Mechanics, Materials Science & Engineering journal Vol. 14

MMSE Journal. Open Access www.mmse.xyz

Sankt Lorenzen 36, 8715, Sankt Lorenzen, Austria

Mechanics, Materials Science & Engineering Journal

February 2018

MMSE Journal. Open Access www.mmse.xyz

Mechanics, Materials Sciences & Engineering Journal, Austria, Sankt Lorenzen, 2018

Mechanics, Materials Science & Engineering Journal (MMSE Journal) is journal that deals in peerreviewed, open access publishing, focusing on wide range of subject areas including, engineering, materials science, physics, FEA etc.

MMSE Journal is dedicated to knowledge-based products and services for the academic, scientific, professional, research and student communities worldwide.

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The Journal Policy declares the acceptance of the scientific papers worldwide, if they passed the peerreview procedure. Published by industrial company Magnolithe GmbH MMSE Journal Editorial Board Dr. Girish Mukundrao Joshi, VIT University, India Prof., Dr. Murch, Graeme E.,University of Newcastle, Australia, Centre for Geotechnical Science and Engineering, Callaghan, Australia Prof. Amelia Carolina Sparavigna, Politecnico di Torino, Italy Dr. Zheng Li, University of Bridgeport, USA Prof. Kravets Victor, National Mining University, Ukraine Dimitrios Vlachos, Associate professor, University of Peloponnese, Department of Informatics and Telecommunications, Greece Hovik A. Matevossian, Russian Academy of Sciences, Russian Federation Dr. S. Ramesh, KCG College of Technology, Karapakkam, India Dr. Yang Yu, University of Technology Sydney, Australia Ph.D. José Correia, University of Porto, Portugal

ISSN 2412-5954 e-ISSN 2414-6935

Design and layout: Mechanics, Materials Science & Engineering Journal (Magnolithe GmbH) www.mmse.xyz Support: hotmail@mmse.xyz ©2018, Magnolithe GmbH © Published by Magnolithe GmbH. This is an open access journal under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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CONTENT I. Materials Science MMSE Journal Vol. 14 ................................................................................... 5 AC Impedance, Surface & TGA/DTA Analysis of PVC- LiNO3 –CdO. P. Karthika, B. Sundaresan ..................................................................................................................................... 6 Synthesis and Electrochemical Studies of ReO3 Type Phase Nb3O7F. D. Saritha ................ 11 The Structural and Electrical Properties of Nano Sized Zn and Mn Ferrites by Sol-Gel Method. R. Kishore Kumar, C.S. Naveen, V. Mowlika, R. Robert, A.R. Phani ................................ 17 Manifestation of Ferromagnetism in Rare Earth Doped BiFeO3 Multiferroics. Avinash M., Murlidharan M., Sivaji K. .................................................................................................................. 22 Crystallization of Alpha- Lactose Monohydrate (α-LM) from Aqueous Solution through Gas-Phase Diffusion and Anti-Solvent Crystallization Methods. K. Vinodhini, K. Srinivasan .. 30 Synthesis, Characterisation and Heat Transfer Analysis of TiO2 -Water Nanofluid. Bikash Pattanayak, Abhishek Mund, Jayakumar J.S., Kajal Parashar, S.K.S. Parashar ............................. 36 Grey Relational Analysis for Wire-EDMed HCHCr using Taguchi’s Technique. K. Srujay Varma, Shaik Riyaaz Uddien, G. Narendar, V. Durga Prasad ......................................................... 46 Investigation on Embllishment of Metal Nanoparticles on Graphene Nanosheets and Its Sensing Applications. V. Ramalakshmi, J. Balavijayalakshmi ........................................................ 52 Co-Dopands on Hydroxyapatite in Structural, Morphology And in Antibacterial Activity.

S. Helen, A. Ruban Kumar ................................................................................................................ 66 First-Principles Study on the Electrical Properties of Cu2GeSe3 Compound. Devi Prasadh P.S., B. K. Sarkar, A. Arulgnanam ..................................................................................................... 72 Impedance Behavior of Pb1-xCoxFe12O19 Obtained by Sol-Gel Auto Combustion Method.

S. Prathap, W. Madhuri ..................................................................................................................... 76 II. Mechanical Engineering & Physics MMSE Journal Vol. 14 ................................................. 80 Design Validation of the Working Surface of a Sheep’s Foot Roller for Compaction of Freshly Prepared Soil. D. Artemenko, V. Nastoyaschiy, V. Darienko ............................................. 81 Feature-Based Discretization of a Turbine Disk for Probabilistic Risk Assessment. Michael A. Thomas, Jace Carter, Lloyd Matson, Tarun Goswami ................................................................ 90

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I . M a t e r i a l s S c i e n c e M M S E J o u r n a l V o l . 1 4

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AC Impedance, Surface & TGA/DTA Analysis of PVC- LiNO3 –CdO 1

P. Karthika1,a, B. Sundaresan1 1 – Centre for Research and Post-Graduate Studies in Physics, Ayya Nadar Janaki Ammal College (Autonomous), Sivakasi, India a – pkarthikaa@gamil.com DOI 10.2412/mmse.96.41.206 provided by Seo4U.link

Keywords: NCPE, AC Impedance, SEM & TGA/DTA.

ABSTRACT. Polymer electrolytes PVC – LiNO3 - CdO were prepared using solution casting technique and were characterized by AC impedance, SEM & TGA/DTA techniques. Ionic conductivity of the polymer electrolytes was determined using AC impedance method. Maximum value of ionic conductivity was observed for the optimized composition of PVC and LiNO3 in the polymer electrolyte. SEM micrographs brought out a good correlation among the surface morphology, ionic conductivity and amorphous/crystalline structures of the studied polymer electrolytes.

The thermal properties of polyvinyl chloride (PVC) – Lithium Nitrate (LiNO3)- Cadmium Oxide(CdO) by Thermo Gravimetric Analysis(TGA) gives rise the information on the thermal stability of polymer electrolytes.

Introduction. Recent days, there is very much interest in studying the ionic conductivity at ambient temperature due to their good performance in high power rechargeable lithium battery, which may be used in laptops and even an electric vehicles & other portable electronic equipment. The polymer electrolytes prepared with high conductivity, good mechanical strength and thermal stabilities , have interest due to the role of polymer electrolytes in lithium batteries, electro – chromic windows, sensors and fuel cells etc. [1]. Polymers are widely used in our routine life due to their fascinating and extraordinary characteristics. These materials are found to replace the conventional materials in terms of strength, stability and toughness. Since the beginning of plastic industry, it is observed that blending yields materials with superior features of the individual components. Blending of polymers provide new materials which combine the useful property of all constituents.

Polymer electrolytes have technological interest due to their applications as solid electrolytes in various electrochemical devices such as energy conversion units, electro-chromic display devices, photo chemical solar cells and sensors. Lithium batteries with polymer electrolytes are mostly studied among the various applications. A polymer electrolyte acts as a separator as well as an electrolyte in a secondary battery. Studies on polymer electrolytes have great intention to explain the enhancement mechanism of conductivity. In various ionic species, the concentrations are important to understand the overall mechanism of conductivity. The surface and morphological behaviors of polymer electrolytes have been studied by SEM. Here, the polymer electrolytes are prepared by solution casting technique, which contained polyvinyl chloride (PVC) as a host polymer and lithium nitrate (LiNO3) as a salt. The nano filler CdO is added with various proportion to this polymer electrolytes to get nanocomposite polymer electrolytes (NCPE). Then, the thermal characteristics have been done by Thermo Gravimatric Analysis (TGA). Conductivity studies are done with the help of ac impedance analyzer.

Experimental Techniques.

© 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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Materials & Methods. Chemicals with AR/BDH grade purchased from Aldrich, Merck companies and used as such, Tetra Hydro Furan (THF) used after distillation only. Polymer: Poly(vinyl chloride), Polyelectrolyte: Lithium nitrate(LiNO3), Solvent: Tetra Hydro Furan (THF), Nano filler: Cadmium Oxide (CdO).

The polymer complex prepared by solvent casting technique. It was very simple and most widely used technique for preparation of thick films. The appropriate quantity of PVC & LiNO3 dissolved in Tetra hydro furan. After a complete dissolution of polymer and salt, metallic filler CdO added and stirred for 4 – 5 hours. A homogeneous solution obtained after stirrer and resulting solution poured on to a glass plate and THF allowed to evaporate in air at room temperature in dust free atmosphere. The films dried for another one day to remove any trace of THF. For various concentration of CdO the films were prepared.

Result and Discussion AC Impedance Analysis. PVC composite with LiNO3 analyzed in order to understand the effect of polymer electrolyte conductance. Ionic conductivity determined by ac impedance analysis at room temperature say around 302K. Various combination of the three components PVC- LiNO3- CdO compared and one of them shown in Fig. 1, (e). The ionic conductivity of polymer electrolyte can be calculated using the formula given. σac=Thickness/(Area) × (Resistance) = s/cm.

Ionic conductivity of polymer electrolyte varied due to the concentration of conducting species and their mobility. Increasing conductivity against the concentration of CdO can be seen that PVC – LiNO3 exhibited the lowest conductivity as 5.27 × 10- 10 s/cm. The effect of concentration of nanofiller CdO on the ionic conductivity of the films showed that the increase in concentration of CdO, ionic conductivity also increased which may be due to increase in the number of mobile ions in the solid polymer electrolytes. A highest value of 6.33 × 10-6 s/cm was obtained at 10 Wt % of CdO. The addition of nanofiller with the polymer electrolyte system made the system be more amorphous and promoted more free lithium ions from the inorganic salt of LiNO3 [1].

Fig. 1. Impedance Plot for PVC + LiNO3 + CdO (10 Wt).

Increase of nanofiller reduced the crystallinity of composite polymer electrolyte. A polymer chain in the amorphous phase was more flexible which increased segmental motion of polymer. Oxygen concentration enhanced the conductivity of electrolyte [2]. The lithium (Li +) ion moved like a gaseous molecule in free volume model where Li+ transferred to coordinating sites in the same MMSE Journal. Open Access www.mmse.xyz

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polymer chain. The segmental motion of increased ionic conductivity. When smaller size nanofiller added to polymer electrolytes may be promoted amorphous region there by enhancing the transportation of ions in membrane.

Based on Lewis acid – base interaction, ceramic filler influenced the ionic conductivity of polymer electrolyte due to interactions between the surface groups of ceramic particles and lithium salt [3].

