-carbonate-based indices and the saline waters of the Negev Desert, and therefore developed an empirical index that included the effect of calcium carbonate solubility and the ions of the LR. The reported lack of a definite correlation between the LSI and corrosion rates evident in both the drinking water industry and laboratory-scale closed-loop experiments prompted Pisigan and Singley (1984) to embark on a series of jar tests. The results of the laboratory tests permitted them to empirically derive a four-variable model (Equation [6]) and an eight-variable model (Equation [7]) that could account for 98% of the variations in corrosion rate under the experimental conditions explored. The equations hypothesized indicated that the corrosion rate of mild steel was in fact influenced by factors beyond just the precipitation or dissolution of calcium carbonate.

Pisigan and Singley 4-variable equation: CR4 = ((TDS)0.253 (DO)0.820)/((10SI)0.0876 (Day)0.373) [6] Pisigan and Singley 8-variable equation: CR8 = (Cl)0.509 (SO4)0.0249(Alk)0.423(DO)0.780) / ((Ca)0.676(β)0.0304(Day)0.381(10SI)0.107)

[7]

where TDS (total dissolved solids): mg/l, Ca (calcium): mg/l as Ca, Mg (magnesium): mg/l as Mg, Na(sodium): mg/l as Na, Cl (chloride): mg/l as Cl, SO4 (sulphate): mg/l as SO4, Alk (alkalinity): mg/l as CaCO3, β (buffer capacity): mg/l as CaCO3/pH, DO (dissolved oxygen): mg/l as O2.

Pisigan and Singleyâ&#x20AC;&#x2122;s eight-variable model (1984) suggests that increasing chloride, sulphate, alkalinity, and dissolved oxygen levels would accelerate corrosion, whereas increases in calcium concentration, buffer capacity, saturation index, and exposure time would lead to decreasing corrosion rates. In this hypothetical equation, the alkalinity is declared to accelerate rather than reduce corrosion, as is commonly known. The authors attributed this contradiction to the overwhelming influence of the increased ionic strength over the effect of alkalinity with increasing dosages of sodium bicarbonate while attempting to raise the alkalinity during the laboratory experiments.

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The first use of the buffer capacity (β) appeared in the literature pertaining to the subject of corrosion prediction in the work by Stumm (1960). Laboratory tests with synthetic solutions helped explain the mutual interaction of corrosionstimulating and -inhibiting factors of natural waters, namely: pH, buffer capacity, CaCO3 deposition, and alkalinity. This study was thought to at least partially explain the increase in corrosion rates with increasing pH between the values of 7.0 and 8.5.

Several studies found that as the pH approached 8.4, either from a higher or lower pH value, the corrosion rate of cast iron increased with decreasing buffer intensity. It is presumed that this effect occurs as a result of there being fewer but larger cathodic and anodic areas, thereby encouraging the electrochemical cell (Stumm, 1960).

Based on the independent studies reported by Pisigan and Singley (1987) and Imran et al. (2005a), it was possible to propose a modified Larson ratio (LRM) that would compensate for the increase in total dissolved solids with the increasing alkalinity by including the sodium ion concentration.

Imran continued his work on potable water distribution systems and published an article (Imran et al., 2005a) that included a wider range of parameters in an empirically derived nonlinear model. The model is based on the change in apparent colour (Î&#x201D;C in cpu) as a measure of corrosion in distribution lines, as it was found to be a reliable surrogate measurement of total iron. Calcium and pH were not deemed significant during the statistical modelling, because all tests were performed in waters stabilized for CaCO3 solubility.

Alkalinity was the only variable that could be effectively controlled by chemical addition.

In the arena of oilfield brines, where the high salinity affects the ionic strength and influences the calcium carbonate solubility, the Stiff-Davis Index (SDI) (Equation [8]) has been used (Stiff and Davis, 1952) in place of the Langelier Index. Waters with total dissolved solids levels higher than 4000 mg/l require that the SDI is used.

SDI = pH - pCa- pAlk â&#x20AC;&#x201C; K

[8]

where pH: pH measured, pCa = -log (Ca in mg/l as Ca2+), and pAlk = -log (M alkalinity in mg/l as CaCO3), K = constant based on the total ionic strength and temperature.

Is (O & T scaling Index) = log (TCa Alk) + pH â&#x20AC;&#x201C; 2.78 + 1.143 Ă&#x2014; 10-2 T â&#x20AC;&#x201C; 4.72 Ă&#x2014; 10-6 T2 â&#x20AC;&#x201C; 4.37 Ă&#x2014; 10-5 P â&#x20AC;&#x201C; 2.05 Ă&#x2014; I½ + 0.727 Ă&#x2014; I [9] where I (ionic strength): moles/l, TCa (calcium): moles/l as Ca, Alk (alkalinity): moles/l as HCO3-, T (temperature):â °F, P (pressure): psi.

As with the Langelier Saturation Index, positive SDI or Is values indicate â&#x20AC;&#x2DC;oversaturationâ&#x20AC;&#x2122; and a tendency for a protective CaCO3 coating to form, whereas negative values indicate the tendency to dissolve an existing CaCO3 coating Higher CR values indicate higher corrosion rates in mils per year (mpy).

The Stiff-Davis (Stiff and Davis, 1952) method is one of the easiest ways to calculate calcium carbonate scaling tendencies (Calcite Saturation Index) in brines and it is valid

The accuracy of calcium-carbonate-based saturation indices for temperatures from 0â&#x20AC;&#x201C;90°C and ionic strengths from 0â&#x20AC;&#x201C;4.

This index does not take into account the pressure and carbon dioxide concentration. It requires that the pH is measured on a fresh sample to avoid inaccuracies. As ionic strength and/or the temperature increase, so the K value decreases, resulting in a higher SDI, indicating a higher calcium carbonate scaling tendency. Higher concentrations of calcium or alkalinity would also lead to higher SDI values, also resulting in increased scaling tendencies. Calculating the SDI requires a calculation of the ionic strength, knowing the temperature of the operation, and looking up the K value in a K versus ionic strength graph (Stiff and Davis, 1952).

The Oddo-Tomson (1982) method is an alternative index applicable to high ionic strength waters for predicting the formation of calcium carbonate and various sulphate scales.

It is valid between temperatures of 0â&#x20AC;&#x201C;200ÂşC, ionic strengths of 0â&#x20AC;&#x201C;4.0, and pressures of 1â&#x20AC;&#x201C;1380 bar (0â&#x20AC;&#x201C;20000 psig) (Equation [9]). The calculation was reported by Oddo and Tomson (1982) to be accurate at high and low temperatures and pressures. The calculation can be easily performed in the field and is said to work well when applied to geopressured wells.

The prediction of the corrosivity of underground minewaters towards mild steel was also explored by White and Higginson (1985). It was reported that the corrosion takes place under cathodic control, with the metal acting as a substrate for the cathodic reaction. Thus the corrosivity of minewaters is largely dependent upon on the oxygen concentration and the pH of the water.

6</4=;?A@;5A4=?3>5>9>2, In determining the relationship between the calcium hardness and alkalinity and the corrosion rate of mild steel in brackish water at elevated temperatures (35â&#x20AC;&#x201C;45Ë&#x161;C), numerous laboratory tests were conducted with synthetic solutions.

The main aim of the laboratory evaluation was to determine the impacts of temperature (between 35Ë&#x161;C and 45Ë&#x161;C), calcium hardness (between 50 mg/l and 100 mg/l as Ca2+), and total alkalinity (between 55 and 220 mg/l as CaCO3) on the corrosivity of brackish water towards mild steel. Thus, the limiting conditions for the applicability of this study are waters having a quality range defined in Table I. C1010 (mild steel) corrosion coupons were subjected to synthetic test solutions (4000 ml) stirred at 100â&#x20AC;&#x201C;110 revolutions per minute (r/min) for 72 hours. The coupons were then removed, cleaned with a water wash to finger-

touch, followed by an ethanol wipe; and then oven-dried, weighed and the corrosion rates calculated based on their weight loss. The methods followed were based on ASTM methods: â&#x17E;¤ G31-72 (Reapproved 1999): Standard Practice for Laboratory Immersion Corrosion Testing of Metals â&#x17E;¤ G1-90 (Reapproved 1999: Standard Practice for Preparing, Cleaning, and Evaluating Corrosion Test Specimens.

A CorraterÂŽ (Rohrback Cosasco) was used to measure the general corrosion rate and imbalance (i.e. indicator of the tendency for localized corrosion). The test solutions were also tested for their total iron concentrations and compared against the coupon method and CorraterÂŽ readings. Each set of tests was performed in a batch of six tests in a â&#x20AC;&#x2122;Laboratory Scale and Corrosion Test Stationâ&#x20AC;&#x2122;, a Buckman proprietary corrosion testing device, over a period of three days (refer to Figures 1 and 2).

Each of the six stations has its dedicated 5-litre beaker and an overhead paddle stirrer, dedicated temperature probe, hot plate, three coupon holders, and a CorraterÂŽ probe

=869?8 Table II lists the target calcium and total alkalinity concentrations, the temperatures explored, and the total iron concentrations of the test solutions. Table III summarizes the corrosion coupon results and the CorraterÂŽ readings taken over the three days.

Figure 3 compares the mild steel coupon corrosion rates (mm/a) for the two positions, and Figure 4 provides a threedimensional view of the correlations between the three corrosion measurements: the average coupon corrosion rate, the average CorraterÂŽ general corrosion rate, and the total iron concentrations.

Figure 5 reflects the impact of a 10ÂşC difference in temperature on the corrosion rates as well as the impact of higher and lower alkalinity. It includes the error bars based on the maximum standard deviation â&#x20AC;&#x201C; that is, a value of 0.07 mm/a â&#x20AC;&#x201C; for the entire set of coupon data recorded during the 30 test runs.

Statistical correlations were performed between the average coupon corrosion rate and the various parameters

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pH Calcium (mg/l as Ca2+) Total alkalinity (mg/l as CaCO3) Magnesium (mg/l as Mg2+) Chloride (mg/l as Cl ) Sulphate (mg/l as SO42-) Fluoride (mg/l as F )

7.8 (6.0â&#x20AC;&#x201C;8.1) 50â&#x20AC;&#x201C;100 (49â&#x20AC;&#x201C;97) 55â&#x20AC;&#x201C;220 (19â&#x20AC;&#x201C;228) 27.3 (22â&#x20AC;&#x201C;30) 750 (717â&#x20AC;&#x201C;822) 1125 (1100â&#x20AC;&#x201C;1400) 10 (8â&#x20AC;&#x201C;10)

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The accuracy of calcium-carbonate-based saturation indices

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measured during the experiment. Statistically significant linear model correlations, with a 95% confidence level, were found between the average coupon corrosion rate and the following parameters: the initial and final calcium concen-

trations, the initial total alkalinity, the average CorraterÂŽ general corrosion rates, and the total iron levels. Inverse relationships were evident between the average coupon corrosion rate and the calcium and total alkalinity values,

@:,<;2A7@97<64A@;5A@9*@9<;<?, A?@:2=?A%@96=8A@;5 .<;@9A?>?@9A<:>;A9=%=98A Run Target concentrations/conditions Total iron Calcium Total Temperature alkalinity mg/l as Ca2+ mg/l as ÂşC mg/l as Fe3+ CaCO3 (total) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

50 50 50 50 50 50 62.5 62.5 62.5 62.5 62.5 62.5 75 75 75 75 75 75 87.5 87.5 87.5 87.5 87.5 87.5 100 100 100 100 100 100

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36.8 15.5 14 8.7 10.1 13 36.6 28.6 30.5 19.3 21.6 17.3 30.1 8.1 28.6 25.7 31.4 38.4 12.6 15.4 9.8 9.4 12.2 22.4 9.9 4.7 8.4 5.2 7.7 4.4

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4.1 8.1 6.6 6.6 1.1 2.6 1.9 6.5 9.2 1.0 3.7 1.3 2.2 6.6 3.1 4.4 13.3 9.6 3.4 0.3 6.1 1.7 0.9 0.7 1.1 0.1 3.5 2.6 1.1 0.4

34 12.6 11.1 8.3 8.7 10.1 34.4 21.1 29.9 21.3 19.8 17.8 30.5 9.2 31.4 30.4 30.1 39.4 11.4 14.9 10.4 7.6 10.6 19.0 6.4 4.6 7.6 4.1 8.6 15.6

1.1 4.4 3.4 2.1 0.1 2.4 6.3 12.5 6.8 7.4 5.3 6.4 6.6 6.6 6.6 6.2 8.6 6.7 2.2 1.0 0.9 0.8 2.6 1.0 2.2 3.2 4.4 0.2 2.6 5.5

35.5 12.1 10.9 9.3 8.7 10.4 33.5 22.8 20.7 19.5 19.5 17.7 30.4 12.1 32.4 33.4 33.4 38.9 14.4 15.2 8.1 7.7 9.5 16.7 -

2.6 5.3 3.7 7.1 7.1 2.3 5.5 0.8 5.6 5.2 3.3 3.4 2.1 3.1 3.8 9.8 6.7 1.1 6.6 2.2 0.9 1.3 0.2 1.5 -

0.48 0.38 0.32 0.25 0.24 0.30 0.50 0.39 0.30 0.28 0.32 0.34 0.37 0.26 0.19 0.14 0.25 0.25 0.34 0.23 0.16 0.22 0.29 0.16 0.26 0.13 0.14 0.22 0.37 0.69

0.46 0.35 0.28 0.21 0.20 0.26 0.46 0.38 0.29 0.19 0.24 0.26 0.34 0.25 0.20 0.18 0.24 0.20 0.29 0.22 0.15 0.20 0.25 0.15 0.24 0.13 0.14 0.21 0.35 0.65

4.3 8.6 7.4 6.9 3.5 7.1 1.2 1.1 1.5 1.3 9.8 9.3 6.2 2.2 2.2 6.2 2.9 6.2 1.1 1.8 3.4 0.6 0.1 0.8 3.3 2.2 0.2 0.9 0.4 10.9

whereas direct moderate correlations were noted between the average coupon rates and both the average CorraterÂŽ general corrosion rates and the total iron concentrations. The average CorraterÂŽ general corrosion rates did not correlate well with the total iron values.