Li+ served as a strong Lewis acid where as polymer and filler CdO served as a Lewis base centers.

Therefore, the polymer - Li+ cation and filler - Li+ cation interactions may be widely used to explain the polymer – salt complex interaction [4]. This created structural modification, which may be acted as a cross linking centers for the polymer segment and the salt anions.

The Lewis – base interaction centers lowered ionic coupling there by salt dissociation promoted via a sort of ion – ceramic complex formation. The mentioned two effects enhanced the conductivity of nanocomposites. Oxygen and OH surface groups on CdO grains interacted with cations and anions based on Lewis acid – base and promoted additional site creating favorable high coordinating pathways in the vicinity of grains for the migrations of ions [5]. It enhanced the mobility for migrating ions.

SEM Analysis. Fig. 2 (a) showed that the rough surface with streaks. PVC – LiNO3 complex with CdO (3 Wt %) showed maximum number of pores of random shapes giving rise to increase in conductivity of this sample. There are two possible ways for formation, first one was the evaporation of solvent and second one was the casting of the film. Plasticizer occupied the pores, which acted as the tunnel for ionic transport.

a)

b) Fig. 2. (a) SEM Micrograph for PVC + LiNO3, (b) SEM Micrograph for PVC + LiNO3 + CdO (8 Wt %).

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It was observed that pores in 3 Wt % disappeared when CdO concentration increased to 5 Wt %.

This might be occurred due to fill the pores of CdO there by promoting amorphicity through plasticizing effect of filler.

In Fig. 2 (b), it was noticed that the appearance of number of uniform tracks of few micrometer size along with reduced size which was responsible for the enhancement o ionic conductivity of PVCLiNO3 – CdO (8 Wt %). The distinct spherules by dark boundaries showed in solid polymer electrolyte with CdO 10 Wt %. This was due to amorphous phase [10]. Thus, SEM study supported the conclusions drawn through ac conductivity studies.

TGA/DTA Analysis. Based on the TGA graph, the percentage total weight loss of sample can be calculated through the direct subtraction of the percentage residue from 100 Wt %. Since this graph was plotted as weight as temperature. In Fig. 3 (a), the TGA/DTA trace of pure PVC, the weight losses corresponding to various temperature regions were shown. It showed that six stages of degradation. The first stage of degradation occurred in region 0˚ C – 250 ˚ C with weight loss of 1.54 % which ascribed to the removable of unsaturation of PVC [5]. The unbroken double bonds of vinyl chloride monomers presented in some of PVC macromolecules as a consequences of the disproportionate chain termination reaction during polymerization and called unsaturation reaction.

These double bonds would be broken at the first stage of degradation and would be led to monomers evaluation as observed in the case of PMMA [5].

In pure PVC + LiNO3, 1st degradation occurred at 0 C ̊ -150 ̊C with 16.59% weight loss which was very much higher than Pure PVC. There was gradual then faster degradation around 150 ̊C that indicated the thermal stability of complexes initially lower than PVC. Around 250 C ̊ - 315 C , there was 40.87% weight loss compared with PVC, then the thermal stability was higher. Around 315 ̊C – 445 ̊C, 6.22% weight loss and around 445 ̊C – 555 C ̊ , 17.95% weight loss occurred, both indicated higher thermal stability. Thermally irreversible state reached by following degradations such as around 555 ̊C – 610 C, 2.86% weight loss ,610 ̊C – 770 ̊C, 7.704 % weight loss and 770 C ̊ – 1050 ̊C, 1.85% weight loss. PVC + LiNO3 initially exhibited lower thermal stability when compared with PVC & then above 150 C ̊ showed higher thermal stability.

Fig. 3. TGA – DTA plot for pure PVC. Summary. Using solvent casting technique, the nanocomposite polymer electrolyte prepared and in order to understand the role of nanofiller on the thermal and electrical properties, the nanofiller of different concentration of CdO added to PVC - LiNO3. Ionic conductivity of polymer electrolyte depends on the concentration of conducting species & their mobility .The addition of nano-fillers MMSE Journal. Open Access www.mmse.xyz

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enhanced the ionic conductivity. SEM confirmed the plasticizing action of CdO. TG-DTA provided the information with regard to their thermal stability, crystallinity & other thermal parameters.

References [1] S. Ramesh, A.K. Akof (2001), Ionic conductivity studies of plasticized poly (vinyl chloride) polymer electrolytes, Mater. Sci. Eng. B, 85 (1), 11-15, DOI: 10.1016/S0921-5107(01)00555-4.

[2] Sejal Shah, Dolly Singh, Anjum Qureshi, N L Singh, V. Shrinet (2008), Dielectric properties and surface morphology of proton irradiated feuic oxalates dispersed PVC films, Indian J. Pure & Appl. Phys, 46, 439-442.

[3] Azizan Ahmad, Mohd. Yusri Abdul Rahman, Siti Aminah Mohd Noor, Mohd Reduan Abu Bakar (2009), Preparation and characterization of PVC - Al2O3-LiClO4 composite polymeric electrolyte, Sains. Malays, 38 (4), 107- 113.

[4] W. Wiec Zorek, J.R. Stevens, Z. Florja Czyk, (1996), Composite polyether based solid electrolytes, The Lewis acid base approach, Solid State Ionics, 85 (1-4), 67-72, DOI 10.1016/01672738(96)00042-2.

[5] F. Croce, L. Persi, F. Ronci, B. Scrosati (2000), Nanocomposite polymer electrolytes and their impact on the lithium battery technology, Solid State Ionics, 135 (1-4), 47-52, DOI 10.1038/28818.

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Synthesis and Electrochemical Studies of ReO3 Type Phase Nb3O7F 1

D. Saritha1,a 1 – KL University, Department of Chemistry, Hyderabad, India a – sarithaiitm@gmail.com DOI 10.2412/mmse.12.100.949 provided by Seo4U.link

Keywords: ReO3 structure, electrochemical studies, Nb3O7F.

ABSTRACT. In latest era, explore for alternative materials to carbonaceous negative electrodes working at higher potential in lithium ion batteries is given enormous significance to avoid lithium plating and electrolyte decomposition.

Niobium based oxides show enhanced results as choice to carbonaceous anodes and also Nb 5+/4+ redox couple working at approximately 1.5 V vs lithium. The redox potential of the niobium metal ion (~1.5V) and the structure of Nb 3O7F encourage us lithium insertion studies. Nb3O7F compound has been synthesized through a simple solid state method to explore as anode material. A structural and electrochemical property of this compound is studied in detail. The chargedischarge curves are obtained galvanostatically at C/5 rate. In first discharge step, 5.3 Li can be inserted into four step process between 3.0 – 1.0 V with a specific capacity of 350 mAhg-1. Four plateaus are observed at 1.65, 1.3, 1.2 and 1.1V. During charge 1.3 Li can be extracted with an irreversible capacity loss. The total first-charge capacity is 86 mAhg-1 corresponding to the extraction of 1.3 Li. These cells show a reversible capacity 86 mAhg -1 after 25 cycles. The detailed results will be described and discussed.

Introduction. Lithium insertion in oxides is a vital area in view of lithium ion batteries applications.

Materials which can reversibly incorporate Li ions at `room temperature has gained momentous attention owing to their potential use as electrode materials in lithium ion batteries. Numerous framework structure metal oxides have been studied to satisfy these concerns. Out of these structures, two structures are familiar ReO3 related shear structures and rutile structures [1-3].The ReO3 structure type phases have fascinated as a host to lithium ions, in prospect of attaining fast lithium diffusion, because in such structure, lithium sites are connected in all three directions. The ReO 3 structure consists of corner-shared ReO6 octahedra [1]. Lithium insertion into ReO3 structure leads to structural distortion [2]. Cava et al. have exposed that introducing edge sharing into the corner sharing ReO3 structure stabilizes the structure after lithium insertion [3-5] The redox potential of the concerned transition-metal element and the open crystallographic structure of the oxide are the two important criteria to study the new materials as electrode materials for lithium ion batteries [5]. Based on all these factors, the redox couples of the compound Nb3O7F are Nb5+/Nb4+ and Nb4+ /Nb3+ and also the open ReO3 framework structure motivated to study the Nb3O7F as electrode material. Nb3O7F belongs to shear ReO3 type structure [6]. It crystallizes in the orthorhombic space group Pbcn with lattice parameters a = 20.67 Å, b = 3.833 Å and c = 3.927 Å.

The structure of Nb3O7F projected along the b-axis is shown in Fig. 1. The cavity: I and II in the Fig. 1 represents the perovskite holes and the distorted six-coordinated interstices in the shear planes [6 ].

Nb3O7F is built up of Nb(O,F)6 octahedra linked in such a way that two different interstices the 12coordinated perovskite holes in the slabs of corner-sharing octahedra and the 6-coordinated holes in the shear planes. Permer et al. has studied the chemical lithium insertion into the compound.

[6].Recently, electrochemical lithium insertion studies on ReO3 structure type LiTiNbO5, Ti2Nb2O9 and AlNbO4 has been explored for Li insertion [7- 9].

© 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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Fig. 1.Crystal structure of Nb3O7F along ac-plane [6].

Niobium based oxides has gained attention for its possible use as anode materials in terms of safety and reliability compared to carbon based materials since the potential of Nb5+ /Nb4+ and Nb4+/Nb3+ redox couples positioned between 1.0 and 2.0 V. Moreover, it leads to high capacity due to two electron transfer per niobium [10, 11]. In this perspective, numerous niobium oxides with different structural types have been reported, such as Nb2O5 [10–14], LiNb3O8 [15], Ti2Nb10O29 [16], TiNb2O7 [17], KNb5O13 [18], FeNb11O29 [19], LiNbO3 [20], Nb ions are chemically reducible; Li ions can be inserted into the vacant sites. In fact, chemical insertion of Li using n- butyl lithium into Nb3O7F has been reported [6]. Currently, we have studied the electrochemical behaviour of Nb3O7F with Li-metal under discharge–charge conditions (range 1.0V–3.0 V). The results showed that the Nb3O7F exhibits a reversible capacity of 86 mAh g−1 Corresponding to ∼1.5 mol of Li per mole of Nb3O7F. In addition, the high oxidation state of the transition metal that forms this structure can facilitate insertion of a large amount of lithium [2].