Contour plots (Figures 6 to 9) were drawn to reveal the combined effect of the calcium hardness and total alkalinity on the average coupon corrosion rate. The initial or final calcium concentrations and initial or final total alkalinity values were plotted against the average coupon rate.

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The accuracy of calcium-carbonate-based saturation indices

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how the response variable changes as the particular predictor variables change. This was done without taking into account the impact of the 10ÂşC temperature difference (refer to Equation [10]): Corrosion (mm/a) = 4.58E-6 Ca2 - 8.85E-3 Ca + 4.64E-5 (Ca Ă&#x2014; M [10] alk) - 9.30E-3 Ă&#x2014; M alk + 1.90E-5 M alk2 + 1.26

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A nonlinear multivariate regression analysis was conducted to predict the relationship between coupon corrosion rate and various predictors in order to determine

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where Ca = mg/l calcium as Ca and M alk = mg/l total alkalinity as CaCO3.

Figure 10 serves to confirm the accuracy of the empirically derived nonlinear regression equation by comparing it to the laboratory coupon corrosion data. An R2 adjusted value of 90.06% was obtained. The graph also indicates where large residuals and an unusual result occurred, explicitly at the upper section of curve.

The empirically derived equation was then compared statistically against the predictive indices discussed in the literature survey. This was performed by using the test solution target values and the comparison performed at both 35ÂşC and 45ÂşC. The results of the comparison are given in Table IV and shown by the scatter plot correlations in Figure 11. The statistical analysis indicated that the calculated rate

The accuracy of calcium-carbonate-based saturation indices

(?@?<8?<7@99,A8<2;<.<7@;?A:=9@?<>;83</8A$=? ==;A?3= 7@9769@?=5A:@?=A@;5A?3=A>?3=:A<;5<7=8 -@9769@?=5A:@?=A144 @0A Ca

-0.408 0.093 TOT Alk (SGO) -0.344 0.162 CR8 Corrosion In -0.053 0.833 Buffer Capacity -0.344 0.162 CR4 Corrosion In 0.529 0.024 CCPP (mg/l) -0.259 0.300 Is (Oddo &Tomson, 1982) -0.536 0.022 Ionic Strength (M) -0.531 0.023 (Stiff and Davis,1952) -0.570 0.013 CaCO3 -0.180 0.474 CaF2 0.176 0.485 Langelier -0.532 0.023 RSI 0.526 0.025 PSI 0.539 0.021 Larson Skold 0.545 0.019 CaCO3 FIME -0.038 0.880 Note: the top number is the Pearson coefficient of correlation, r.

As a rule of thumb, r > 0.65 or R < 0.65 indicate correlation.

The bottom number is the p-value. P-values â&#x2030;¤ 0.05 indicate correlation at the 95% confidence level.

had the statistically significant moderately strong relationships at a 95% confidence level shown in Table V. A contour plot (Figure 12) of the derived multivariate nonlinear regression equation (Equation [10]) was included to facilitate a visual comparison with the contour plots of the laboratory coupon corrosion data (Figures 6â&#x20AC;&#x201C;9). Contour plots (Figures 12â&#x20AC;&#x201C;19) of statistically significant indices taken from the literature, as per Table V, were also included for further comparisons.

<87688<>; In order to first determine the correlation between the two coupon positions in the test vessel it was necessary to compare their results by means of a paired t-test. The paired t-test for the mean of coupon 1 versus the mean of coupon 2

(644@:,A>.A?3=A8?@?<8?<7@99,A8<2;<.<7@;?A7>::=9@?<>;8 $=? ==;A?3=A7@9769@?=5A7>::>8<>;A:@?=A@;5A?3= =8?@$9<83=5A<;5<7=8 =2@?<%=A:=9@?<>;83</8

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Is(Oddo), Oddo-Tomson (1982) method Ionic strength

CR4, 4 variable model (Pisigan and Singley, 1984) RSI, Ryznar Stability Index (Ryznar, 1944) PSI, Puckorius or Practical Scaling Index (Puckorius and Brooke, 1990) LR, Larson Skold Index, also known as the Larson Ratio (Larson and Skold, 1957, 1958).

SDI, Stiff Davis Index (Stiff and Davis, 1952) LSI, Langelier Saturation Index (Langelier, 1936)

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The accuracy of calcium-carbonate-based saturation indices

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showed that the two coupon positions were statistically different at a 95% confidence level. The two coupon positions did, however, demonstrate similar trends, as apparent in Figure 3; hence the average coupon rate was adopted as the result for each test.

A comparison of the plots of the average coupon rate against either the average CorraterÂŽ readings or the test solution total iron concentrations (Figure 4) demonstrated moderate direct correlations. The strength and direction of these correlations therefore supported the use of the average coupon rate for the continued corrosion studies. There was, however, a substantial discrepancy between the couponbased rates and the CorraterÂŽ readings, with the latter indicating rates that were approximately 54 times higher. The findings of this investigation were addressed by Van der Merwe and Palazzo (2015), and similar concerns over the lack of correlation between linear polarization resistance probe measurements and coupon immersion tests have also recently been investigated by Wu et al. (2015).

Figure 5 reflects the impact of a 10ÂşC difference in temperature, where the higher temperature produced higher

corrosion rates at the lower targeted calcium hardness values of 50 and 62.5 mg/l (as Ca). At the higher calcium hardness values both temperatures resulted in similar corrosion rates.

Figure 5 depicts the impact of different total alkalinities. It is apparent that higher alkalinity resulted in lower coupon corrosion rates, with the exception of the increased corrosion evident for the points corresponding to the combination of a high target calcium hardness (above 75 mg/l as Ca) and high target alkalinity (165 mg/l as CaCO3).

The contour plots (Figures 6 and 7) for the average coupon rate versus calcium and total alkalinity for the corrosion tests performed at 35ÂşC demonstrated: â&#x17E;¤ Lowest corrosion rates at high calcium (>70 mg/l as Ca) and high total alkalinity (>90 mg/l as CaCO3) â&#x17E;¤ Highest corrosion rates at high total alkalinity (>90 mg/l as CaCO3) and low calcium (<60 mg/l as Ca).

The contour plots (Figures 8 and 9) for the average coupon rate versus calcium and total alkalinity for the corrosion tests performed at 45ÂşC demonstrated: â&#x17E;¤ Lowest corrosion rates at: â&#x20AC;˘ High calcium (80â&#x20AC;&#x201C;100 mg/l as Ca) and moderately high total alkalinity (65â&#x20AC;&#x201C;110 mg/l as CaCO3) â&#x20AC;˘ Moderate calcium (60â&#x20AC;&#x201C;80 mg/l as Ca) and moderate total alkalinity (150-200 mg/l as CaCO3 â&#x17E;¤ Highest corrosion rates at low total alkalinity (<50 mg/l as CaCO3) and either low calcium (<50 mg/l as Ca) or high calcium (>85 mg/l as Ca).

The regions of either low or high corrosivity are similar for both the lower temperature of 35ÂşC and higher temperature of 45ÂşC. The empirically derived nonlinear regression equation, based on only the solutionâ&#x20AC;&#x2122;s initial calcium and initial total alkalinity, was confirmed to account for 90.06% of the variations in the average corrosion coupon data.

Statistically significant moderately strong relationships, at a 95% confidence level, were evident between the derived nonlinear regression equation and the various established indices, namely: LSI, Langelier Saturation Index (Langelier, 1936), RSI, Ryznar Stability Index (Ryznar, 1944), LR, Larson Skold Index also known as the Larson Ratio (Larson and Skold, 1957, 1958), SDI, Stiff Davis Index (Stiff and Davis, 1952), Is (Oddo), Oddo-Tomson (1982) method, ionic strength, CR4, four-variable model (Pisigan and Singley, 1984), and PSI, Puckorius, or Practical Scaling Index (Puckorius and Brooke, 1990).

A comparison of the contour plot of the new model versus those of other indices, for the set of target values considered revealed some subtle differences between them. One of the more obvious differences was the impact of the calcium concentration on the corrosivity, as evident by the relatively steeper diagonal contour lines for some of the indices, particularly in the new model, LSI, RSI, and PSI (Figures 12, 16, 17, and 18, respectively). As per the literature, it appears that a number of the authors included calcium in their empirically derived predictive models: LSI, RSI, SDI, and CCPP. The same can be said of pH for the LSI, RSI, PSI, SDI, and Is indices.

Linear regression analysis of the correlation between the average coupon corrosion rates and the various predictors confirmed the role of the initial pH and the initial calcium concentration.

The accuracy of calcium-carbonate-based saturation indices ->;7968<>;

LANGELIER, W.F. 1936. The analytical control of anti-corrosion water treatment.

Journal of the American Water Works Association, vol. 28, no. 10. pp. 1500â&#x20AC;&#x201C;1521.

Although the average coupon rate, the total iron concentrations, and the CorraterÂŽ general corrosion rate readings appeared closely related, it was possible to find statistically significant linear correlations, at a 95% confidence level, only between the average coupon rate and total iron concentration as well as the average coupon rate and the CorraterÂŽ general corrosion readings.

It was also confirmed that raising the calcium hardness and/or total alkalinity within the range of chemistries explored for the application of the brackish water in a cooling system does reduce mild steel corrosion. It did, however, become apparent that calcium carbonate saturation or supersaturation can lead to precipitation, resulting in reduced levels of calcium and alkalinity which in turn leads to increased corrosion rates.

The empirically derived equation was at best capable of only moderately strong correlations with any of the numerous calcium-carbonate-based models found in the literature. A comparison of the formulae of the statistically significant eight indices and a comparison to the remaining six non-statistically significant and weakly correlated indices revealed that the latter six were linearly related to either the calcium concentration or total alkalinity, whereas the former eight indices are a function of either the log or the inverse of either the calcium concentration and/or total alkalinity. The newly proposed empirically derived nonlinear regression model differes from both sets of indices in that it is based on a quadratic equation incorporating both the calcium concentration as Ca2+ and total alkalinity in mg/l as CaCO3.

As stated in the introduction, it would be grossly inaccurate to base the calculation of the corrosivity of brackish water solely on its calcium concentration, total alkalinity, and temperature without giving any consideration to the many other factors or conditions prevailing in a typical industrial system. What is, however, apparent from the study, since it is based only on changes in the calcium hardness and total alkalinity, is that the empirically derived model may prove more accurate than most of the existing commonly found indices at estimating the corrosivity of brackish water, of similar characteristics to the chemistry explored, on mild steel between 35 and 45ÂşC.

SCHOCK, M.R. 1984. Temperature and ionic strength corrections to the Langelier Index revisited. Journal of the American Water Works Association, vol.

76, no. 8. pp. 72â&#x20AC;&#x201C;76.

SINGLEY, J.E. 1981. The search for a corrosion index. Journal of the American Water Works Association, vol. 73, no. 11. pp. 579â&#x20AC;&#x201C;582.

AWWARF and DVGW-TZW. 1996. Internal Corrosion of Water Distribution Systems. 2nd edn. American Water Works Association, Denver, CO. pp. 29â&#x20AC;&#x201C;70.

STIFF, Jr., H.A. and DAVIS, L.E. 1952. A method for predicting the tendency of oil field water to deposit calcium carbonate. Petroleom Transactions of AIME, vol. 195. p. 213.

DYE, J.F. 1958. Correlation of the two principle methods of calculating the three kinds of alkalinity. Journal of the American Water Works Association, vol.

50, no. 6. pp. 801â&#x20AC;&#x201C;820.

STUMM, W. 1960. Investigation of the corrosive behavior of waters. Journal of the American Society of Civil Engineers, Sanitary Engineering Division, vol. 86, no. SA6. pp. 27â&#x20AC;&#x201C;45.

FEIGENBAUM, C., Gal-Or, L., and Yahalom, J. 1978. Scale protection criteria in natural waters. Corrosion, vol. 34, no. 4. pp. 133â&#x20AC;&#x201C;137.

IMRAN, S.A., DIETZ, J.D., MUTOTI, G., TAYLOR, J.S., and RANDALL, A.A. 2005a.

Modified Larsons ratio incorporating temperature, water age, and electroneutrality effects on red water release. Canadian Journal of Environmental Engineering, vol. 131, no. 11. pp. 1514â&#x20AC;&#x201C;1520.

IMRAN, S.A., DIETZ, J.D., MUTOTI, G., TAYLOR, J.S., RANDALL, A.A., and COOPER, C.D. (2005b). Red water release in drinking water distribution systems. Journal of the American Water Works Association, vol. 97, no. 9. pp. 93â&#x20AC;&#x201C;100.

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LARSON, T.E. and SKOLD, R.V. 1957. Corrosion and tuberculation of cast iron.

Journal of the American Water Works Association, vol. 49, no. 10. pp. 1294â&#x20AC;&#x201C;1302.

LARSON, T.E. and SKOLD, R.V. 1958. Laboratory studies relating mineral water quality of water to corrosion of steel and cast iron. Corrosion, vol. 14. pp. 285â&#x20AC;&#x201C;288.

LARSON, T.E. and SOLLO Jr., F.W. 1967. Loss in water main carrying capacity.

Journal of the American Water Works Association, vol. 59, no. 12. pp. 1565â&#x20AC;&#x201C;1572.

MERRILL, D.T. and SANKS, R.L. 1978. Corrosion control by deposition of CaCO3 films: Part 3, a practical approach for plant operators. Journal of the American Water Works Association, vol. 70, no. 1. pp. 12â&#x20AC;&#x201C;18.

MILLETTE, J.R., HAMMONDS, A.F., PANSING, F.J., HANSEN, C.E., and CLARK, P.J. 1980.

Aggressive water: assessing the extent of the problem. Journal of the American Water Works Association, vol. 72, no. 5. pp. 262â&#x20AC;&#x201C;266.

ODDO, J.E. and TOMSON, M.B. 1982. Simplified calculation of CaCO3 saturation at high temperatures and pressures in brine solutions. Journal of Petroleum Technology, July. pp. 1583â&#x20AC;&#x201C;1590.

PIRON, D.L., DESJARDINS, R., BRIERE, F., and ISMAEL, M. 1986. Corrosion rate of cast iron and copper pipe by drinking water. Corrosion Monitoring in Industrial Plants Using Nondestructive Testing and Electrochemical Methods, ASTM STP 908. Morgan, G.C. and Labine, P. (eds). American Society for Testing and Materials, Philadelphia.

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PISIGAN, R.A. and SINGLEY, J. E. 1984. Evaluation of the corrosivity using the Langelier Index and relative corrosion rate models. Material Performance, vol. 24, no. 4. pp. 26â&#x20AC;&#x201C;36.

PUCKORIUS, P.R. and BROOKE, J.M. 1991. A new practical index for calcium carbonate scale prediction in cooling tower systems. Corrosion, vol. 47, no.

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75, no. 2. pp. 95â&#x20AC;&#x201C;100.

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115, no. 3. pp. 173â&#x20AC;&#x201C;178.

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http://dx.doi.org/10.17159/2411-9717/2015/v115n12a13

The effect of sodium carbonate on the dispersion behaviour and froth flotation of a nickel ore

by B. Feng*â&#x20AC; , Q.M. Fengâ&#x20AC; , Y.P. Luâ&#x20AC; , and H.H. Wang*

13$.2.

The effect of sodium carbonate on the flotation performance of a nickel ore was studied and the mechanism investigated. The flotation results show that lizardite minerals in the ore interfere with the flotation of pentlandite, and the addition of sodium carbonate improves pentlandite flotation recovery. The pulp pH did not change with increasing sodium carbonate dosage. Drawing on the literature in this area, combined with the sedimentation test results, sieving test results, and infrared spectra study, it is proposed that carbonate ions, derived from sodium carbonate, interact with lizardite slime and change the interparticle force from attraction to repulsion, resulting in the removal of adhering slimes from pentlandite surfaces.

4 30). sodium carbonate, nickel flotation, lizardite, pentlandite.

# $402'41/-(

Nickel deposits can be classified into two main groups: laterites and sulphides. Even though nearly 70% of nickel resources are contained in laterites, the bulk of production comes from sulphides due to the complex and high-cost processing required for laterite. The sulphide ores are universally treated by flotation, and the major gangue components include a host of MgO minerals, such as serpentine.

MgO minerals (e.g. serpentines) break readily. Thus grinding produces fines or slimes, particles less than approximately 10 Âľm. These gangue slimes can interfere with flotation by forming a coating on the pentlandite surfaces (Edwards et al., 1980; Pietrobon et al., 1997; Wellham et al., 1992).

This has two consequences: dilution of the concentrate when pentlandite partially coated with fines remains floatable, and loss of pentlandite when extensively coated pentlandite becomes hydrophilic (Learmont and Iwasaki, 1984; Trahar, 1981). In order to improve the flotation of the pentlandite, sodium hexametaphosphate, sodium silicate, carboxymethyl cellulose (CMC), and other agents are used to disperse slime particles of MgO-type minerals from sulphide surfaces (Bremmell et al., 2005; Kirjavainen and Heiskanen 2007; Lu et al., 2011). Adsorption of these reagents on serpentine reverses the

The serpentine lizardite used for the FTIR study was obtained from Donghai, Jiangsu Province, China. The mineral composition of the lizardite as determined by XRD was: lizardite 98%, chlorite 2%.

The ore sample used in this study is of high nickel grade (1.35% Ni). Approximately 96% of the nickel content is in the form of pentlandite and can be recovered by true flotation. The remaining 4% of nickel is distributed in non-sulphide minerals, and can be recovered only by entrainment or as composites with pentlandite. The ore contains 37% w/w MgO, distributed mainly in lizardite (46% w/w) and olivine (19% w/w), as determined by X-ray diffraction.

* Jiangxi Key Laboratory of Mining Engineering,Jiangxi University of Science and Technology, Ganzhou, China. â&#x20AC; School of Mineral Processing and Bioengineering, Central South University, Changsha, China. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received Apr. 2015 and revised paper received July 2015.

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positive surface charge, so attraction forces between pentlandite and serpentine are eliminated (Bremmel et al., 2005).

Sodium carbonate is a reagent that commonly used to modify the pulp pH. However, the carbonate ions will not only change the pH, but can also increase nickel flotation selectivity over MgO minerals (Pietrobon et al., 1997). Sodium carbonate may have an influence on both the mineral surfaces and solution chemical species. The mechanism by which sodium carbonate improves nickel flotation recovery has not been elucidated to date. In this study, the effect of sodium carbonate on the flotation performance of a nickel ore was studied and the mechanism investigated.

The effect of sodium carbonate on the dispersion behaviour and froth flotation of a nickel ore PAX (potassium amyl xanthate) and MIBC (methyl isobutyl carbinol) were used as collector and frother respectively. All the reagents used in this study were of analytical grade.

Ore samples were crushed to -2 mm, riffled into representative samples of 500 g, purged with nitrogen, and frozen during storage. For each flotation experiment, samples were ground in a mild steel rod mill to a P70 of 74 Îźm. Sodium carbonate was added at the grinding stage.

The flotation tests were performed in a XFD-63 flotation cell (self-aeration) with a flotation volume of 1.5 L, using an agitation speed of 2800 r/min. The solid concentration in the ďŹ&#x201A;otation cell was 35% by weight. The pulp pH was maintained at 9 owing to the buffer effect of the minerals within the pulp. During the conditioning, collector (150 g/t) and frother (30 g/t) were added and conditioned for 5 minutes respectively to allow for collector and frother adsorption. After conditioning, ďŹ&#x201A;otation was started with the injection of air into the ďŹ&#x201A;otation cell. The air flow rate was maintained at 0.1 Nm3/h, monitored with a ďŹ&#x201A;ow meter.

Flotation was performed for 15 minutes and five concentrates were collected after cumulative times of 1, 3, 6, 10, and 15 minutes (Feng et al., 2012).

To study the effect of sodium carbonate on the settling behaviour of the pulp, sedimentation tests were performed.

Ore samples were ground to a P70 of 74 Îźm. Sodium carbonate was added at the grinding stage when needed. 100 ml aliquots of ground pulp were transferred to a 100 ml measuring cylinder, and the height of the upper clear layer recorded at fixed times.

The floatability of pentlandite depends on the amount of slimes on its surface. To study the effect of sodium carbonate on the amount of slimes removed from the surfaces of coarse sulphide particles, sieving tests were performed. Pulps were sampled from the flotation cell before and after the addition of sodium carbonate and sieved to remove -75 Îźm particles.

The particle size distribution of the +75 Îźm pulp samples was measured using a Malvern Master Sizer X (using tap water as a carrier for the measurements). The samples were measured after sonication (in a sonication bath attached to the Malvern Master Sizer X) for 4 minutes at the maximum sonication intensity (Chen et al., 1999a, 1999b). Portions of the +75 Îźm samples were treated by sonication and re-sieved at 75 Îźm, and the -75 Îźm particles collected for XRD analysis.

samples of pure lizardite were individually suspended in 200 ml of sodium carbonate solution for 5 minutes. The pulps were then centrifuged and washed at least three times with distilled water and dried in a vacuum oven at 40°C. The infrared spectra were obtained as for the pure lizardite sample.

4.*(/.5-1)5)2.+*..231 The ore contained a large amount of lizardite slimes after grinding. The slimes interfered with the pentlandite flotation by adsorbing onto its surface. In the past, the concentrator used carboxymethyl cellulose to disperse and depress the slime. Sodium carbonate is a reagent that is commonly used to modify the pulp pH, and it can also be used to precipitate metal ions and disperse slime. To further improve the flotation recovery of pentlandite, sodium carbonate was considered as a dispersing agent on the basis of the original reagent regime.

The effect of sodium carbonate on the recovery and grade of the nickel ore is shown in Figure 1, and the effect of flotation time on the recovery with different sodium carbonate dosages is shown in Figure 2. The flotation results indicate that the addition of 5 kg/t sodium carbonate increased the nickel recovery from 82% to 90%, while the Ni grade did not change.

To study the mechanism by which sodium carbonate increased the flotation recovery of pentlandite, the effect of sodium carbonate on the settling behaviour of the nickel ore was investigated. The results (Figure 3) show that the addition of sodium carbonate reduced the settling velocity of the nickel ore, indicating that sodium carbonate has a dispersion effect on the pulp.

The effect of sodium carbonate on surface cleaning of the coarse particlea was investigated by the sieving tests and the results are shown in Figure 4. Pulps were sampled from the flotation cell before and after the addition of sodium carbonate and sieved at 75 Îźm to remove -75 Îźm particles.

Ideally, no particles less than 75 Îźm should remain in the +75 Îźm fraction after sieving, unless those particles are adhering to the +75 Îźm coarse particles through slime coating. Thus, the change of size distribution of the fines (â&#x20AC;&#x201C;75 Îźm fraction) in the +75 Îźm sample after the addition of

In order to study the interaction of carbonate with lizardite, the IR (infrared) spectra of lizardite before and after sodium carbonate treatment were measured using a Nexus 670 series Fourier transform infrared spectrometer in the range 4000â&#x20AC;&#x201C; 350 cmâ&#x2C6;&#x2019;1. For the analysis of pure sodium carbonate or lizardite, a 20 mg sample was added to 200 mg KBr, for a concentration of approximately 10 wt%. To test the infrared spectra of lizardite treated with sodium carbonate, 0.5 g

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sodium carbonate can be used to indicate the change in the amount of slimes on the coarse particle surfaces.

The results show that the amount of slimes removed from the surfaces of the coarse particles increased with increasing sodium carbonate dosage, and the coarse particle surfaces were free of particles less than 4 Îźm in size when 5 kg/t sodium carbonate was used. This shows that sodium carbonate is effective in assisting the removal of adhering slime particles from pentlandite surfaces.

The mineral composition of the slimes removed from large particles was investigated using XRD analysis. The results (Figure 5) suggest that the slimes attached to the surfaces of large particles were mainly lizardite, chlorite, and talc. The magnesium silicate gangue minerals are soft and more easily broken than the sulphide minerals in the grinding and conditioning processes. Thus the slimes consisted mainly of magnesium silicate gangue minerals.

The pH of the pulp after the addition of sodium carbonate is shown in Figure 6. The pulp pH remained essentially constant with the increase of sodium carbonate concentration. This result shows that sodium carbonate does not play a role in modifying the pulp pH. The pH regulators are divided in two main groups: reagents that produce hydroxyl (OH-) by dissociation and

reagents which form OH- by hydrolysis. Sodium carbonate belongs to the latter group. Equations [1]-[3] show hydrolysis of carbonate. The ore contains 46% lizardite (w/w), which will consume carbonate; thus, there will not be sufficient carbonate ions left in the pulp to alter the pH.