Experimental Syntheis. Nb3O7F is synthesized by thermal decomposition of NbO2F (obtained from Nb2O5 metal dissolved in HF) in Ar atomsphere at about 500 C [6]. The obtained samples are used for characterization and electrochemical studies.

Characterization. The obtained powder is characterized by x-ray diffractometer (Rigaku miniflex) equipped with Cu-Kα radiation. For electrochemical studies, electrodes are fabricated by mixing active material, acetylene black (Denka Singapore Pvt.Ltd.) and polyvinylidene fluoride (PVDF) in the weight ratios 70:20:10. The slurry prepared by using N-methyl-2-pyrrolidinone is spread on a stainless steel foil and dried in an oven at 80 ºC for 12 h. Swagelok cells were fabricated in an argon filled glove box (mBraun, Germany, <5 ppm H2O) with lithium foil as anode, Teklon (Anatek, USA) as separator and 1 M LiPF6 in 1:1 EC + DMC (Chiel industries Ltd., Korea) as the electrolyte.

Charge-discharge cycling of the cells is carried out in galvanostatic mode at 1 C rate (reaction of I Li in I hour) at room temperature by using Arbin battery cycling unit (BT2000, USA).

Results and Discussion Phase formation. The representative powder x-ray diffraction pattern of Nb3O7F is shown in Fig. 2.

The sample is single phase and is indexed according previous reports [6].

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Fig. 2. Powder x-ray diffraction patterns of Nb3O7F. Electrochemical studies Voltage-capacity-composition profile Nb3O7F cell is shown in the potential range of 1.0–3.0 V (Fig. 3).The charge-discharge curves are obtained galvanostatically at C/5 rate.

During initial discharge, the voltage drops from the open circuit voltage of 2.7 V to 2.1 V. When discharged at this rate, 5.3 Li in Nb3O7F are inserted. During charge, 1.3 Li are extracted. On subsequent cycling 1.3 Li are reversibly inserted. The discharge profile of second and consequent cycles is similar however the first discharge is different from that of the first charge. The irreversible capacity loss in the first cycle is ascribed to the irreversible structural change. Large polarization is observed between discharge and charge processes. Four plateaus are observed at 1.65, 1.3, 1.2 and 1.0 V from the differential capacity plot of Nb3O7F (Fig. 4). These peaks can also be observed from the charge-discharge cycles. One peak is observed at 1.65V. This peak can be assigned to the Nb5+/Nb4+ redox couple based on the previous reports [10-21]. Three peaks are observed in the range of 1.0–1.4 V corresponds to the Nb4+/Nb3+ redox couple. The initial discharge capacity of Li vs.

Nb3O7F cell is 350 mAhg-1, corresponds to the insertion of 5.3 Li. The first-charge (extraction of Li) profile is qualitatively different from that for the first discharge, and shows a smooth increase in voltage with a small plateau at 1.9V (Fig. 7, b). Thereafter, the voltage increases rapidly up to the upper cutoff of 3.0V. The total first-charge capacity is 86 mAhg-1 corresponding to the extraction of 1.3 Li. However, the second charge curve follows the same trend as that of the first-charge profile.

The powder XRD pattern of Lithium inserted phase was indexed as LiNbO3 structure type phase, whereas the diffraction pattern of the Lithium deinserted phase was very diffuse, and no discrete lines could be recognized based on previous literature reports [6, 21]. The electrochemical cycling performance of Nb3O7F prepared by solid state methods at C/5 rates is shown in Fig. 5. These cells show a reversible capacity 86 mAhg-1 after 25 cycles (Fig. 5).

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Fig. 3. Charge-discharge curves of Nb3O7F.

Fig. 4. Differential capacity plots of Nb3O7F for the first three cycles.

Fig. 5. Cyclic behavior of Nb3O7F.

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Summary. Nb3O7F anode material was synthesized by an effortless solid-state method. In the present work we have studied electrochemical lithium insertion in Nb3O7F with ReO3 type structure. Our studies show that, 5.3 Li can be inserted into Nb3O7F. Nb3O7F shows reversible capacity of 86 mAh/g after 25 cycles. Nb3O7F exhibits a poor reversibility as a result of irreversible structural transformation. Nano Size can improve the reversibility of Nb3O7F anode.

References [1] R.J. Cava, A. Santoro, D.W. Murphy, S. Zahurak, R.S. Roth (1981), Structural aspects of lithium insertion in oxides: LixReO3 and Li2FeV3O8, Solid State Ionics, 5, 323-326, DOI 10.1016/01672738(81)90258-7 [2] D.W. Murphy (1986), Insertion reactions in electrode materials, Solid State Ionics, 18-19, 847851, DOI 10.1016/0167-2738(86)90274-2 [3] A. Martı’nez-dela Cruz, M. Torres-Martı’nez Leticia, F. Garcı’a Alvarado, E. Mora’n, M.A. Alario-Franco (1998), Formation of new tungsten bronzes: electrochemical zinc insertion in WO3, J. Mater. Chem, 8(8), 1805-1807, DOI 10.1039/a801461b [4] R.J. Cava, D.W. Murphy, S.M. Zahurak (1983), Lithium insertion in Wadsley-Roth Phases Based on Niobium Oxide, J. Electrochem. Soc, 130, 2345-2351, DOI 10.1149/1.2119583 [5] R.J. Cava, D.W. Murphy, E.A. Rietman, S.M. Zahurak, H. Barz (1983), Lithium insertion, electrical conductivity and chemical substitution in various crystallographic shear structures, Solid State Ionics, 9-10, 407-411, DOI 10.1016/0167-2738(83)90267-9 [6] L. Permer (1992), Li-inserted Nb3O7F and its thermal decomposition products studied by highresolution electron microscopy and X-ray powder diffraction, J. Solid State Chem, 97, 105–114, DOI 10.1016/0022-4596(92)90014-M [7] J.F. Colin, V. Pralong, V. Caignaert, M. Hervieu, B. Raveau (2006), A new layered titanoniobate LiTiNbO5: Topotactic synthesis and electrochemistry versus lithium, Inorg. Chem, 45(18), 72177223, DOI 10.1021/ic060801o [8] J.F. Colin, V. Pralong, M. Hervieu, V. Caignaert, B. Raveau (2008), Lithium insertion in an oriented nonporous oxide with a tunnel structure: Ti2Nb2O9, Chem. Mater, 20(4), 1534-1540, DOI 10.1021/cm702978g [9] M. Anji Reddy, U.V. Varadaraju (2008), Facile insertion of lithium into nanocrystalline AlNbO4 at room temperature, Chem. Mater, 20(14), 4557-4559, DOI 10.1021/cm801194b [10] A.L. Viet, M.V. Reddy, R. Jose, B.V.R. Chowdari, S. Ramakrishna (2009), Nanostructured Nb2O5 polymorphs by electrospinning for rechargeable lithium batteries, J Phys Chem C, 114(1), 664, DOI 10.1021/jp9088589 [11] X.J. Wang, F. Krumeich, M. Wcrle, R. Nesper, L. Jantsky, H. Fjellva (2012), Niobium(V) oxynitride: synthesis, characterization, and feasibility as anode material for rechargeable lithium-ion batteries, Chem Eur J, 18(19), 5970, DOI 10.1002/chem.201102653 [12] L.P.Wang, L.H. Yu, R. Satish, J.X.Zhu, Q.Y.Yan, M. Srinivasan, Z.C. Xu (2014), Highperformance hybrid electrochemical capacitor with binder-free Nb2O5@graphene,RSC Adv,4(70), 373-389, DOI 10.1039/C4RA06674J [13] P. Arunkumar, G. Ashisha, B. Babu, S. Sarang, A. Suresh, C.H.Sharma, M. Thalakulam, M.M.Shaijumon (2015), Nb2O5/graphene nanocomposites for electrochemical energy storage, RSC Adv, 5(74), 599-97, DOI 10.1039/C5RA07895D [14] E. Lim, H. Kim, C.Jo, J. Chun, K. Ku, S. Kim, H.I. Lee, I.S. Nam, S. Yoon, K. Kang, J. Lee (2014), Advanced hybrid supercapacitor based on a mesoporous niobium pentoxide/carbon as highperformance anode, ACS Nano, 8(9), 8968, DOI 10.1021/nn501972w MMSE Journal. Open Access www.mmse.xyz

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[15] Z. Jian, X. Lu, Z. Fang, Y.S. Hu, J. Zhou, W. Chen, L. Chen (2011), LiNb3O8 as a novel anode material for lithium-ion batteries, Electrochem Commun, 13(10), 1127, DOI 10.1016/j.elecom.2011.07.018.

[16] X. Wu, J. Miao, W. Han, Y.S. Hu, D. Chen, J.S. Lee, J. Kim, L. Chen (2012), Investigation on Ti2Nb10O29 anode material for lithium-ion batteries, Electrochem Commun, 25, 39, DOI 10.1016/j.elecom.2012.09.015.

[17] C. Jo, Y. Kim, J. Hwang, J. Shim, J. Chun, J. Lee (2014), Block copolymer directed ordered mesostructured TiNb2O7 multimtallic oxide constructed of nanocrystals as high power Li-ion battery anodes, Chem Mater, 26(11), 3508, DOI 10.1021/cm501011d.

[18] J.T. Han, D.Q. Liu, S.H. Song, Y. Kim, J.B. Goodenough (2009), Lithium ion intercalation performance of niobium oxides: KNb5O13 and K6Nb10.8O30, Chem Mater, 21(20), 4753, DOI 10.1021/cm9024149.

[19] I. Pinus, M. Catti, R. Ruffo, M.M. Salamone, C.M. Mari (2014), Neutron diffraction and electrochemical study of FeNb11O29/Li11FeNb11O29 for lithium battery anode applications, Chem Mater, 26(6), 2203, DOI 10.1021/cm500442j.

[20] X. Gao, C.A.J. Fisher, Y.H. Ikuhara, Y. Fujiwara, S. Kobayashi, H. Moriwake, A. Kuwabara, K. Hoshikawa, K. Kohama, H. Iba, Y. Ikuhara (2015), Cation ordering in a-site-deficient Li-ion conducting perovskites La(1-x)/3LixNbO3, J Mater Chem A, 3(7), 3351, DOI 10.1039/C4TA07040B. [21] J.T. Han, M.V. Reddy, S. Madhavi, G.V. Subba Rao, B.V.R. Chowdari (2006), Metal oxyfluorides TiOF2 and NbO2F as anodes for Li-ion batteries, Journal of Power Sources, 162, 1312– 1321, DOI 10.1016/j.jpowsour.2006.08.020.