In a previous study, it was demonstrated that sodium carbonate can effectively disperse lizardite and pyrite, improving the flotation performance of pyrite, which is depressed by lizardite (Feng and Luo, 2013). In order to study how the carbonate interacted with the lizardite surface, the IR (infrared) spectra were measured, and the results are shown in Figure 7. The IR spectrum of lizardite shows a peak at 3686.3 cm-1 due to external Mg-OH stretching vibration, and the adsorption band of 984.6 cm-1 is assigned to stretching vibration of Si-O. The peaks at 580 cmâ&#x2C6;&#x2019;1 and 443.6 cmâ&#x2C6;&#x2019;1 corresponding to deformation of the Mg-OH bond and shear vibration of Mg-OH, respectively. The IR spectrum of sodium carbonate has a strong adsorption peak at 1441.5 cmâ&#x2C6;&#x2019;1, and

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[1]

CO32-+H2O HCO3-+OH-

[2]

HCO3-+H2O H2CO3+OH-

[3]

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The effect of sodium carbonate on the dispersion behaviour and froth flotation of a nickel ore

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there also exists a peak at 1621.1 cmâ&#x2C6;&#x2019;1, both of which are attributed to the C-O asymmetric stretching vibration results.

After treatment with sodium carbonate, a new adsorption peak of 1423.8 cmâ&#x2C6;&#x2019;1 appeared in the infrared spectrum of lizardite, which is the result of carbonate adsorbed on the surface of lizardite.

The particles finer than 5 Îźm in diameter are generally described as â&#x20AC;&#x2DC;slimesâ&#x20AC;&#x2122;. The detrimental effect of slimes on flotation is encountered in many mineral systems. One of the reasons is related to their coating on valuable mineral particles.

The dominant component in this nickel ore is lizardite, which is soft and easily broken during the grinding process to form slimes.

Surface charge is an important factor in controlling particleparticle interactions. The formation of slime coatings is directly related to the surface potentials of the sulphide minerals and lizardite particles. The lizardite has a positive potential at the pH range in which the flotation of nickel sulphide ore is performed; it is therefore likely that it will attach through electrostatic attraction to the negatively charged sulphide surface and form slime coatings. A coating of hydrophilic lizardite slimes will decrease the hydrophobicity of the sulphide particle and result in lower sulphide mineral recovery.

The sodium carbonate can interact with lizardite and change the surface charge to a negative value. The repulsive forces due to like charges are greater than the attractive van der Waals forces and some slimes are removed from the sulohide surface. The amount of slime removed is related to the dosage of sodium carbonate.

+ 13 (4)&4'41/.

KIRJAVAINEN, V. and HEISKANEN, K. 2007. Some factors that affect beneficiation of sulphide nickelâ&#x20AC;&#x201C;copper ores. Minerals Engineering, vol. 20, no. 7. pp. 629â&#x20AC;&#x201C;633.

31+(*.231.

LEARMONT, M.E. and IWASAKI, I. 1984. Effect of grinding media on galena flotation. Mineral and Metallurgical Processing, vol. 1. pp. 136â&#x20AC;&#x201C;143.

The valuable mineral of the nickel ore is pentlandite and the main gangue mineral is lizardite. The lizardite breaks readily during the grinding process and produces slimes, which are positively charged at the pH where flotation of nickel sulphide ore is performed. Thus the slime will adsorb onto the negatively charged pentlandite surface through electrostatic attraction and depress pentlandite flotation. Sodium carbonate interacts with slime particles and removes adhering slimes from pentlandite surfaces. The coarse particle surfaces were free of particles less than 4 Îźm in size at a sodium carbonate addition of 5 kg/t. This work has shown that carbonate can improve pentlandite flotation performance.

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The authors acknowledge the support of the National Natural Science Foundation of China (Nos.51404109), and the National Basic Research Program of China (Nos. 2014CB643400).

4,4041+4.

BREMMELL, K.E., FORNASIERO, D., and RALSTON, J. 2005. Pentlanditeâ&#x20AC;&#x201C;lizardite interactions and implications for their separation by flotation. Colloids and Surfaces A â&#x20AC;&#x201C; Physicochemical and Engineering Aspects, vol. 252, no. 2/3. pp. 207â&#x20AC;&#x201C;212.

CHEN, G., GRANO, S., SOBIERAJ, S., and RALSTON, J. 1999a. The effect of high intensity conditioning on the flotation of a nickel ore, Part 1: Size by size analysis. Minerals Engineering, vol. 12, no. 10. pp. 1185â&#x20AC;&#x201C;1200.

CHEN, G., GRANO, S., SOBIERAJ, S., and RALSTON, J. 1999b. The effect of high intensity conditioning on the flotation of a nickel, part 2: Mechanisms.

Minerals Engineering, vol. 12, no. 11. pp. 1359â&#x20AC;&#x201C;1373.

EDWARDS, G.R., KIPKIE, W.B., and AGAR, G.E. 1980. The effect of slime coatings of the serpentine minerals, chrysotile and lizardite on pentlandite flotation. International Journal of Mineral Processing, vol. 7, no. 1. pp. 33â&#x20AC;&#x201C;42.

FENG, B. and LUO, X. 2013. The solution chemistry of carbonate and implications for pyrite flotation. Minerals Engineering, vol. 53. pp. 181â&#x20AC;&#x201C;183.

FENG, B., FENG, Q., LU, Y., and LV, P. 2012. The effect of conditioning methods and chain length of xanthate on the flotation of a nickel ore. Minerals Engineering, vol. 39. pp. 48â&#x20AC;&#x201C;50.

LU, Y.P., ZHANG, M.Q., FENG, Q.M., LONG, T., OU, L.M., and ZHANG, G.F. 2011.

Effect of sodium hexametaphosphate on separation of serpentine from pyrite. Transactions of the Nonferrous Metals Society of China, vol. 21. pp. 208â&#x20AC;&#x201C;213.

PIETROBON, M.C., GRANO, S.R., SOBIERAJ, S., and RALSTON, J. 1997. Recovery mechanisms for pentlandite and MgO-bearing gangue minerals in nickel ores from Western Australia. Minerals Engineering, vol. 10, no. 8. pp. 775â&#x20AC;&#x201C;786.

TRAHAR, W.J. 1981. A rational interpretation of the role of particle size in flotation. International Journal of Mineral Processing, vol. 8. pp. 289â&#x20AC;&#x201C;327.

WELLHAM, E.J., ELBER, L., and YAN, D.S. 1992. The role of carboxy methyl cellulose in the flotation of a nickel sulphide transition ore. Minerals Engineering, vol. 5. pp. 381â&#x20AC;&#x201C;395. â&#x2014;&#x2020;

http://dx.doi.org/10.17159/2411-9717/2015/v115n12a14

The influence of water quality on the flotation performance of complex sulphide ores: case study at Hajar Mine, Morocco

by K. Boujounoui*, A. Abidiâ&#x20AC; , A. Bacaoui*, K.El Amariâ&#x20AC;Ą, and A. Yaacoubi*

-CB9EDE

G-!BA=E flotation, process water chemistry, complex sulphide ore, screening design.

CFAB=:>FDBC Mineral processing can be considered as one of the most intensive water-consuming processes. To reduce fresh water consumption, numerous research works have focused on the use of recycled process water. However, in flotation, recycling water can have adverse effects on the mineral separation. The content of organic reagents (frothers, collectors, depressants) as well as inorganic constituents (suspended matter, base metals, calcium, magnesium, sodium, sulphite, sulphate etc.)

(Leavay et al., 2001; Johnson, 2003; Slatter et al., 2009) builds up and consequently affects the flotation performance (Lui et al., 1993; Leavay et al., 2001; Seke et al.,2006; Kelebek and Nanthakumar, 2007; Haran et al., 2008; BĹçak et al., 2012; Ikumapayi et al., 2012).

Generally, the hydrolyzed metallic ions in the alkaline recycled water form a hydrophilic precipitate (metal hydroxides, sulphates, or carbonates) on the mineral surfaces, resulting in the formation of a hydrophilic barrier that prevents adsorption of the collector (Senior

and Trahar, 1991; Fornasiero and Ralston, 2006).

Cu2+ in copper sulphate form is known as a sphalerite activator, and Zn recovery by flotation is enhanced by increasing concentrations of Cu2+ ions in synthetic water (BĹçak et al., 2012). Cu2+ can also enhance the recovery of galena, chalcopyrite, and pyrite (Coetzer et al., 2003). However, the effect of increasing copper concentration on flotation is not evident above pH 12 and below pH 5, where Cu(OH)3- and Cu2+ are respectively the stable copper species (Fornasiero and Ralston, 2006).

The hydrophobicity of the sphalerite surface is controlled by the Zn(OH)2 formed (Prestidge et al., 1997; Fornasiero and Raston, 2006). For sphalerite in alkaline media, the surface Cu(OH)2 directly interacts with the xanthate (Leppinen,1990).

Cyanide ions used as depressant in a polymetallic ore can produce cupric ions by reaction with copper minerals and cause inadvertent activation of sphalerite. The activation process is enhanced at higher pH values (Seke et al., 2006; Rao et al., 2011).

The presence of Zn2+ in recycled water strongly depresses the recovery of sphalerite, and slightly depresses chalcopyrite and pyrite, but favours the recovery of galena (Coetzer et al., 2003). The use of zinc sulphate at alkaline pH decreases the recovery of galena due to coating by hydrophilic Zn(OH)2 (Trahar et al., 1997; Seke, 2005).

* Faculty of Sciences Semlalia, department of chemistry, BP 2390 Marrakech, Morocco. â&#x20AC; Mining Institute of Marrakech (IMM), B.P. 2402, Marrakech, Morocco. â&#x20AC;Ą Laboratoire GĂŠoressources, UnitĂŠ associĂŠe au CNRST (URAC 42), FacultĂŠ des Sciences et Techniques Marrakech,. Marrakech, Morocco. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received Mar. 2015 and revised paper received July 2015. $(.%2'H880

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As part of the process optimization project of CMG (Mining Company of Guemassa-Marrakech, Morocco), a preliminary study on the effect of water quality on the flotation of galena, sphalerite, chalcopyrite, and pyrrhotite was carried out using asymmetrical fractional factorial design.

The multivariable analysis showed that of ten studied factors, six (Cu2+, Zn2+, Mg2+, Ca2+, SO42-, and PAX) have a significant influence on the flotation of these sulphide minerals. Graphical analysis showed that high concentrations of Cu2+ (7â&#x20AC;&#x201C;14 mg/L) in synthetic process water increased the recovery of galena, chalcopyrite, sphalerite, and pyrrhotite. At low Cu2+ concentrations (0â&#x20AC;&#x201C;7 mg/L), sphalerite was depressed. Zn2+ at low concentrations (0â&#x20AC;&#x201C;20 mg/L) decreased the recovery of all studied minerals.

However, at high concentrations (20â&#x20AC;&#x201C;40 mg/L), an increase in chalcopyrite, sphalerite, and pyrrhotite recoveries was observed. Mg2+ (100â&#x20AC;&#x201C;200 mg/L) decreased the recovery of galena, chalcopyrite, and sphalerite. Ca2+ (1200â&#x20AC;&#x201C;2000 mg /L) depressed sphalerite flotation.

Sulphate ions (SO42-) enhanced recovery of all the studied minerals.

Potassium amyl xanthate (PAX) promoted sphalerite recovery at high concentrations (10â&#x20AC;&#x201C;20 mg/L).

The influence of water quality on the flotation performance of complex sulphide ores Ca2+ and Mg2+ are the most cited cations in the literature as precipitated species with a negative effect on mineral recoveries. Sphalerite recovery is significantly reduced in the presence of these ions; the decrease is more pronounced for Mg at pH 9 than for Ca at pH 12. This is due to the formation of the metal hydroxides on mineral surfaces (Lascelles et al., 2003). The adsorption of calcium and other metal ions in during flotation leads to the reduction of negative surface charges and consequently inhibits the adsorption of xanthate on the mineral surfaces (Ikumapayi et al., 2012).

Generally, the presence of SO42- in process water containing numerous species, including SO32- and Ca2+, in addition to dissolved iron, could form hydrophilic layers on the surface mineral (CaSO42- or CaSO32-) (Ikumapayi et al., 2012). Furthermore, a high concentration of SO42- ions has the same depressing effect by competing with collector molecules for adsorption on mineral surfaces (Wu et al., 2002; Lefèvre and FÊdoroff, 2006).

In Morocco, the semi-arid to arid climate makes water a limited and precious resource. According to data from the Haouz Tensift Basin Agency (HTBA), the Marrakech region of Morocco is characterized by low and irregular rainfall (250 mm/a) with a high evaporation rate (2500 mm/a). The Mining Company of Guemassa (CMG), located 30 km southwest of Marrakech, is affected by this issue of water shortage.