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The Structural and Electrical Properties of Nano Sized Zn and Mn Ferrites by Sol-Gel Method 1

R. Kishore Kumar1, C.S. Naveen1, V. Mowlika2, R. Robert2, A.R. Phani1 1 – Innovative Nano & Micro Technologies Private Limited, T.M Industrial Estate, Mysore Road, Bengaluru, Karnataka, India 2 – Dept. of Physics, Govt. Arts College (Men), Krishnagiri, Tamil Nadu, India DOI 10.2412/mmse.75.21.462 provided by Seo4U.link

Keywords: ferrites, sol-gel, XRD, nonohomic.

ABSTRACT. Mn and Zn ferrites belong to the group of soft ferrite materials characterized by high magnetic permeability, low power loses and used as electro ceramic materials in transformers, sensors, choke coils, magnetic recording heads, noise filters, information storage systems, medical diagnostic devices and biomedical devices. The Mn and Zn ferrites can be prepared by various methods such as ceramic method, co-precipitation, sol–gel, hydrothermal etc.

In present work, ferrite Nano particles prepared by cost effective sol gel method. X-Ray Diffraction analysis (XRD) used to identify the phase formation of Zn and Mn ferrites and its crystal system. The particle size and elemental analysis revealed through scanning electron microscopy (SEM – EDAX) assisted with Energy Dispersive X – Ray images.

Electrical properties were carried out using Keithley Measurement unit.

Introduction. In recent years researchers are focused on spinel ferrites due to their useful applications in information storage systems, sensors, actuators, magnetic fluid, microwave absorbers and medical diagnostics. Thus much attention has been focused on the preparation and characterization of spinel ferrites [1-2]. With the rapid development of industry, advanced properties of Mn–Zn ferrites such as high permeability and low loss are required in response to the progress of electronic equipment towards miniaturization, lightweight and multifunction [3]. Spinel is the name of naturally occurring mineral with chemical formula MgAl2O4. Spinels have face cantered cubic crystal structure with space group Fd3mOk [4-8].

In this work, we synthesize Zinc and Manganese ferrites by using Sol Gel technique and to investigate their structural, electrical and morphological properties.

Experimental details.

Preparation of Zn and Mn ferrites. The Zinc and Manganese ferrites were prepared using solgel method. AR grade chemicals such as manganese acetate MnC6H9O6.(H2O)2, zinc nitrate (Zn(NO3)2), nickel nitrate (Ni(NO3)2), ferrite nitrate (Fe(NO3)3) and citric acid (C6H8O7) were used for the synthesis. The synthesized powder is sintered at 600° C for 12 hours and then for further investigations of structural, electrical and morphological properties.

Characterization techniques. The synthesized Zinc (Zn) and Manganese (Mn) spinel ferrites were characterized by standard techniques such as X-ray diffraction (XRD), scanning electron microscope (SEM) and I-V measurement.

Results and discussion.

Phase identification. The X-ray diffraction pattern of the zinc ferrite is shown in figure 1. The X-ray diffraction pattern of the Manganese ferrite is shown in figure 2. The XRD patterns show the

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reflections belonging to cubic spinel structure with space group Fm3m and no extra peaks have been observed in the XRD patterns.

Fig. 1. XRD pattern of Zinc Ferrite at sintering temperature of 600◦C.

Fig. 2. XRD pattern of Manganese Ferrite at sintering temperature of 600◦C. Microstructure. The properties of ferrites are dependent on their microstructures aspects like porosity and grain size. The surface morphology of the Zn and Mn ferrites has been studied by scanning electron microscopy (SEM). Figure 3 shows SEM micrographs of Zinc ferrite and Manganese ferrite. Both the samples have very good morphology and uniformly distributed with the particles size in the range of 30 – 60 nm.

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(a)

(b)

Fig. 3. Surface Morphology of a) Zn Ferrite, b) Mn Ferrite using Scanning Electron Microscopy.

I-V Characteristics. Figure 4 (a) and 4 (b) shows DC I-V characteristics of Zinc and Manganese ferrite. Both the graphs shows non-linear or nonohomic behaviour of Zinc and Manganese ferrites.

This gives a possibility for space charge limited conduction (SCLC).

(a)

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Fig. 4. (a). DC I-V characteristics of Zn Ferrite, (b). DC I-V characteristics of Mn Ferrite.

Summary. The Zn and Mn ferrites with particle size of 30-60nm were successfully synthesized using sol-gel technique. This method provides simple, fast, and low temperature syntheses and thus formed Nano-size particles of powders. X-ray diffraction patterns showed that both the samples Zinc and Manganese ferrites have simple cubic spinel phase. The morphology of the prepared samples was shown uniform nanostructured grains. The non- linear trend in I-V measurements confirms that the behavior of these samples is nonohmic. This gives a possibility for space charge limited conduction (SCLC). Results indicate that these ferrites can be used for microwave applications.

References [1] U. Konig (1974), Substitutions in manganese zinc ferrites, Applied Physics, 4 (3), 237, DOI 10.1007/BF00884234 [2] A.B. Gadkari, T.J. Shinde, P.N. Vasambekar (2009), Structural analysis of Y3+-doped Mg–Cd ferrites prepared by oxalate co-precipitation method, Mater. Chem. Phys., 114(2-3), 505-510, DOI 10.1016/j.matchemphys.2008.11.011.

[3] K. Q. Jiang, K. K. Li, C. H. Peng, and Y. Zhu (2012), Effect of multi-additives on the microstructure and magnetic properties of high permeability Mn–Zn ferrite, J. Alloys Compd., 541, 472–476, DOI 10.1016/j.jallcom.2012.06.113.

[4] K. Praveena, K. Sadhana, S. Bharadwaj, S.R. Murthy (2010), Development of nanocrystalline Mn–Zn ferrites for forward type DC–DC converter for switching mode power supplies, Materials Research Innovations, 14(1), 56-61, DOI 10.1179/143307510X12599329343727.

[5] K. Praveena, K. Sadhana, S. Bharadwaj, S.R. Murthy (2009), Development of nanocrystalline Mn–Zn ferrites for high frequency transformer applications, J. Magn. Magn. Mater., 321(16), 24332437, DOI 10.1016/j.jmmm.2009.02.138.

[6] A.K. Subramani, K. Kondo, M. Tada, M. Abe, M. Yoshimura,N. Matsushita (2009), High resistive ferrite films by a solution process for electromagnetic compatible (EMC) devices, J. Magn. Magn.

Mater., 321(24), 3979-3983, DOI 10.1016/j.jmmm.2009.07.036.

[7] M. Latorre-Esteves, A. Cortes, M. Torres-Lugo, C. Rinaldi (2009), Synthesis and characterization of carboxymethyl dextran-coated Mn/Zn ferrite for biomedical applications, J. Magn. Magn. Mater., 321(19), 3061-3066, DOI 10.1016/j.jmmm.2009.05.023.

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[8] Rastislav Dosoudil, Vladimir Olah (2001), Complex Permeability Spectra Of Manganese–Zinc Ferrite And Its Composite, Journal of Electrical Engineering, 52(1-2), 24-29.

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Manifestation of Ferromagnetism in Rare Earth Doped BiFeO3 Multiferroics 1

Avinash M.1, Murlidharan M.1, Sivaji K.1, a 1 – Department of Nuclear Physics, University of Madras, Guindy Campus, Chennai, India a – k_sivaji@yahoo.com DOI 10.2412/mmse.34.79.169 provided by Seo4U.link

Keywords: rare earth doping, XRD, Raman, SEM, ferromagnetic hysteresis loop.

ABSTRACT. Polycrystalline Bi1-xNdxFe1-xMnxO3 (x=0.00-0.50) ceramic powders have been synthesized by solid-state method. The phase identification and lattice parameter were analyzed using XRD technique. Active Raman modes and the local order and disorder parameters were probed. Surface morphology of the prepared samples was analyzed by Scanning electron microscopy and the particle size was estimated. Magnetic study of the prepared sample demonstrate the antiferromagnetic to weak ferromagnetic behaviour. The transition from antiferromagnetic to weak ferromagnetic nature can be understood interms of exchange interactions. Magnetic hysteresis loops were observed in the materials with increasing magnetization as rare Earth substitution increases. From the present investigation, it was observed that the co doping of Nd and Mn in BiFeO3 results in a new class of multiferroic material for the fabrication of optoelectronic devices.

Introduction. Multiferroics are a class of materials exhibiting more than one ferroic or anti-ferroic behaviour in single phase. Among these, magnetoelectric compounds are materials possessing both ferroelectric and ferromagnetic properties. Employment of external electric and magnetic field can induce magnetization and intrinsic polarization in these magnetoelectronic compounds. Due to their enriched physical properties of magnetoelectric compounds, coupling between them makes for both industrial application and Physics point of view [1-2]. Bismuth Ferrite is an important multiferroic material crystallizing in distorted perovskite structure. BiFeO3 exhibits G-type antiferromagnetic ordering much below Neel temperature, TN= 370 ֯C and ferroelectricity below TC= 830 ֯C [3-4].

Due to the spiral spin structure, BFO shows low magnetization when in bulk form [5]. One of the prime drawbacks of BiFeO3 based perovskite materials is the formation of impurity phases during preparation.

Impurity phases like Bi2Be4O9 with rich Iron content often seem to evolve along pure perovskite phase due to the loss of bismuth during the synthesis of BFO in bulk form. For its real use in industrial application, these drawbacks seem to restrict this material. By preparing nano sized materials and doping them on both Bi and Fe sites, may overcome the drawbacks partially or fully. By doping 3+ rare Earth atoms like (La, Nd, Y etc) and 2+ alkaline Earth atoms such as Cr, Mn etc, in BiFeO3 ceramic materials show enhanced single phase magnetic properties[6] Hence, in the present work, synthesis of Nd and Mn co doped BiFeO3 ceramics using ball mill assisted solid state reaction method was investigated. The crystal structure was studied using X-ray diffraction (XRD). Shape and size of the prepared samples was examined using Scanning electron microscopy.

Raman modes were identified using Raman spectroscopy and the magnetic studies reveal the anti ferro magnetic to weak ferromagnetic transition was occurred when the Mn concentration increases.

Experimental Procedure. Bi0.75Nd0.25Fe0.75Mn0.25 and Bi0.75Nd0.25Fe0.5Mn0.5 ceramics were synthesised by ball mill assisted solid state method. Bi2O3 and Fe2O3 powders (Purity ≥ 99.0%) were weighed in 1.1:1 molar ratio to compensate the loss of Bi during the sintering process. The ceramic powders were ball milled for 24h using alcohol as a medium. The ball milled sample was then dried © 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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at 400 ÖŻC for 5h and sintered at 830 ÖŻC for 3h. The sintered powders were then pressed into a disk and subjected to various characterizations.

Sample Characterization. The phase identification of the material was examined using a Rigaku Multiplex X-ray diffractometer with radiations of KÎą (1.5406 â&#x201E;Ť) over the angular range of 2θ (20ÖŻ80ÖŻ). The scanning rate was 2ÖŻ per minute at room temperature working at 40KV voltage and 40mA current. Micro-Raman spectra were measured using a Nanoscale Model X-per Ram 200 Raman spectrometer equipped with a green laser of Îť= 532 nm. The grain morphologies were characterized using a Hitachi S-3400N Scanning electron microscope (SEM). The average grain sizes were calculated by counting the number of grains intercepted by several straight lines sufficiently long to include most of the grains on the SEM photomicrograph. The magnetization studies were carried out using a lakeshore (7410) Vibrating sample magnetometer.

Results and Discussion: Phase Analysis. Fig 1 shows the X-ray diffraction pattern of Nd and Mn co-doped BiFeO3 ceramics.

Fig. 1. X-ray diffraction data of Bi1-xNdxFe1-xMnxO3 (x=0.00-0.50) ceramics.

From the XRD pattern, it is inferred that prepared samples exhibit rombohedral structure with a space group of R3C. Comparison with JCPDS standard data (card number 742016) supported the formation of rombohedral structure. The structural stability was examined using Goldschmidt tolerance factor (t), đ?&#x2018;Ą = (< đ?&#x2018;&#x;đ??´ + đ?&#x2018;&#x;0 )/â&#x2C6;&#x161;2(< đ?&#x2018;&#x;đ??ľ + đ?&#x2018;&#x;0 )

(1)

Where <rA> and <rB> are the average radius of A and B site cations and r0 is the ionic radius of Oxygen. The calculated value was around 0.84 which infers comprehensive strain acting on Fe-O bonds and Bi-O bonds. The oxygen octahedral must buckle in order to fit a bigger cation into a smaller space for minimum lattice strain [7]. For a rombohedral unit cell, the lattice parameter is given by đ?&#x2018;&#x17D;đ?&#x2018;&#x2026; = đ??ľđ?&#x2018;&#x2018;(â&#x201E;&#x17D;đ?&#x2018;&#x2DC;đ?&#x2018;&#x2122;) [đ?&#x2018; đ?&#x2018;&#x2013;đ?&#x2018;&#x203A;2 â&#x2C6;? (â&#x201E;&#x17D; + đ?&#x2018;&#x2DC; + đ?&#x2018;&#x2122;) + 2(đ?&#x2018;&#x2DC;â&#x201E;&#x17D; + đ?&#x2018;&#x2DC;đ?&#x2018;&#x2122; + đ?&#x2018;&#x2122;â&#x201E;&#x17D;)(đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018; 2 â&#x2C6;? â&#x2C6;&#x2019;đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018; â&#x2C6;?)]1/2 MMSE Journal. Open Access www.mmse.xyz

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(2)

Mechanics, Materials Science & Engineering, Vol. 14 2018 â&#x20AC;&#x201C; ISSN 2412-5954

Where, đ??ľ = [1 â&#x2C6;&#x2019; 3đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018; 2 â&#x2C6;? +2đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018; 3 â&#x2C6;?]â&#x2C6;&#x2019;1/2

(3)

The average crystallite size and strain induced by the dopant were calculated by Williamson Hall plot and the estimated equation is given [8] đ?&#x203A;˝(â&#x201E;&#x17D;đ?&#x2018;&#x2DC;đ?&#x2018;&#x2122;) đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018; đ?&#x153;&#x192;(â&#x201E;&#x17D;đ?&#x2018;&#x2DC;đ?&#x2018;&#x2122;) =

đ??žđ?&#x153;&#x2020; đ??ˇ

+ 4đ?&#x153;&#x20AC;đ?&#x2018; đ?&#x2018;&#x2013;đ?&#x2018;&#x203A;đ?&#x153;&#x192;(â&#x201E;&#x17D;đ?&#x2018;&#x2DC;đ?&#x2018;&#x2122;)

(4)

Where D is the crystallite size in nano meters, K is the shape factor (0.9), Îť is the wavelength of CuKÎą (1.5406â&#x201E;Ť), β is the Full Width Half Maximum (FWHM) of peak intensity, θ is the peak position (Bragg angle) and Ξ is the micro strain. The Williamson Hall plot of Nd and Mn co doped BiFeO3 are shown in Fig 2(a) and 2(b).

(a)

Fig. 2. (a) Williamson Hall Plot of Bi0.75Nd0.25Fe0.75Mn0.25Ceramics (b) Williamson Hall plot of Bi0.75Nd0.25Fe0.5Mn0.5ceramics MMSE Journal. Open Access www.mmse.xyz

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It is found that BFO reveals tensile strain in nature and may be attributed to the incorporation of Nd and Mn ions into Bi-Fe-O lattice. The calculated average crystallite size and strain shown in table 1 proves the inverse proportionality of strain and crystallite size.

Table 1. Calculated Crystallite size and Strain values of Nd & Mn co doped BFO ceramics.

Sample

Average crystallite size (nm)

Strain (10-3)

Bi0.75Nd0.25Fe0.75Mn0.25

46

2.2

Bi0.75Nd0.25Fe0.5Mn0.5

63

1.3

Raman studies. Raman active and inactive modes of Bi0.75Nd0.25Fe0.75Mn0.25 and Bi0.75Nd0.25Fe0.5Mn0.5 and the degree of order-disorder structural parameters were analysed. Raman spectra of Nd & Mn co doped BFO ceramics were shown in figure 3.

Fig. 3. Raman Spectra of Bi1-xNdxFe1-xMnxO3 (x=0.00-0.50) ceramics.

BFO is a well-known classic rombohedral antiferrogmatic material belonging to R3C space group.

Group theory leads to two formula units (Z=2) and has 13 Raman active modes i.e, 4A1+9E [9-11].

Four major modes appear below 250 cm-1. E (1) mode appears at ~60-80cm-1, E(2) at ~130-140cm-1.

A1(1) at ~160-170cm-1, A1(2) at ~210-220cm-1. Vibrational frequencies corresponding to Bi, Fe and O atoms mainly appear below 170cm-1 and above 260cm-1 [9]. The Fe atom motion can be associated with the vibrational frequencies of A1(1) and A1(2) modes and are sensitive to vibrations of Fe-O-Fe bonds.

The Bi atom motion can be associated with the vibrational frequencies of E(1) and E(2).

The coupling between Fe 3d spin and phonon are sensitive to A1 and E modes [9]. The deviation in presence of active Raman modes can be associated with preparation techniques, average crystallite size and degree of order-disorder structural parameters [12-13]. Thus, the Raman spectra confirm the existence local structural disorder present in the co-doped BFO ceramics.

Surface Morphology Analysis. The surface morphology of rare Earth (Nd, Mn) doped BFO compounds were shown in Fig 4 (a) and 4 (b)

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(a)

Fig. 4. (a) SEM grain morphologies of Bi0.75Nd0.25Fe0.75Mn0.25 ceramics, (b) SEM grain morphologies of Bi0.75Nd0.25Fe0.5Mn05 ceramics.

From the SEM micrograph, it is seen that the particles possess brick like shape this may be due to high surface energy particles reduce their surface energy by growing in to larger particles. In general, it is well known that the size and shape of particles depend on crystal structure of precursor and synthesis condition, pH and sintering temperature [14]. From the intercept method, the particle size was found to be 2.2μm and 3.1μm which infers a transformation in size of particles due to increase in dopant concentration [15].

Magnetic Studies. The field dependent magnetization behaviour of rare Earth doped BFO compounds at room temperature was shown in Fig 5.

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(a)

Fig. 5. (a) Magnetization studies of Bi0.75Nd0.25Fe0.75Mn0.25 ceramics, (b) Magnetization studies of Bi0.75Nd0.25Fe0.5Mn0.5 ceramics.

It has been reported earlier that pure BFO exhibits linear antiferromagnetic nature [16]. From the first principle calculations, one can infer that, in oxygen abundant sintering condition, a ferromagnetic magnetization may be developed [17]. From the present study it, is evident that Nd and Mn co-doped BFO compounds exhibit anti ferro to weak ferromagnetic transition.as the content of Mn increases there could be possible exchange interactions between the dopants and host lattice which results in magnetic phase transitions. Further, effect of dopant suppress the spiral order can be the reason for weak ferromagnetism in co- doped BFO ceramics. The canting of antiferromagnetic spin structure is indicated by the existence small remnant magnetization and unsaturated hysteresis loops, which may be due to the unique magnetic behaviour of induced Nd and Mn compared to that of Fe ions. Hence, the magnetisation study confirms the inducement of ferromagnetism in rare Earth doped BiFeO 3 compounds.

Summary. The structural and magnetic properties of Co-doped BFO ceramics were examined. The Nd and Mn doped BiFeO3 ceramics with average crystallite size of about 45 nm have been prepared MMSE Journal. Open Access www.mmse.xyz

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by ball mill assisted solid state reaction method. X-ray diffraction pattern reveal the rombohedral structure and the calculated the strain value indicate that prepared compounds are in tensile nature.

Presence of active Raman modes confirms the existence of local structural orders in the prepared ceramics. Magnetic studies indicate inducement of weak ferromagnetism as doping concentration increases. Hence, from the present study, it is evident that BiFeO3 might be a promising candidate for Spintronic and Optoeletronic applications.

Acknowledgement. The authors would like to thank Graduate Institute of Applied Science and Engineering, Fu Jen Catholic University, Taiwan, ROC for their support in XRD, SEM and Raman characterizations.

References [1] Fiebig, M. (2005), Revival of the magnetoelectric effect, J. Phys. D: Appl. Phys., 38(8), R123, DOI: 10.1088/0022-3727/38/8/R01.