CMG uses a selective flotation flow sheet to produce a galena concentrate (with Aerophine A3418 using NaCN at pH of 11.3), then a chalcopyrite concentrate (with Aerophine A3418 at pH of 8.9), and finally a sphalerite concentrate (with potassium amyl xanthate; PAX, at pH of 12-12.5) from a complex polymetallic sulphide ore.

To reduce the consumption of fresh water and to test the possibility of using a single process water in the overall CMG flotation process, this study focused on the effect of simulated process water quality on the recovery of Pb, Cu, and Zn during the galena flotation step. The study considered the effect of various ions in the water, as well as the particle size of the feed. The goal was to achieve a better recovery and selectivity of galena over sphalerite, chalcopyrite, and pyrrhotite. The results will assist in the flotation optimization exercise by identifying the most important factors influencing galena recovery and the interactions between them.

In this study, flotation tests were carried out on a complex sulphide ore provided by CMG. The results were

subjected to statistical analysis to assess the relative significance of the main factors affecting flotation performance as evaluated from the experimental results. The statistical design of the experiments allows a full study of the effects of all parameters on a given process and their optimization, providing maximum information from a minimum of experiments by implementing a simple mathematical model to represent the studied phenomenon (Box et al., 1978; Akhanazarova and Kafarov, 1982; Obeng et al., 2005; Napier-Munn, 2012; Ennaciri et al., 2014).

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To study the effect of water quality on the flotation of zinc, lead, and copper, the focus was on the parameters listed below and presented in Table I. These variables, with their respective ranges of values, were chosen on the basis of data from the literature and preliminary experiments. â&#x17E;¤ Water quality. Process water was synthesized from Marrakech drinking water. Cations and anions were added to simulate the composition of recycled water in the CMG zinc process. These ions are: Cu2+, Fe2+, Zn2+, Pb2+, Ca2+, Mg2+, SO42-, and PAX â&#x20AC;˘ Marrakech drinking water was used during grinding.

Once the pulp was introduced into the flotation cell, the desired synthesized water quality was adjusted by adding the salts of the relevant ions â&#x20AC;˘ The grinding step was also performed using synthesized water directly â&#x17E;¤ Particle size â&#x20AC;&#x201C; to distinguish the effect due to water quality and mineralogical mixing.

Screening of these ten studied parameters reduced the number tests required to 27 (Table I and II) and enabled the factors influencing the investigated responses: galena, chalcopyrite, sphalerite and pyrrhotite recoveries to be identified.

Flotation tests were carried out on a representative sample of complex sulphide ore composed of 6.43% sphalerite (Sp: ZnS), 2.22% galena (Gl: PbS), 0.95% chalcopyrite (Cp: CuFeS2), 41.57% pyrrhotite (Po: Fe9S10), and 48.82% gangue (Gg) consisting mainly of silica, carbonates, and chlorides.

Table I

Parameter limits for the flotation tests on water quality effect on Ga, Cp, Sp, and Po recoveries Coded variables

Natural variables

X1

A

X2 X3 X4 X5 X6 X7 X8 X9 X10

B C D E F G H I J

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Level of addition of synthesized water Cu2+, mg/L Fe2+, mg/L Zn2+, mg/L Pb2+, mg/L Ca2+, mg/L Mg2+, mg/L SO2-4, mg/L PAX, mg/L d80, Îźm

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Levels 2

3

In grinding

In flotation

--

0 0 0 0 400 0 200 0 200

7 350 20 0.25 1200 100 1500 10 100

14 700 40 2.5 2000 200 6000 20 80

The influence of water quality on the flotation performance of complex sulphide ores

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GR GR GR GR GR GR GR GR GR FL FL FL FL FL FL FL FL FL GR GR GR GR GR GR GR GR GR

0 0 0 7 7 7 14 14 14 0 0 0 7 7 7 14 14 14 0 0 0 7 7 7 14 14 14

0 0 0 350 350 350 700 700 700 350 350 350 700 700 700 0 0 0 700 700 700 0 0 0 350 350 350

0 0 0 20 20 20 40 40 40 40 40 40 0 0 0 20 20 20 20 20 20 40 40 40 0 0 0

0 0.25 2.5 0 0.25 2.5 0 0.25 2.5 0 0.25 2.5 0 0.25 2.5 0 0.25 2.5 0 0.25 2.5 0 0.25 2.5 0 0.25 2.5

0 100 200 0 100 200 0 100 200 200 0 100 200 0 100 200 0 100 100 200 0 100 200 0 100 200 0

200 1500 6000 1500 6000 200 6000 200 1500 200 1500 6000 1500 6000 200 6000 200 1500 200 1500 6000 1500 6000 200 6000 200 1500

0 10 20 10 20 0 20 0 10 10 20 0 20 0 10 0 10 20 20 0 10 0 10 20 10 20 0

200 100 80 100 80 200 80 200 100 80 200 100 200 100 80 100 80 200 100 80 200 80 200 100 200 100 80

47.13 69.10 70.40 52.81 64.02 47.88 75.90 51.52 54.42 56.73 53.18 71.39 55.23 66.83 58.83 57.50 49.87 57.94 43.61 38.54 55.40 61.93 32.62 51.71 55.49 62.59 50.29

50.37 70.05 70.93 47.65 64.57 48.26 77.59 53.14 56.51 55.65 55.36 73.10 54.48 63.51 58.35 57.58 36.31 57.31 45.48 41.61 56.32 61.72 44.92 56.39 63.22 61.67 56.10

23.15 41.29 42.95 22.66 42.30 19.76 51.54 43.27 31.83 30.36 26.52 38.66 22.36 26.23 30.54 26.60 22.62 28.48 21.11 24.05 24.32 28.98 21.02 31.12 27.18 30.91 27.08

400 1200 2000 400 1200 2000 400 1200 2000 1200 2000 400 1200 2000 400 1200 2000 400 2000 400 1200 2000 400 1200 2000 400 1200

35.93 56.08 53.32 33.17 53.53 33.23 66.12 43.27 42.37 39.64 42.67 54.95 33.58 39.55 44.38 41.84 28.29 43.14 32.81 32.18 37.91 43.29 38.20 50.60 48.36 49.67 42.33

FL: water addition in flotation step; GR: water addition during grinding step; WAL: water addition level

/D6:AGH8H H A?DCHED GH=DEFAD*:FDBCH>:A GEHB@H+2 H>B39<G HE:<9;D=GHBAG

Flotation tests were carried out in a Denver flotation cell of 1.5 litre capacity. Solid concentration was about 27% by weight, using synthetic water at the required quality.

The natural pH was about 7. NaOH was used as pH regulator for all tests to pH=11.3. Sodium cyanide (NaCN) was used as a depressing reagent for Sp, Cp, and Po for all tests at a specific addition of 350 g/t. Diisobutyl phosphinate (Aerophine 3418A) (40 g/t) and methyl isobutyl carbinol (MIBC) (40 g/t) were used as galena collector and frother respectively. The impeller rotation speed was a constant 700 r/min. The level of the pulp was constantly adjusted by the addition of synthetic water at the required quality. The flotation time was 10 minutes for each test, and the concentrate was recovered by manual scraping every 30 seconds. All concentrates and tails were filtered, dried, and weighed, and then analysed by atomic adsorption spectroscopy (AAS) for Cu, Pb, Zn, and Fe. Metal recoveries to the concentrates were calculated according to the following equation:

where R is the metal recovery; tc the concentrate metal grade; tf the feed metal grade; C the concentrate weight, and A the feed weight.

Waters used for the tests were synthesized by using various salts: CaCl2 (97%), ZnSO4.7H2O (98%), and $(.%2'H880

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A sample of 120 kg was taken from the feed belt of the primary ball mill of the CMG flotation plant and crushed down to 2 mm using roll crushers in the laboratory of the Institute of Mines in Marrakech. The crushed sample was sieved at 2 mm and the undersize split using a riffle divider into 500 g batch samples for the flotation experiments. The batch samples were stored in vacuum sealed bags to prevent oxidation of the sulphide minerals.

Prior to the flotation tests, samples of 500 g were milled in 250 ml of synthetic water using a Denver carbon steel ball mill of 9.5 litres internal volume. The size fractions studied in this work were d80 = 200 Îźm, 100 Îźm, and 80 Îźm (Figure 1).

The influence of water quality on the flotation performance of complex sulphide ores FeCl2.6H2O (97%) from Prolabo; Na2SO4 (99%) and PbCl2 (98%) from Fluka; Cu(NO3)2.3H2O (99.5%) from Merck; and Mg(NO3)2.6H2O (99-102%) from Panreac. Flotation reagents (Aerophine 3418A, PAX, and MIBC) were provided by CMG. The effect of water addition was also studied. Water can be introduced at the grinding or at the flotation stage. Table II summarizes the designed experiments and operating conditions.

To assess the effect of each factor on the flotation of Pb, Cu, Zn, and Fe during the lead flotation step, the operating conditions of the tests were established according to an asymmetrical fractional factorial matrix. These kinds of multivariate experimental designs are powerful tools for the optimization of such procedures. Compared to traditional univariate approaches, based on the study of the effect of one variable at a time on the selected response, multivariate techniques allow the simultaneous evaluation of several factors with a minimum number of experiments.

Furthermore, they provide additional data about the system, with the estimation of interactions between the influencing factors.

The screening experiment for several factors enables estimation of K factors in N experiments (K=10 and N= 27 in our case) with a variance of Ď&#x192;²/27. The model applied in this

study is a polynomial empirical model of the first degree, which contains only the terms (bi) that will reflect the effect of each of the ten factors on the four responses: recovery of galena (R-Pb), of chalcopyrite (R-Cu), of sphalerite (R-Zn), and of pyrrhotite (R-Fe).

The model can be written as: Y = b0 + b1A*(X1A) + b2A*(X2A) + b2B*(X2B) + b3A*(X3A) + b3B*(X3B) + b4A*(X4A) + b4B*(X4B) + b5A*(X5A) + b5B*(X5B) + b6A*(X6A) + b6B*(X6B) + b7A*(X7A) + b7B*(X7B) + b8A*(X8A) + b8B*(X8B) + b9A*(X9A) + b9B*(X9B) + b10A*(X10A) + b10B*(X10B) where Y: the studied response, which could be the recovery of lead (R-Pb), Y1: of copper (R-Cu), Y2: of zinc (R-Zn), Y3; or of iron (R-Fe), Y4 Xi: the investigated factor (i varies from 1 to 10) A: the domain delimited by levels 1 and 2 of the factor Xi B: the domain delimited by levels 2 and 3 of the factor Xi biA: Xi effect in the domain A biB: Xi effect in the domain B. Tables I and II describe the approach of this study. The design matrix (fractional factorial), generated by the screening design resulted in the development of a series of 27 flotation tests (Table II). The experimental sequence was

/?>FBAEHDC@<:GC>DC6H *7H+:7H C7H?C=H/GHAG>B GADGEH?C=HF;GDAHG 9GAD3GCF?<H=B3?DCE 1G9BCEGE

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Y1 (R-Pb)

B2-3 : Cu2+ 7 - 14 D1-3 : Zn2+ 0 - 40 D1-2 : Zn2+ 0 - 20 G1-3 : Mg2+ 0 - 200 G2-3 : Mg2+ 100 - 200 H1-3 : SO42200 - 6000 H1-2 : SO42200 - 1500 J1-3 :d80,Îźm 200 - 80 B2-3 : Cu2+ 7 - 14 Y2 (R-Cu) D1-2 : Zn2+ 0 - 20 D2-3 : Zn2+ 20 - 40 G2-3 : Mg2+ 100 - 200 H1-3 : SO42200 - 6000 H1-2 : SO42200 - 1500 J1-3 : d80, Îźm 200 - 80 Y3 (R-Zn) B1-2 : Cu2+ 0-7 B2-3 : Cu2+ 7 - 14 D1-2 : Zn2+ 0 - 20 D2-3 : Zn2+ 20 - 40 F2-3 : Ca2+ 1200 - 2000 G2-3 : Mg2+ 100 - 200 H1-3 : SO42+ 200 - 6000 H1-2 : SO42+ 200 - 1500 I2-3 : PAX 10 - 20 J1-3 : d80 ,Îźm 200 - 80 J1-2 : d80 ,Îźm 200 - 100 Y4 (R-Fe) B2-3 : Cu2+ 7 - 14 D1-2 : Zn2+ 0 - 20 D2-3 : Zn2+ 20 - 40 H1-3 : SO42200 - 6000 J1-3 : d80, Îźm 200 - 80 J1-2 : d80, Îźm 200 - 100 ** Statistically significant at the 99% level (p-value < 0.01) * Statistically significant at the 95% level (p-value < 0.05)

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-13.076 11.227 18.039 10.397 11.673 -14.091 -9.992 -12.090 -9.117 17.340 -11.211 10.001 -15.644 -9.397 -8.420 4.499 -8.661 12.132 -12.171 8.553 8.923 -11.166 -5.898 -6.338 -9.876 -7.698 -7.443 9.241 -8.346 -10393 -14.297 -8.881

2.954 2.954 2.954 2.842 2.842 2.842 2.842 2.954 2.465 2.465 2.321 2.372 2.372 2.372 2.465 1.612 1.652 1.652 1.612 1.652 1.612 1.612 1.652 1.538 1.652 1.612 2.560 2.463 2.463 2.560 2.560 2.560

-4.43 3.80 6.11 3.66 4.11 -4.96 -3.52 -4.09 -3.70 7.04 -4.83 4.22 -6.60 -3.96 -3.42 2.79 -5.24 7.34 -7.55 5.18 5.53 -6.93 -3.57 -4.12 -5.98 -4.77 -2.91 3.75 -3.39 -4.06 -5.59 -3.47

1.27 * 2.02 * 0.479** 2.27 * 1.60 * 0.899 ** 2.55 * 1.61 * 2.19 * 0.317 ** 0.972 ** 1.47 * 0.382 ** 1.78 * 2.78 * 3.82 * 0.392 ** 0.111 ** 0.100 ** 0.411 ** 0.318 ** 0.137 ** 1.65 * 0.972 ** 0.238 ** 0.559 ** 4.42 * 2.10 * 2.85 * 1.65 * 0.626 ** 2.66

The influence of water quality on the flotation performance of complex sulphide ores randomized in order to minimize the effects of the uncontrolled factors. The results were analysed using Nemrodw Software (New Efficient Methodology for Research using Optimal Design from LPRAI, Marseille, France) (Mathieu et al., 2000). The interpretation of the coefficients and the main effects of factors (bi), was performed from statistical tests on the coefficients using Studentâ&#x20AC;&#x2122;s test (t /2,d).