[2] VanAken, B. B.; Rivera, J. –P.; Schmid, H.; Fiebig, M. (2007), Observation of ferrotoroidic domains, Nature, 449, 702, DOI: 10.1038/nature0613.

[3] Fischer, P.; Polomska, M.; Sosnowska, I.; Szymanksi (1980), Temperature dependence of the crystal and magnetic structures of BiFeO3, M. J. Phys. C: Condens. Matter, 13(10), 1931, DOI: 10.1088/0022-3719/13/10/012 [4] Tabares-Munoz, C.; Rivera, J. P.; Monnier, A.; Schmid, H. (1985), Measurement of the Quadratic Magnetoelectric Effect on Single Crystalline BiFeO3, Jpn. J. Appl. Phys., 24, 1051, DOI: 10.7567/JJAPS.24S2.1051.

[5] Sosnowska, I.; Peterlin-Neumaier, T.; Steichele (1982), Spiral magnetic ordering in bismuth ferrite, E. J. Phys. C: Condens. Matter, 15(23), 4835, DOI: 10.1088/0022-3719/15/23/020.

[6] Maître, A.; François, M.; Gachon, J. C. (2004), J. Pha. Equi. and Diff., 25(1), 59-67, DOI: 10.1007/s11669-004-0171-0.

[7] P.Kumar, M. Kar (2014), Tuning of net magnetic moment in BiFeO3 multiferroics by co-substitution of Nd and Mn, Physica B, 448, 90–95, DOI: 10.1016/j.physb.2014.03.080.

[8] M. Muralidharan, V. Anbarasu, A. Elaya Perumal, K. Sivakumar (2014), Carrier induced ferromagnetism in Yb doped SrTiO3 perovskite system, J. Mater. Sci. Mater. Electron., 25(9), 4078– 4087, DOI: 10.1007/s10854-014-2132-7.

[9] Hermet P, Gofinet M, Kreisel J et al (2007), Raman and infrared spectra of multiferroic bismuth ferrite from first principles. Phys Rev B, 75(22), 220102, DOI: 10.1103/PhysRevB.75.220102.

[10] Hlinka J, Pokorny J, Karimi S et al (2011), Angular dispersion of oblique phonon modes in BiFeO3 from micro-Raman scattering. Phys Rev B, 83(2), 020101, DOI: 10.1103/PhysRevB.83.020101.

[11] Bielecki J, Svedlindh P, Tibebu DT et al (2012), Structural and magnetic properties of isovalently substituted Multiferroic BiFeO3: insights from Raman spectroscopy. Phys Rev B, 86(18), 184422, DOI: 10.1103/PhysRevB.86.184422.

[12] Fiebig, M. (2005), Revival of the magnetoelectric effect, J. Phys. D: Appl. Phys., 38(8), R123, DOI: 10.1088/0022-3727/38/8/R01.

[13] D. Chen, K. Tang, F. Li, H. Zheng (2006), A Simple Aqueous Mineralization Process to Synthesize Tetragonal Molybdate Microcrystallites, Cryst. Growth Des., 6(1), 247-252, DOI: 10.1021/cg0503189.

[14] Niu, P. Yang, W. Wang, F. He, S. Gai, D. Wang, J. Lin (2011), Solvothermal synthesis of SrMoO4:Ln (Ln = Eu3+, Tb3+, Dy3+) nanoparticles and its photoluminescence properties at room temperature, Mater. Res. Bull., 46(3), 333-339, DOI: 10.1016/j.materresbull.2010.12.016.

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[15] P. Yang, C. Li, W. Wang, Z. Quanb, S. Gai, J. Lin (2009), Uniform AMoO4:Ln (A=Sr2+, Ba2+; Ln=Eu3+, Tb3+) submicron particles: Solvothermal synthesis and luminescent properties, J. Solid State Chem., 182(9), 2510–2520, DOI: 10.1016/j.jssc.2009.07.009.

[16] Yi Ting, Chi-Shun Tu et al (2017), Magnetization, phonon, and X-ray edge absorption in bariumdoped BiFeO3 ceramics, J Mater Sci, 52(1), 581–594, DOI: 10.1007/s10853-016-0355-0.

[17] Paudel TR, Jaswal SS, Tsymbal EY (2012), Intrinsic defects in multiferroic BiFeO3 and their effect on magnetism. Phys Rev B, 85(10), 104409, DOI: 10.1103/PhysRevB.85.104409.

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Crystallization of Alpha- Lactose Monohydrate (α-LM) from Aqueous Solution through Gas-Phase Diffusion and Anti-Solvent Crystallization Methods 1

K. Vinodhini1, K. Srinivasan1,a 1 – Crystal Growth Laboratory, Department of Physics, School of Physical Sciences, Bharathiar University, Coimbatore, Tamil Nadu, India a – nivas_5@yahoo.com DOI 10.2412/mmse.20.93.441 provided by Seo4U.link

Keywords: nucleation, anti-solvent, morphology, X-ray diffraction, differential scanning calorimetry.

ABSTRACT. Alpha-lactose monohydrate (α-LM) is an important disaccharide and is widely used as a carrier in dry powder inhaler (DPI) and also used as a main ingredient in most of the dairy products. The quality, shelf-life and biopharmaceutical performance of the DPI and dairy products depends on the size, size distribution and morphology of αLM. Crystallization of α-LM is an important purification step in refining lactose from whey solutions. Nucleation of αLM occurred only after a very long time ~134 h and this is a major drawback leading to the uneven distribution and growth of larger crystals. To overcome these problems, we employed two different techniques, (i) gas-phase diffusion and (ii) anti-solvent crystallization to reduce the nucleation time and to control the size and morphology of α-LM. The aqueous solution of α-LM was mixed with different volumes of organic solvents like, DMSO and ethanol. The different levels of supersaturation generated through gas-phase diffusion and anti-solvent crystallization leads variation in the nucleation time, size and morphology of the crystals. The crystals grown by these two methods were analyzed by optical microscope and by PXRD and DSC. By employing gas-phase diffusion crystallization process we could able to crystallize α-LM crystals within shorter induction time when compared to conventional crystallization method and also α-LM crystals with high purity when compared to anti-solvent crystallization method.

Introduction. Industrially, lactose is extracted from whey of cow’s milk by a crystallization process. Alpha-lactose (α-L) and beta-lactose (β-L) are the two isomeric forms of lactose. α-L crystallizes as a monohydrate (α-LM) and β-L crystallizes as an anhydride form below and above the temperature of 93.5°C, respectively [1]. Nucleation of α-LM occurred only after a very long time ~134 h and this is a major drawback leading to the uneven distribution and growth of larger crystals [2]. In the pharmaceutical products, the size and shape of α-LM crystals are important because a small change in this attributes highly which affect physical properties such as powder flow, blending, mixing, compaction, caking and drug delivery efficiency [3]. In food products, the α-LM crystals require the size of ˃100 µm with narrow crystal size distribution (CSD). In this regard, the definite control of the physicochemical properties of α-LM is highly essential to engineer the α-LM products with desired quality. To achieve this task, we employed two different techniques (i) gas-phase diffusion and (ii) anti-solvent crystallization method.

Experimental Procedure.

Preparation of saturated α-LM solution. Saturated solution of α-LM in water was prepared in an airtight round bottomed flask (RBF) fitted by PTFE stirrer shaft with ground sleeved stirring gland attachment. At 33°C, the solution was stirred for about 9 hrs with continuous stirring. After saturation, the solution was filtered using Whatmann No.41filter sheets into another similar RBF. Experimental setup for anti-solvent crystallization. The saturated solution was split up into capacities of 10 mL each into 10 test tubes. Ethanol (polar protic solvent) was added as an antisolvent into the solutions with different concentration from 5% to 85 % v/v in the steps of 20% © 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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whereas, DMSO (polar aprotic solvent) was added as an anti-solvent with different concentration from 5 to 85% v/v in the steps of 20% into the rest of the test tubes that containing solution and then the test tubes were tightly covered. The experimental solutions were kept at room temperature (33 °C) for growth.

Experimental setup for gas-phase diffusion crystallization. After saturation of α-LM from aqueous solution, 10 ml solution was taken in 30 ml test tube and it was placed in a large test tube (38 mm OD x 200 mm length) filled with 30 mL organic solvents (ethanol or DMSO). The system was ultimately capped and left for growth at room temperature (33 °C).

The solutions prepared from these both methods were carefully monitored for the occurrence of nucleation event and left undisturbed to the growth of nucleated crystals. The induction time, size and shape of the nucleated crystals were monitored. Finally, the grown crystals were subjected to PXRD and DSC analyses.

Results and discussion.

Anti-solvent crystallization method. When adding the organic solvents such as ethanol or DMSO into water, the solubility of α-LM is reduced [4, 5]. Hence, in the present work anti-solvent crystallization of lactose has been carried out using organic solvents such as ethanol and DMSO as an anti-solvent. The induction time of α-LM was reduced significantly with increasing ethanol concentration as shown in Fig. 1.

Fig. 1. Microscopic image of nucleated α-LM crystals at different ethanol concentrations from 585% v/v.

While increasing the concentration of ethanol from 5% to 85% v/v, number of α-LM crystals with tomahawk morphology was found decreased and number of α-LM crystals with needle like morphology was found increased. Nucleated crystals were subjected to PXRD and DSC analyses.

The characteristic 2Ѳ peak at 20° was observed at lower anti-solvent concentrations (5-45%v/v). It is the characteristic PXRD peak of α-LM. The primary characteristic PXRD peak of β-L was observed at 10.5° 2Ѳ and it became more prominent at higher anti-solvent concentrations (6585%v/v). The recorded DSC thermograms show a clear endothermic peak at 145-155°C corresponding to the removal of water from the α-LM crystals and another endothermic peak observed at 200-217 °C shows melting point of α-LM crystals. Hence, it was confirmed that α-LM crystals dominantly nucleate at lower anti-solvent crystallization (5-45%v/v). The peak observed at

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225-235 °C is the melting endotherm of β-L crystals. Hence, it was confirmed that β-L crystals dominantly nucleate at higher anti-solvent concentration (65-85%v/v).

Fig. 2. PXRD pattern of lactose crystals grown at different anti-solvent concentrations (5-85%v/v).

Fig. 3. DSC thermogram of lactose crystals grown at different anti-solvent concentrations (585%v/v).

From the above results, it is confirmed that the different pseudo-polymorphic forms of lactose formed while using different concentration of ethanol. When ethanol concentration is in the range of 5% to 45% v/v, the nucleation of α-LM becomes dominant, when ethanol concentration is in the range of 65% to 85% v/v, nucleation of α-LM is decreased and the nucleation of β-L becomes dominant as shown in Fig. 2 - 3.

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While adding 10-85% v/v of DMSO, the desired result was not found on induction time of α-LM since there is no nucleation observed up to 7 days. Hence, DMSO was not found suitable as an antisolvent to grow α-LM crystals within a shorter induction time.

Gas-phase diffusion crystallization method. To observe the effect of atmospheric gas in crystallization of α-LM, DMSO and ethanol were chosen as the ambient atmospheric environment as shown in Fig. 4.

Fig. 4. Gas-phase diffusion crystallization method using (a) DMSO, (b) ethanol as an atmospheric environment.

A single crystal with tomahawk morphology formed since the organic solvents such as DMSO and ethanol diffused into the aqueous α-LM solution at room temperature as shown in Fig. 5 - 6.

Fig. 5. Microscopic image of nucleated α-LM crystals in aqueous solution through gas-phase diffusion of (a) DMSO and (b) ethanol.

When α-LM aqueous solution was adapted to anti-solvent crystallization method using DMSO, the induction time was long whereas, when α-LM aqueous solution was adopted to gas-phase diffusion crystallization method using DMSO, induction time was found reduced. The reason behind this reduction is not only depend on diffusion of DMSO but also hygroscopic nature of DMSO. When experimental solution was adapted to growth in this method, DMSO solvent absorbed water from the aqueous solution and hence solution volume slightly decreased and DMSO volume slightly increased with time. As the volume of the water from aqueous solution was decreased as well as diffusion of DMSO was increased with time, the induction time of α-LM was reduced when compared to anti-solvent crystallization method.

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Fig. 6.Growth progression of α-LM crystals from aqueous solution through gas-phase diffusion of (a) DMSO and (b) ethanol.

The nucleated crystals were allowed to grow further within the solution. Finally the grown crystals were carefully harvested and subjected to PXRD and DSC analyses. The PXRD and DSC analyses revealed (Fig. 7 - 8) that the grown crystals are pure α-LM and no incorporation of β-L was present in the crystal lattice of α-LM.

Fig. 7. PXRD pattern of α-LM crystals grown from aqueous solution through gas-phase diffusion of (a) DMSO and (b) ethanol.

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Fig. 8. DSC thermogram of α-LM crystals grown from aqueous solution through gas-phase diffusion of (a) DMSO and (b) ethanol.

Summary. The concentration of ethanol as an anti-solvent plays a vital role in controlling the induction time, type of nucleation and morphology of the nucleated crystals. Lower anti-solvent concentration is more favourable for the crystallization of α-LM crystals with shorter induction time and narrow crystal size distribution (CSD). Higher anti-solvent concentration produces unstable crystals hence it is not favourable for the growth of stable α-LM crystals. While adding different concentration of DMSO as an anti-solvent, induction time of α-LM was very long, hence it is not suitable for growth of α-LM. By employing gas-phase diffusion crystallization process we could able to crystallize α-LM crystals within shorter induction time when compared to conventional crystallization method and also the α-LM crystals harvested were having with high purity when compared to the anti-solvent crystallization method.

References [1] H. D. Belitz, W. Grosch, P. Schieberle (2009), Food Chemistry, 498-528.

[2] P. Parimaladevi, K. Srinivasan (2014), Influence of supersaturation level on the morphology of α-lactose monohydrate crystals, Int. Dairy. J., 39(2), 301-311, DOI 10.1016/j.idairyj.2014.08.007.

[3] S.Y. Wong, R. W. Hartel (2014), Crystallization in Lactose Refining—A Review, J. Food. Sci., 79(3), R257-272, DOI 10.1111/1750-3841.12349.

[4] F. Majd, T. A. Nickerson (1976), Effect of Alcohols on Lactose Solubility, J. Dairy Sci., 59(6), 1025-1032, DOI 10.3168/jds.S0022-0302(76)84319-6.

[5] K. Vinodhini, K. Srinivasan (2015), The role of a mixture of DMSO : water in the crystallization of α-lactose monohydrate (α-LM) single crystals with desired morphology, Cry.Eng.Comm, 17(33), 6376-6383, DOI 10.1039/C5CE00001G.

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Synthesis, Characterisation and Heat Transfer Analysis of TiO2 -Water Nanofluid 1

Bikash Pattanayak1,a, Abhishek Mund1,b, Jayakumar J.S.1,c, Kajal Parashar2,d, S.K.S. Parashar2,e 1 – Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, Kerala, India 2 – Nano sensor Lab, School of Applied Sciences, KIIT University, Bhubaneswar, Odisha, India a – bikash.ptnk@gmail.com b – abhishek93mund@gmail.com c – jsjayan@amrita.edu d – kparasharfch@kiit.ac.in e – sksparashar@yahoo.com DOI 10.2412/ mmse.26.53.749 provided by Seo4U.link

Keywords: LPSA, thermal conductivity, heat transfer, nanofluids.

ABSTRACT. The thermal conductivity of traditional heat transfer fluids is inherently low. Metal oxide in nano form comparatively has higher thermal conductivity than normal fluids. So it is a need to understand the fundamental behaviour of the metal oxides nanoparticles in base fluids. TiO2 nanoparticles are prepared by high energy planetary ball milling of TiO2 powders with BPR 10:1 at 300 rpm for different milling time. It was observed from LPSA that the size of the particles is in the range of 100nm-200nm. These nanoparticles are used to make nanofluids by mixing them with water at different volume fraction of solute. The nanofluids behaviour was studied in terms of viscosity, density and thermal conductivity. The volume fraction of TiO2 nanoparticle plays a very crucial role in thermal conductivity. The viscosity ratio of nanofluids increases with increase in concentration. In this study the thermal conductivity and viscosity will be discussed in details with theoretical models.

Introduction. This era has come with new horizon of technologies. We have witnessed the transformation of gigantic megabyte hard disk to micro sized memory chips. This miniaturisation technique has operation and performances in regular aspect and also has some technological challenges for thermal engineers. One of the challenges for thermal engineer is the effective cooling of device irrespective of its size. Conventionally the heat transfer can be enhanced by either increasing the surface area or by increasing the flow velocity [1]. However the study is limited to suspension of micro-macro sized particles and has following disadvantages as the particle settle down rapidly, form a layer and reduces heat transfer, clogging of the flow channel. Therefore the researchers have replaced the micro-macro sized particles with nano-sized particles. The colloidal suspension of these nano-sized particles in a base fluid is known as nanofluid [2]. In this experiment TiO2-Water nanofluids were prepared, its thermal conductivity, viscosity, specific heat was determined and the effect of it on the cooling time of hot water by using a concentric double pipe heat exchanger was analysed.

Theoretical analysis.

Titanium dioxide has three types of crystal habits which are brookite, anatase and rutile. Brookite is one kind of unstable crystal, with no industrial value, while anatase and rutile all have stable properties, which are very important white pigment. Compared with other white pigments, it is well © 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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accepted for its super whiteness, tinting strength, covering power, durability, heat resistance, chemical stability, and especially without any toxicity. Titanium dioxide is widely applied in many fields, including nanofluids preparation. Nanofluids can be prepared by two methods i.e. One step method and two step method. One step method combines the production of nanoparticles and synthesis of nanofluid in a single cycle where as in two step method the nanoparticle is prepared and then it is mixed with base fluids by magnetic stirring, ultrasonic agitation etc. This method works well for oxide nanoparticles. The main advantage of two step method is the large scale production of nanofluid with a wide variety [3]. He et al. [4] mixed TiO2 nanoparticles in the form of large agglomerates with distilled water using ultra sonication for 30 min. Then, the suspension was processed in a mediummill to reduce the agglomerated nanoparticles. The pH value was adjusted to 11 (corresponding to zeta potential of w40 mV) to prevent re-agglomeration of the milled samples. Therefore, the obtained nanofluids were found to be very stable for months. Murshed et al. [5] used ultrasonic dismembrator for 8-10 hour to ensure proper dispersion of TiO2 nanoparticles with deionized water. The size of the nanoparticles in the base fluid was found to be increased. Therefore, oleic acid and cetyltrimethyl ammonium bromide (CTAB) surfactants (0.01e0.02%) were added to ensure better stability and proper dispersion.

Experimental analysis.

In this experiment the nanoparticle was prepared by the principle of Top-Down approach using High energy planetary ball milling machine. A ball mill is a type of grinder used to grind or blend materials on the principle of impact and attrition [6]. The milling machines used in this experiment contain two vessels consisting of Tungsten Carbide balls. Whenever Tungsten Carbide balls collide, some amount of powder is trapped in between them, particles are repeatedly flattened, cold welded, fractured and re-welded inside milling machine. The TiO2 Nano powder is obtained by wet milling the raw powder at 10:1 ball to powder ratio at 300 rpm for 15 hours as shown in figure 1&2. Then the particles are characterised using laser particle size analyser and it is observed that d(0.1)=136nm, d(0.5)=176nm, d(0.9)=242nm i.e. 10% of particle size lie within 136nm, 50% of particle size lie within 176nm and less than 90% of particle size is 242nm and can be analysed in figure 3. The minimum size of the particle is 136 nm and maximum size of the particle is 242nm.Three different masses of TiO2 was taken for this experiment i.e. 0.025gram, 0.05 gram, 0.075 gram. These powders are then mixed with normal water using magnetic stirrer for 2 hours succeeded by ultrasonic agitator for 2 hours and nanofluid is obtained for the experiment.

Fig. 1. High energy ball milling machine.

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Fig. 2. Nanopowder prepared after15 hours wet milling.

Fig. 3. Laser particle size analyser graph of the nanoparticle prepared.

The stability analysis of nanofluid is the topic of concern for all the researchers because if the particles settle down during the experiment then it will offer resistance to the heat transfer and affect the experiment [3]. In this experiment there was no use of any surfactant for the stability analysis. Less volume fraction of powder was used so that it will not settle down and by magnetic stirring for 2 hours succeeded by ultrasonic agitating for two hours the stability for our prepared fluid is observed to be more than a day (24 hours) and was good for conducting the experiment as shown in figure 4 & 5.