1GE:<FEH?C=H=DE>:EEDBC The results of the flotation tests conducted according to the experiments in Table II are presented in Figures 2â&#x20AC;&#x201C;5 and Tables II and III. The standard errors calculated for the responses (R-Pb), (R-Cu), (R-Zn), and (R-Fe) were 3.215, 4.10, 2.240, and 3.338 respectively.

Table II shows that despite the flotation conditions (reagents, depressant, pH etc.) being favourable for good lead recovery and selectivity over Cu, Zn, and Fe, the flotation responses are affected by the quality of the process water.

Lead recovery seems to be inversely related to the flotation recoveries of the other elements. This could be due to the composition of the process water, where dissolved species could depress galena and/or activate the other mineral phases. Their effects could be assessed from Figures 2â&#x20AC;&#x201C;5, which are useful for identifying the statistically significant factors at level 99% (p-value < 0.01) and 95% (p-value < 0.05) (Table III). The limits of significance are represented by dashed lines in Figures 2aâ&#x20AC;&#x201C;5a, which depict the differences in the weight of the different levels for each response. Nonsignificant effects are those located between the two limits of significance.

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The influence of water quality on the flotation performance of complex sulphide ores From these figures, the more important factors influencing Pb, Cu, Zn, and Fe recoveries during the lead flotation step were derived and are presented in Table III. The effect of Cu2+ is clear on the responses of R-Pb, R-Cp, R-Sp, and R-Po. Increasing the Cu2+ concentration from 7 to 14 mg/L (B2 to B3) has a positive effect on the recovery of all studied minerals. It also affects the selectivity for galena over chalcopyrite, sphalerite, and pyrrhotite. This selectivity could be enhanced at 0â&#x20AC;&#x201C;7 mg/L Cu2+ (B1 to B2), where a negative effect on the sphalerite recovery was observed.

The positive influence of high concentrations of Cu2+ on the recoveries of Ga, Sp, and Po could be due to the adsorption of Cu2+, Cu(OH)2, and Cu(OH)3- on the surfaces of these minerals (Prestidge et al., 1997; Fornasiero and Ralston, 2006; Chandra and Gerson, 2009). Low concentrations of Cu2+ depress only the recovery of sphalerite. This depressing effect might be due to weak absorption of copper

onto the sphalerite surface due to competition with Cu2+ for adsorption sites (Deng et al., 2013). Moreover, the cyanide ions could cause inadvertent activation of sphalerite by cupric ions produced by the action of cyanide on copper minerals (Seke and Pistorius, 2006; Rao et al., 2011).

Zinc ions at concentrations from 0 to 40 mg/L (D1 to D3) have a negative effect only on the recovery of galena, but this negative effect is very pronounced from 0 to 20 mg/L (D1 to D2) on the recoveries of galena, chalcopyrite, sphalerite, and pyrrhotite. However, at Zn2+ concentrations from 20 to 40 mg/L (D2 to D3), the effect becomes positive except for galena. Both recovery and selectivity of galena over the other minerals are poor at zinc concentrations up to 40 mg/L. The positive effect of Zn2+ could be due to the formation of hydrophobic precipitated species on the mineral surfaces (Znnâ&#x20AC;&#x201C;xCux.xZn(OH)2(surface), for example). Generally, Zn2+ ions (as zinc sulphate) in alkaline conditions are used to

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The influence of water quality on the flotation performance of complex sulphide ores depress sphalerite to increase lead/zinc selectivity.

High concentrations of Ca2+ in the synthesized water (1200â&#x20AC;&#x201C;2000 mg/L) (F2 to F3) depress sphalerite and have no notable depressant effect on the other minerals, especially galena. The presence of Ca2+ might be considered beneficial within the lead circuit.

Mg2+ at high concentrations (100â&#x20AC;&#x201C;200 mg/L) (G2 to G3) has a very important negative effect on galena, chalcopyrite, and sphalerite recoveries, but no effect on pyrrhotite. The Mg2+ concentration in water process in the lead circuit must therefore be controlled.

The depressive effect of Ca2+ and Mg2+ could be due to the formation of hydrophilic layers such as CaCO3 on the mineral surfaces in alkaline conditions, which prevents the adsorption of the collector onto mineral surfaces (Lascelles et al., 2003; Deng et al., 2013; Ikumapayi et al., 2012).

Sulphate ions (SO42-) from 200 to 6000 mg/L (H1 to H3)

have a significant positive effect on the recovery of all studied minerals, consequently affecting the lead selectivity.

This positive effect is weak from 200 to 1500 mg/L SO42- (H1 to H2) on the recoveries of galena, chalcopyrite, and sphalerite.

The positive effect of sulphate on recoveries could be due to the formation of heavy metal sulphite salts, which are slightly soluble in water (e.g. PbSO4, Ks = 1.8*10-8 at 25°C in pure water), on the mineral surfaces.

High concentrations of PAX (1020 mg/L) in synthesized water (I1 to I2) promote sphalerite recovery. The positive effect of PAX is due to the formation of Cu(I)-xanthate and adsorption of dixanthogen (when Cu2+ concentration is low) on the surface of the sphalerite (Leppinen, 1990; Popov and Vucinc, 1990). Xanthates are widely used in sulphide mineral flotation, especially in the selective flotation of sphalerite (Finkelstein, 1997).

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The influence of water quality on the flotation performance of complex sulphide ores The particle size (d80 from 200 to 80 Îźm) (J1 to J3) has a positive effect on the recovery of all studied minerals. These effects are more pronounced between 200 to 100 Îźm (J1 to J2). Decreasing the particle size promotes the recovery of all studied minerals and affects the lead selectivity over Cu, Fe and Zn, due to the fact that the smaller the particle size, the greater the probability of adhesion to the air bubbles (Jowett et al., 1980), and the less the probability of detachment (Holtham et al., 1991).

+BC><:EDBCE Batch-scale flotation tests were performed on a complex PbCu-Zn-Fe sulphide ore to investigate the influence of recycled water quality on the flotation of galena, chalcopyrite, and sphalerite during the lead flotation step. Screening

experiments were conducted to study the effects of ten factors (Cu2+, Fe2+, Zn2+, Pb2+, Ca2+, Mg2+, SO42-, and PAX concentration, grain size, and water addition) on Pb, Cu, Zn, and Fe recoveries. The results showed that the influence of process water on lead flotation depends on its composition and concentrations of constituents. â&#x17E;¤ The addition level of recycled water (during the grinding or at the start of flotation) has no significant effect on the flotation of the studied minerals â&#x17E;¤ A small particle size enhances the recoveries of all the minerals studied â&#x17E;¤ Sulphate ions (SO42-) also have a positive effect on recoveries, but the domains of influence varies from one mineral to another â&#x17E;¤ High concentrations Cu2+ increase the recovery of the

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The influence of water quality on the flotation performance of complex sulphide ores all studied minerals. Cu2+ has a depressing effect of sphalerite at low concentrations â&#x17E;¤ Zn2+ at low concentrations has a depressant effect on the recovery of all the mineral phases, but at high concentrations improves the recovery of chalcopyrite, sphalerite, and pyrrhotite â&#x17E;¤ Mg2+ depresses galena, chalcopyrite, and sphalerite at the high concentrations â&#x17E;¤ Ca2+ has a depressant effect on sphalerite at concentrations â&#x17E;¤ Potassium amyl xanthate at high concentrations enhances sphalerite recovery.

These factors, with their ranges of influence, will be the subject of further investigations to determine the nature of the interactions between them and their effects on recoveries.

An optimization study will be carried out to determine the parameters that have the greatest influence on recoveries.

> CB!<G=6G3GCFE The authors thank the Mining Company of Guemassa for providing the sulphide ore sample and the flotation reagents, and Reminex Society for the chemical analyses.

1G@GAGC>GE

JOWETT, A. 1980. Formation and disruption of particle-bubble aggregates in flotation. Fine Particles Processing. Somasundaran, O. (ed.). American Institute of Mining, Metallurgical and Petroleum Engineers. pp. 721â&#x20AC;&#x201C;751.

KELEBEK, S. and NANTHAKUMAR, B.2007. Characterization of stockpile oxidation of pentlandite and pyrrhotite through kinetic analysis of their flotation.

International Journal of Mineral Processing, vol. 84. pp. 69â&#x20AC;&#x201C;80.

LASCELLES, D., FINCH, J.A., and SUI, C. 2003. Depressant action of Ca and Mg on flotation of Cu activated sphalerite. Canadian Metallurgical Quarterly, vol.

42, no. 2. pp 133-140.

Leavay, G.R.St., Smart, C., and Skinner, W.M., 2001. The impact of water quality on flotation performance. Journal of the South African Institute of Mining and Metallurgy, vol. 101, no. 2. pp. 69â&#x20AC;&#x201C;75.

LEFĂ&#x2C6;VRE, G. and FĂ&#x2030;DOROFF, M. 2006. Sorption of sulfate ions onto hematite studied by attenuated total reflection-infrared spectroscopy: kinetics and competition with other ions. Physics and Chemistry of the Earth, Parts A/B/C, vol. 31, no. 10â&#x20AC;&#x201C;14. pp. 499â&#x20AC;&#x201C;504.

LEPPINEN, J.O. 1990. FTIR and flotation investigation of the adsorption of ethyl xanthate on activated and non-activated sulfide minerals. International Journal of Mineral Processing, vol. 30. pp. 245â&#x20AC;&#x201C;263.

LIU, W., MORAN, C.J., and VINK, S. 2013. A review of the effect of water quality on flotation. Minerals Engineering, vol. 53. pp. 91â&#x20AC;&#x201C;100.

LUI, L., RAO, S.R., and FINCH, J.A. 1993. Laboratory study effect of recycle water on flotation of a Cu/Zn Sulphide ore. Minerals Engineering, vol. 6, no. 11. pp. 1183â&#x20AC;&#x201C;1190.

MATHIEU, D., NONY, J., and PHAN TAN LUU, R. 2000. Software NEMRODW. LPRAI-Marseille, France

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BICAK, O., EKMEKCI, Z., CAN, M., and OZTURK, Y. 2012. The effect of water chemistry on froth stability and surface chemistry of the flotation of a Cuâ&#x20AC;&#x201C; Zn sulfide ore. International Journal of Mineral Processing, vol. 102â&#x20AC;&#x201C;103. pp. 32â&#x20AC;&#x201C;37.

OBENG, D.P., MORRELL, S., and NAPIER-MUNN, T.J. 2005. Application of central composite rotatable design to modelling the effect of some operating variables on the performance of the three-product cyclone. International Journal of Mineral Processing, vol. 76. pp. 181â&#x20AC;&#x201C;192.

BOX, G.E.P., HUNTER, W.G., and HUNTER, J.S. 1978. Statistics for Experiments.

Wiley, New York.

POPOV, S.R., VUCINIC, D.R., and KACANIC, J.V.1989. Floatability and adsorption of ethyl xanthate on sphalerite in an alkaline medium in the presence of dissolved lead ions. International Journal of Mineral Processing, vol. 27. pp. 205â&#x20AC;&#x201C;219.

CHANDRA, A.P. and GERSON, A.R. 2009. A review of the fundamental studies of the copper activation mechanisms for selective flotation of the sulfide minerals, sphalerite and pyrite. Advances in Colloid and Interface Science, vol. 145. pp. 97â&#x20AC;&#x201C;110.

COETZER, G., DU PREEZ, H.S., and BREDENHANN, R. 2003. Influence of water resources and metal ions on galena flotation of Rosh Pinah ore. Journal of the South African Institute of Mining and Metallurgy, vol. 103, no. 3. pp. 193â&#x20AC;&#x201C;207.

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The 2nd School on

Manganese Ferroalloy Production 27–28 June 2016 INTRODUCTION South Africa has the largest, land-based, Mn-ore reserves, exploited by a number of mining companies. Although the country is primarily an exporter of manganese-bearing ores, it has four smelter complexes beneficiating ore by producing high carbon ferromanganese, medium carbon ferromanganese, and silico-manganese. In South Africa, four smelter complexes are operated by Metalloys and Assmang (ferromanganese producers), and Transalloys and Mogale Alloys (silicomanganese producers).

In order to support the smelters, and foster collaboration between researchers in the field, the SAIMM hosted in 2012, a School on Manganese Ferroalloy Production. The school was presented by Prof. Merete Tangstad, and co-workers.

The 2nd School on Manganese Ferroalloy Production will build on the collaboration between South Africa and Norway, and between role players within the South African manganese industry, by including a larger number of local participants. The focus of the event will be the identification of technoeconomic challenges faced by role players in the South African manganese industry, and finding ways to address these challenges.

MAIN PRESENTER—MERETE TANGSTAD Professor at NTNU (Norwegian University of Science and Technology).

Merete took her Master degree and PhD degree at NTNU. In the following years, she worked for Elkem and Eramet, mostly within ferromanganese and silico-manganese production, and mainly with research within these processes. Since 2004, she has been a professor at the Norwegian University of Science and Technology within Material Science and Engineering, with the main emphasis on manganese ferro-alloy production, and upgrading metallurgical silicon to solar-grade silicon. Merete is co-author of the definitive textbook on manganese ferroalloy production: Production of Manganese Ferroalloys, published by Tapir Press in Norway.

EXHIBITION/SPONSORSHIP Sponsorship opportunities are available. Companies wishing to sponsor or exhibit should contact the Conference Co-ordinator.

Topics to be presented will include: Commercial production Overview of manganese production in South Africa Manganese raw materials - mineralogy and other properties Geology, and mining, of the Kalahari manganese ore body Overview and fundamental thermodynamics Slag fundamentals Pre-reduction zone Cokebed zone Electrical current paths and resistance in furnace Energy consumption Lining concepts in the manganese ferroalloy production Environmental considerations.

The intention is to include in the programme, panel discussions on identification of techno-economic challenges faced by role players in the South African manganese industry, and finding ways to address these challenges.

WHO SHOULD ATTEND Delegates from the manganese ferro-alloy industry, or those who support them: Existing and potential industry role players Engineering companies Research/academic institutions Companies providing funding for new manganese projects.

For further information contact: Conference Co-ordinator, Yolanda Ramokgadi Saimm, P O Box 61127, Marshalltown 2107 Tel: +27 (0) 11 834-1273/7 · E-mail: yolanda@saimm.co.za Website: http://www.saimm.co.za

http://dx.doi.org/10.17159/2411-9717/2015/v115n12a15

Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi

by F.X. Paquot* and C. Ngulube*

The Kansanshi Mine (First Quantum Minerals Ltd) treats a mixed sulphide/oxide copper-gold vein deposit. Until June 2009, the sulphide and oxide minerals were respectively recovered by the well established xanthate flotation of sulphides and acid leaching of soluble oxide copper.

The mixed (transitional) sulphide/oxide ores were stockpiled in the absence of an economic processing route due to their poor flotation response and high gangue acid consumption.

Since June 2009, these mixed ores have been treated by flotation using controlled potential sulphidization. This paper describes the development of the process and its optimization. The effect of the complex mineralogy on the flotation performance is also depicted.

copper flotation, mixed sulphide/oxide ore, controlled potential sulphidazition.

The Kansanshi Mine (First Quantum Minerals) treats a mixed oxide/sulphide copper-gold vein deposit with very variable mineralization. All the copper minerals constituting the alteration sequence from primary sulphides to carbonates or silicates are present in various proportions (Table I).

The alteration of primary sulphides starts with an impoverishment in iron to form covellite. Further oxidation generates an impoverishment in sulphur and enrichment in

Chalcopyrite Bornite Covellite Digenite Chalcocite Malachite Azurite Cuprite Tenorite Chrysocolla Native copper

CuFeS2 Cu5FeS4 CuS Cu9S5 Cu2S CuCO3.Cu(OH)2 Cu2(CO3)2.Cu(OH)2 Cu2O Cu0 (Cu,Al)2H2Si2O5(OH)4.nH2O Cu

* First Quantum minerals Ltd, Kansanshi Mine, Solwezi, Zambia. Š The Southern African Institute of Mining and Metallurgy, 2015. ISSN 2225-6253. Paper received Jan. 2013 and revised paper received June 2015.

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copper to form digenite then chalcocite (Dunn and Muzenda, 2001). The ultimate steps of alteration leading to the formation of copper oxide minerals, such as malachite or chrysocolla, depend on the composition of the gangue or fluid. The iron liberated during the alteration sequence can remobilized and form goethite or limonite. These iron oxides and hydroxides are particularly prejudicial for the flotation if they precipitate on the surface of the copper minerals because they are not collectable with xanthates (Woods, 2003).

Since the beginning of the operations in 2004, millions of tons of mixed oxide/sulphide copper-gold ores with a high gangue acid consumption (GAC) were disposed on stockpiles, as they were uneconomic to treat through the old circuit configuration. This conventional flow sheet incorporated the use of xanthate flotation of the sulphide minerals, followed by acid leaching of the oxides.

The traditional method applied for the flotation of copper oxide or mixed ores is sulphidization, which was first developed with industrial success on Pb-Zn oxide ores in Australia (Crozier, 1991). The method involves multistage addition of sodium sulphide (Na2S), sodium hydrosulphide (NaHS), or ammonium sulphide (NH4)2S as a sulphidizing agent, together with xanthate collectors such as potassium amyl xanthate (PAX) (Mwema and Mpoyo, 2001; Kongolo et al., 2003). The effectiveness of sulphization for flotation of oxidized sulphides has also been demonstrated (Newell et al., 2006).

When introduced in the slurry, the sulphidizer dissociates into the species H2S, HS-, S2depending of the pH. These ions react with the copper oxide minerals, to form a sulphide layer on the surface of the mineral particles (Zhou

Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi and Chander, 1992).The sulphidizer concentration can be controlled by measuring the Es potential of the pulp, using a sulphide ion-selective electrode. The reaction between the sulphidizer and the malachite is optimum at an Es potential of -500 mV (Jones and Woodcock, 1978). However, xanthate flotation is depressed at this potential. Oxidation of sulphide ions in excess by aeration (running air through a laboratory cell as the potential is allowed to rise) for two minutes is then necessary to reach the optimal potential of -300 mV (Ferron and Manu, 1994). This leads to the formation of reducing agents such as thiosulphates, which are not necessarily indifferent in the flotation process (Soto and Laskowski, 1973; Castro et al., 1974).

Direct collectors such as fatty acids and hydroxamates have also been developed for the flotation of oxide minerals (Lee et al., 1998, 2009). The fatty acids have the drawback of being unselective over the carbonated gangue minerals and are therefore unsuitable for the Kansanshi mixed ores.

Paquot et al. (2009) demonstrated the advantage of the sulphidization route over direct hydroxamate flotation.

In June 2009, a new processing route involving controlled potential sulphidization (CPS) was successfully commissioned for the treatment of the Kansanshi transitional ore. Since the commissioning of the CPS plant, hundreds of flotation tests have been conducted on flotation feed and final tails, under various plant conditions, in order to compare the performance of the plant with that under ideal conditions in the laboratory.

Based on this test work, the decision was taken to increase the flotation capacity. In 2011, an extension of the CPS plant was commissioned to increase the number of sulphidization steps. This presentation describes the effect of the mineralogy on the variability of the plant performance, and explains the philosophy that led to the extension of the plant.

Figure 1 depicts the flow sheet of the plant. The first two cells, which are 150 m3, are dedicated for the flotation of sulphides in the mixed ores. The tailings from these two float cells are then fed into a 50 m3 sulphidization tank for two

minutes of conditioning at Es of -500 mV. This is immediately followed by a similarly sized collector conditioning tank. This assemblage of sulphidizer conditioning tank, collector conditioning tank, and two float cells essentially forms a CPS stage. The whole bank of six cells and two sets of conditioning tanks results in residence time of around 25 minutes. The rougher and scavenger concentrates produced are further treated to match the requisite final concentrate grade at a minimum of 25% copper in concentrate.

"214,32.-52/*5 41)0*-5

Semi-quantitative mineralogical analyses were performed by optical microscopy, under crossed polarized light, at the laboratory of Minerals Engineering and Recycling of the University of Liege (Belgium). Different sets of composite samples, corresponding to various styles of mineralization and plant performances, were examined. Only the particle size fractions coarser than 38 Îźm were analysed.

Mineralogical classes were defined according to mineralogy, textures, and gangue relationships. A specific gravity and copper content was attributed to each class in order to calculate the copper distribution between the different classes for each sample and within the flotation circuit.

.012130/514-1 For each flotation test, NaHS from the batch mixed in the plant during the corresponding day was dissolved in raw water to obtain a 2% solution. The xanthate (PAX or SIBX) was used as a 1% w/v solution, 2 minutesâ&#x20AC;&#x2122; conditioning time, and the frother (dipropylene glycol methyl ether) was dosed by drops, as supplied.

3%(,45!5 5 .0 5-)44150&51)45 2/-2/-)35# 5'.2/1

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1254

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Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi

The flotation tests were done using a laboratory Essa flotation machine with a 2.5 L cell. Charges of 1 kg were used in order to obtain a pulp density of 32% solids. The impeller speed was fixed at 800 r/min. The Es of the slurry was controlled with a silver/sulphide combination electrode.

Grab samples of flotation feed and final tails were collected at the same time to evaluate the hourly plant performance. For tests on flotation feed, the number of flotation stages was equal to the number of plant flotation stages. To reflect the plant conditions, no sulphidizer was added in the first flotation stage. The first flotation stage on the final tails was done without adding any reagents, and the second stage with an extra suphidization step. The flotation time for each stage of the laboratory tests was determined applying a scale-down factor of 2.5 to the plant residence time. For each CPS stage, the pulp Es potential was maintained at -500 mV for a predetermined time, in order to obtain the same dosage as in the plant, before adding the collector and frother. Air was added at no particular rate but just at a practical and adequate level to have froth flowing over.

Air was not particularly controlled and was used to oxidize excessive NaHS (sulphide ions) to maintain the Es in the normal range for xanthate flotation, which is around -300 mV. Despite excessive oxidation of sulphidizer, consumption for NaHS was still 20% lower.

"3/4,2.0%3+2.5+.2--4-5 '.2/1 "3/4,2.0%3+2.5+.2--

$ 0.

Chalcopyrite Chalcocite Covellite Chalcopyrite partially replaced by secondary sulphides (covelite, digenite and chalcocite) Chalcopyrite partially replaced by secondary sulphides and associated with iron oxides and hydroxides Non-liberated chalcopyrite Malachite Malachite associated with iron oxides and hydroxides Chrysocolla

Cp Cc Cv Cp+Cv+Dg+Cc

Cp+Cv+Dg+Cc Cp+gangue mal mal+Feox Ch

4-(.1 Table II shows the main mineralogical classes that were established on the plant composite samples, according to mineralogy, textures, and gangue relationships.

Figures 2â&#x20AC;&#x201C;5 illustrate some of the classes established and demonstrate the high variability of the Kansanshi transitional ore mineralization. Liberation in fractions coarser than 38 Îźm is between 90 and 95%. Only very small amount of disseminated chalcopyrite can be locked in gangue minerals.

Chalcopyrite can be liberated, or in association with covelite,

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Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi

3%(,45 5 5"2.2+)31452--0+3214*5 31)53,0/50 3*4-52/*5)$*,0 3*4-

3%(,45 5 5 213 45+0''4,52.14,4*5105+(',314

digenite, chalcocite, goethite, and even malachite. Liberated porous or non-porous chalcocite is observed. Malachite can also be liberated or associated with Iron hydroxides, and the proportion of native copper, partially altered to cuprite, is not always negligible.

Table III compares the average recovery in the plant for particles coarser than 38 Îźm of the main classes in the roughing stage, where no sulphidizer is added, with the total recovery obtained after controlled potential sulphidization.

For the sulphide minerals, the best recoveries in the roughing stage are achieved for chalcocite or chalcopyrite partially altered to secondary sulphides (64 to 65%).

Liberated chalcopyrite has an intermediate floatability, with only 43% recovered in the roughing stage. Covellite also has a poor floatability (48% recovered in the roughing stage).

Even after sulphidization, liberated chalcopyrite and covellite are the sulphide species displaying lower recovery.

Formation of iron oxides and hydroxides on some of the particles of chalcopyrite, altered to secondary sulphides, affects their floatability. Only 50% of the liberated malachite is recovered. Malachite associated with iron oxides and hydroxides is not recoverable. Table IV shows the contribution of each mineralogical class to the copper losses in the final tails of the plant.

Copper losses in final tails, attributed to liberated chalcopyrite and malachite that should be recoverable if properly sulphidized, are 16% and 28% respectively.

Malachite associated with iron oxides and hydroxides also contributes to a significant proportion of losses (20%). These losses are attributed mainly to sulphidization efficiency.

0(%)3/%52/*51012.5,4+0 4,$50&542+)5 3/4,2.5+.2- '.2/1 "3/4,2.0%3+2.5+.2--

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Cp Cc Cv Cp+Cv+Dg+Cc Cp+Cv+Dg+Cc+Fe Cp+gangue mal mal+Feox Ch

42.95 63.63 47.51 65.44 26.91 0.00 1.73 0.00 1.35

86.59 90.32 70.54 92.52 74.41 0.00 49.75 0.00 28.68

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Cp Cc Cv Cp+Cv+Dg+Cc Cp+Cv+Dg+Cc+Fe Cp+gangue mal mal+Feox Ch Total

14.57 3.86 7.33 3.30 6.02 9.75 28.03 19.98 6.16 99.00

Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi .012130/514-1

The very high variations in grades of the Kansanshi transitional ores (from 0.5% to 3% for the TCu and from 0.1% to 1.5% for the AsCu) are ideal for modelling. Multivariable statistical analysis showed that the laboratory and plant performance, in terms of TCu grade of the final tails, is dependent on TCu and AsCu feed grades.

Robust multilinear regressions, using iteratively reweighted least squares, were used for the modelling of the plant flotation final tails and laboratory flotation tails. The combined correlation coefficients are given in Table V. Modelling of the recoveries can be done based on the estimation of the TCu tails grade and the well-known twoproducts formula assuming a constant concentrate grade.

Figure 6 shows the difference between the models established for the laboratory and plant recoveries. The difference after refloating the tails is very low for the low feed grades and reaches a maximum of 10% for the highest feed grades and lower AsCu proportions, the average being 9%.

This difference is explained mainly by the more optimal hydrodynamic conditions of the laboratory flotation cell. For the same TCu feed grade, the difference decreases with the increase in the AsCu feed grade. Unit laboratory reagent dosages were similar to plant dosage rates. The fact that the improvement in recoveries is lower for higher proportions of AsCu shows that more sulphidization steps are necessary to achieve the optimal recovery.

The same considerations as for the modelling of the plant and laboratory performance on the feed were applied for the tests on the final tails. Flotation test tails grade, obtained when refloating the plant final tails with or without an additional sulphidization step, still depends of the TCu and AsCu feed grades. Multilinear regressions, using iteratively reweighted least squares, were used for the modelling of the laboratory flotation tails grades. Correlation coefficients are given in Table VI. Recoveries were estimated using the two-product formula assuming a constant final concentrate of 26% copper.

Figure 7 shows the additional recovery obtained when

#0,,4.2130/5+04&&3+34/1- 5'.2/152/*5.2 0,210,$ &.012130/5123.-5 #(5123.-5 -5 +(52/*5 -#(5&44*5%,2*4Plant final tails Laboratory flotation tails

#0,,4.2130/5+04&&3+34/1 0.72 0.73

#0,,4.2130/-5+04&&3+34/1- 5&3/2.5123.- 5 31)52/* 31)0(152**3130/2.5-(.')3*3 2130/ #(5123.-5 -5 #(52/*5 -#(5&44*5%,2*4-

#0,,4.2130/5+04&&3+34/1

Without additional reagents With additional sulphidization step

0.70 0.62

floating the plant flotation tails without any additional reagents and with an additional sulphidization step.

Plant recovery can be increased by an average of 5% when re-floating plant final tails in one flotation step without adding any reagents, the upgrade being 15. The lower the feed grades and the higher the AsCu proportion, the less is the improvement. After an additional sulphidization step, recovery can be increased by an average of 10%, the upgrade being 16. The higher the AsCu proportion the greater the improvement. These observations confirm the results obtained when comparing the laboratory and the plant performances on the flotation feed. Performance of the plant is then affected not only by the hydrodynamics of the cells and the residence time, but also by a lack of sulphidization steps. An increase of 5% recovery is achievable by increasing plant residence time by 20 minutes and a further 5% by adding two more sulphidization stages.

#0/+.(-30/-5 The very variable performances of the new Kansanshi transi-

" 5!! 55

5

1257

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3%(,45 5 5 3&&4,4/+45 41 44/5.2 0,210,$52/*5'.2/15,4+0 4,34-

Development and optimization of mixed sulphide/oxide copper ore treatment at Kansanshi

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tional ore processing route are explained by the complexity of the mineralization. All the minerals constituting the alteration sequence, from primary copper sulphide minerals to oxide minerals, are present in the Kansanshi ores in variable proportions. A detailed optical mineralogical analysis on plant composite samples, corresponding to various mineralization classes and plant performance, showed that the sulphide minerals displaying the best floatability in the roughing stage, where no sulphidizer is added, are the chalcocite or chalcopyrite partially altered in chalcocite and other secondary sulphides. Liberated chalcopyrite is mainly recovered together with the malachite in the controlled potential sulphidization section. Final copper losses are attributed mainly to liberated chalcopyrite and malachite that should be recoverable. Flotation tests on the plant flotation feed and final tails were used to establish models of the difference between laboratory and plant performance, and of the improvement in recoveries when re-floating the plant final tails with and without an additional sulphidization step.

The difference between laboratory and plant performance averages 9% and decreases with low feed grades and high AsCu feed grade proportions. The improvement when refloating the plant final tails without additional reagents averages 5%, and decreases with low feed grades and high AsCu feed grade proportions. The improvement when refloating the plant final tails with an additional sulphidization step averages 10% and increases with high AsCu proportions.

This test work showed that an increase of 10% of recovery should be achievable by increasing plant residence time and the number of sulphidization stages.

4&4,4/+4CASTRO, S., SOTO, H., GOLDFARB, J., and LASKOWSKI, J. 1973. Sulphidizing reactions in the flotation of oxidized copper mineral, II. Role of the adsorption and oxidation of sodium sulphide in the flotation of chrysocolla and malachite. International Journal of Mineral Processing, vol. 1. pp 151â&#x20AC;&#x201C;161.

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CROZIER, R.D. 1991. Flotation, Theory, Reagents and Ore Testing. Pergamon Press.

DUNN, J.G. and MUZENDA, C. 2001. Thermal oxidation of covellite (CuS).

Thermochimica Acta, vol. 369, no. 1-2. pp 117â&#x20AC;&#x201C;123.

FERRON, C.J. and MANU, N.N. 1994. Recovery of copper oxide minerals by sulfidization flotation. Lakefield Research, Canada. 11 pp.

Lee, J.S., Nagaraj, D.R., and Coe, J.E. 1998. Practical aspects of oxide copper recovery with alkyl hydroxamates. Minerals Engineering, vol. 11, no. 10. pp. 929-939.

LEE, K., ARCHIBALD, D., MCLEAN, J., and REUTER, M.A. 2009. Flotation of mixed copper and sulphide minerals with xanthate and hydroxamate collectors.

Minerals Engineering, vol. 22. pp. 395â&#x20AC;&#x201C;401.

JONES, M.H. and WOODCOCK, J.T. 1978. Optimization and control of laboratory sulphidization of oxidized copper ores with an ion selective electrode.

Proceedings of the Australasian Institute of Mining and Metallurgy, no.

266. pp. 11â&#x20AC;&#x201C;17.

KONGOLO, K., KIPOKA, M., MINANGA, K., and MPOYO, M., 2003. Improving efficiency of oxide-cobalt ores flotation by combination of sulphidisers.

Minerals Engineering, vol. 16. pp. 1023â&#x20AC;&#x201C;1026.

MWENA, M.D. and MPOYO, M., 2001. Improvements of cobalt recovery in flotation of cupro-cobaltiferous ore at Gecamines. Proceedings of the Copper Cobalt Nickel and Zinc Recovery Conference, Victoria Falls, Zimbabwe, 16â&#x20AC;&#x201C;18 July, 2001. Southern African Institute of Mining and Metallurgy (Zimbabwe Branch). pp. 1â&#x20AC;&#x201C;9.

NEWELL, A.J., SKINNER, W.M., and BRADSHAW, D.J. 2006. Restoring the floatability of oxidized sulfides using sulfidisation. International Journal of Mineral Processing, vol. 84. pp. 108â&#x20AC;&#x201C;107.

PAQUOT, F.X., BASTIN, D., MUKUTUMA, A., and DELANEY, A. 2009. Metallurgical performances of the sulphidization route and the direct alkyl hydroxamates flotation of mixed carbonated copper-gold ores of the Kansanshi deposit. Flotation 09, Cape Town, South Africa, 9â&#x20AC;&#x201C;12 November 2009.

Minerals Engineering International, Falmouth, UK. RAGHAVAN, S., ADAMEC, E., and LEE, L. 1984. Sulfidization and flotation of chrysocolla and brochantite. International Journal of Mineral Processing, vol. 12. pp. 173â&#x20AC;&#x201C;191.

WOODS, R. 2003. Electrochemical potential controlling flotation. International Journal of Mineral Processing, vol. 72. pp. 151â&#x20AC;&#x201C;162. â&#x2014;&#x2020;

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Webber Wentzel

DTP Mining

Murray and Roberts Cementation

Weir Minerals Africa

Duraset

Nalco Africa (Pty) Ltd

WorleyParsons (Pty) Ltd

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Tomra Sorting Solutions Mining (Pty) Ltd Ukwazi Mining Solutions (Pty) Ltd

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EXHIBITS/S

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SAIMM DIARY or the past 120 years, the Southern African Institute of Mining and Metallurgy, has promoted technical excellence in the minerals industry. We strive to continuously stay at the cutting edge of new developments in the mining and metallurgy industry. The SAIMM acts as the corporate voice for the mining and metallurgy industry in the South African economy. We actively encourage contact and networking between members and the strengthening of ties. The SAIMM offers a variety of conferences that are designed to bring you technical knowledge and information of interest for the good of the industry. Here is a glimpse of the events we have lined up for 2016. Visit our website for more information.

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2016 FORUM Global Mining Standards and Guidelines Group â&#x20AC;&#x2DC;GMSGâ&#x20AC;&#x201D; SAIMM Forum 2016: Building towards the future of miningâ&#x20AC;&#x2122; 15â&#x20AC;&#x201C;16 February 2016, Emperorâ&#x20AC;&#x2122;s Palace, Johannesburg, Gauteng CONFERENCE Diamonds still Sparkle 2016 Conference 14â&#x20AC;&#x201C;17 March 2016, Gaborone International Convention Centre CONFERENCE The SAMREC/SAMVAL Companion Volume Conference 17â&#x20AC;&#x201C;18 May 2016, Johannesburg COLLOQUIUM New technology and innovation in the Minerals Industry Colloquium 9â&#x20AC;&#x201C;10 June 2016, Mintek, Randburg SCHOOL The 2nd School on Manganese Ferroalloy Production 27â&#x20AC;&#x201C;28 June 2016, Johannesburg CONFERENCE Resilience in the Mining Industry Conference 2016 13â&#x20AC;&#x201C;15 July 2016, University of Pretoria CONFERENCE Hydrometallurgy Conference 2016 1â&#x20AC;&#x201C;3 August 2016, Cape Town

For further information contact: Conferencing, SAIMM Pâ&#x20AC;&#x2C6;Oâ&#x20AC;&#x2C6;Box 61127, Marshalltown 2107 Tel: (011) 834-1273/7 Fax: (011) 833-8156 or (011) 838-5923 E-mail: raymond@saimm.co.za

CONFERENCE The Tenth International Heavy Minerals Conference 16â&#x20AC;&#x201C;18 August 2016, Sun City, South Africa CONFERENCE AMI Ferrous and Base Metals Development Network Conference 2016 7â&#x20AC;&#x201C;11 November 2016, MSC Sinfonia Cruise, Durban-Mozambique-Durban

Website: http://www.saimm.co.za

CREATING A SAFE OPERATING ENVIRONMENT WITH OUR SAFETY SPECIALISTS Sasol places safety at the heart of our workplace. Technology like the Close Proximity Detection System shuts down mining machinery if an employee gets too close, and industry projects which improve methane dilution have been co-developed, initiated and rigorously tested by our specialists.

Itâ&#x20AC;&#x2122;s just a few of the many steps we have taken to create a working environment which is safe, responsible and productive.

www.sasol.com