Fig. 4. Nanofluid prepared by adding different volume fraction of nanopowder in water.

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Fig. 5. Stability of nanofluid after 24 hours.

Results and Discussions. a) Density measurement of nanofluid:- Theoretically the density of the nanofluid is measured by using Pak & Choi model [7]. From the data book the values of density of titanium dioxide and water are Ď TiO2 = 4010 Kg/m3, Ď = 1000 Kg/m3 respectively [9]. Ď nf = đ?&#x153;&#x2018;đ?&#x153;&#x152;đ?&#x2018;&#x2021;đ?&#x2018;&#x2013;đ?&#x2018;&#x201A;2 + (1 â&#x2C6;&#x2019; đ?&#x153;&#x2018;)đ?&#x153;&#x152;

1)

where Ď nf â&#x20AC;&#x201C; density of nanofluid; đ?&#x153;&#x2018; â&#x20AC;&#x201C; volume concentration of nanopowder; Ď TiO2 â&#x20AC;&#x201C; density of titanium dioxide; Ď â&#x20AC;&#x201C; density of water.

Experimentally the density was measured by weighing an empty graduated cylinder then by filling the cylinder with nanofluid, and recording the volume. The full graduated cylinder was weighed and the mass of the empty cylinder was subtracted to obtain the net mass of the nanofluid and the density of the fluid is the mass over the volume. The data obtained and error analysis is tabulated in table1.

Table 1. Theoretical, Experimental and error analysis for density of nanofluid at different concentration.

Volume concentration (Ď&#x2020; %)

Density (model) kg/m3

Density(experimental) kg/m3

Error (%)

0.0006

1001.806

995.76

0.608

0.00125

1003.76

999.98

0.376

0.00187

1005.628

1004.26

0.136

b) Thermal conductivity measurement of Nanofluid:- Thermal conductivity is the property of a material to conduct heat [8]. The value of thermal conductivity of the powder and nanofluid are Kwater = 0.6280 W/mk, KTiO2 = 8.3 W/mk [9]. In this experiment thermal conductivity is measured by using three different models i.e. (i) Wasp 1977 model, (ii) Maxwell model and (iii) Bruggeman model MMSE Journal. Open Access www.mmse.xyz

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Hui et.al.[10-13]. The mathematical expressions for the models are listed below and the data are tabulated in table 2. (i) Knf = KW[(KP+2KW-2 Ď&#x2020;(KW-KP))/ (KP+2KW+Ď&#x2020;(KW-KP))]

(2)

(ii) Knf = KW [(KP+2KW+2 Ď&#x2020;(KW-KP))/ (KP+2KW-Ď&#x2020;(KW-KP))]

(3)

(iii) Knf =0.25[(3 Ď&#x2020;-1)KP+(2-3 Ď&#x2020;)-KW]+0.25KWâ&#x2C6;&#x161;â&#x2C6;&#x2020;, â&#x2C6;&#x2020;= (3 Ď&#x2020;-1)2(KP/KW)2+(2-3 Ď&#x2020;)2+2(2+9 Ď&#x2020;-9 Ď&#x2020;2)(KP/KW)

(4)

where Knf â&#x20AC;&#x201C; thermal conductivity of nanofluid; KW â&#x20AC;&#x201C; Thermal conductivity of water; KP â&#x20AC;&#x201C; Thermal conductivity of powder; đ?&#x153;&#x2018; â&#x20AC;&#x201C; volume concentration of nanopowder.

Table 2. Thermal conductivity of TiO2-Water nanofluid based on different models.

Volume concentration (Ď&#x2020; %)

Wasp 1977 model W/mk

Maxwell model W/mk

Bruggeman model Hui et.al W/mk

0.0006

1.00144

0.9985

0.6574

0.00125

1.003

0.9969

0.6585

0.00187

1.0045

0.9955

0.6593

c) Viscosity measurement of nanofluid: The viscosity of a fluid is a measure of its resistance to gradual deformation by shear stress. The value of viscosity of water is Âľ = 0.00082985 Kg/ms [9]. In this experiment viscosity is measured by using three different models i.e. (i) Ls Sundar model, (ii) Buongiorno model, and (iii) Einstein model. The data obtained are tabulated in table 3 [4], [14]. The mathematical expressions for the models are listed below: (i)Âľnf = Âľw (1+39.11Ď&#x2020;+533.9 Ď&#x2020;2) (ii) Âľnf = Âľw (1+5.45 Ď&#x2020; +108.2 Ď&#x2020;2) (iii)Âľnf = 1+2.5 Ď&#x2020; where đ?&#x153;&#x2018; - volume concentration of nanopowder; Âľnf â&#x20AC;&#x201C;viscosity of nanofluid; MMSE Journal. Open Access www.mmse.xyz

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(5) (6) (7)

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µw – viscosity of water.

Table 3. Viscosity of TiO2-water nanofluid based on different models.

Volume concentration (φ %)

Ls sundar et.al, Kg/ms

Buongiorno model, Kg/ms

Einstein Kg/ms

model,

0.0006

0.00084948

0.00083259

0.00083109

0.00125

0.00087112

0.00083564

0.00083244

0.00187

0.00089209

0.00083862

0.00083373

d) Experimental setup and its analysis:

Fig. 6. Double pipe heat exchanger used in the experiment.

Heat exchanger is a device in which heat is transferred from one fluid to another. The fluids are separated by a solid wall to prevent mixing between them [8], [15-17]. In this experiment a double pipe heat exchanger was used where the inner tube is of copper and the outer pipe is of unplasticized polyvinyl chloride plastic (UPVC). The TiO2 – water nanofluid is made to flow into the annulus section, hot water is made to flow into the copper pipe and both the inlet and outlet keys were closed to restrict the flow of both the fluids and heat transfer between them is observed. The temperature of the hot fluid decreases concurrently the temperature of the nanofluid increases. The temperatures were observed from the digital thermometer and after some time the temperature of both the fluid become steady. This temperature-time analysis of nanofluid and hot water was compared with the data observed from the normal cold water and hot water and it is observed that nanofluid causes the hot water to reach steady state temperature faster compared to normal water. More the temperature drop of hot water with less time gives efficient nanofluid for heat transfer purpose.

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Fig. 7. Temperature-time analysis of cold water and hot water. It was observed that from 225 seconds both the fluids approached steady state.

Fig. 8. Temperature-time analysis of nanofluid (φ=0.0006%) and hot water. It was observed that from 175 seconds both the fluids approached steady state.

Fig. 9. Temperature-time analysis of nanofluid (φ=0.00125%) and hot water. It was observed that from 165 seconds hot fluid approached steady state, from 170 seconds nanofluid approached steady state.

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Fig. 10. Temperature-time analysis of nanofluid (Ď&#x2020;=0.00187%) and hot water. It was observed that from 165 seconds both the fluids approached steady state. e) Specific heat measurement and temperature steadiness analysis of Nanofluid: The specific heat is the amount of heat per unit mass required to raise the temperature by one degree Celsius. The magnitude of specific heat of powder and nanofluid đ??śđ?&#x2018;? đ?&#x2018;&#x2021;đ?&#x2018;&#x2013;đ?&#x2018;&#x201A;2 = 690 J/KgK, đ??śđ?&#x2018;?Water = 4187 J/KgK [9], [18]. For a given volume concentration of nanoparticles in the base liquid, the specific heat can be calculated using the mixture formula valid for homogeneous mixtures and is given by

Cpnf =

(đ?&#x153;&#x2018;đ?&#x153;&#x152;đ??śđ?&#x2018;?)đ?&#x2018;?+((1â&#x2C6;&#x2019;đ?&#x153;&#x2018;)đ?&#x153;&#x152;đ??śđ?&#x2018;?)đ?&#x2018;¤ đ?&#x153;&#x152;(đ?&#x2018;&#x203A;đ?&#x2018;&#x201C;)

(J/KgK)

(8)

Where Cpnf â&#x20AC;&#x201C; specific heat of nanofluid; (đ??śđ?&#x2018;?)p â&#x20AC;&#x201C; specific heat of powder; (đ??śđ?&#x2018;?)w â&#x20AC;&#x201C; specific heat of water.

Table 4. Specific heat of TiO2-water nanofluid based on different models Mass (kg) of TiO2

Volume concentration (Ď&#x2020; %)

Cpnf (J/kgk)

0.000025

0.0006

4178.601

0.00005

0.00125

4169.547

0.000075

0.00187

4160.926

Summary. It can be concluded from the experiment that without adding any surfactant in the nanofluid and taking very low volume concentration of nanopowder stable nanofluid for experimental purpose can be prepared. As volume concentration increases, density increases, thermal conductivity increases, dynamic viscosity increases whereas specific heat decreases. As volume concentration increases, the time required for the steadiness of hot water decreases showing enhanced heat transfer.

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[4] He, Y., Jin, Y., Chen, H., Ding, Y., Cang, D., Lu, H. (2007), Heat transfer and flow behaviour of aqueous suspensions of TiO2 nanofluids flowing upward through a vertical pipe, International Journal of Heat Mass Transfer, 50(11-12), 2272-2281, DOI: 10.1016/j.ijheatmasstransfer.2006.10.024.

[5] Murshed, S., Leong, K., Yang, C. (2005), Enhanced thermal conductivity of TiO2-Water based DOI: nanofluids, International journal in Thermal Science, 44(4), 367-373, 10.1016/j.ijthermalsci.2004.12.005.

[6] Rajput, N. (2005), Methods of Preparation of nanoparticles-A Review, International Journal of Thermal Science, 7(4), 367-373.

[7] Pak, B., Cho, Y. (1998), Hydrodynamic and heat transfer study of dispersed fluids with submicron metallic oxide particles, Experimental Heat Transfer, 11(2), 151-170, DOI: 10.1080/08916159808946559.

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[9] Kothandaraman, C., Subramanyan, S. (2014), Heat and Mass transfer data book, New age international publishers.

[10] Boungirno, J. (2006), Convective Heat transfer enchancement in nanofluids, Heat and Mass transfer Proceddings, 2417-2423.

[11] Yang, L., Du, K. (2017), A Comprehensive review on heat transfer characteristics of TiO2 nanofluids, International Journal of heat and mass transfer, 108, 11-31, DOI: 10.1016/j.ijheatmasstransfer.2016.11.086.

[12] Bruggeman, D. (1953), Dielectric constant and conductivity of mixtures of isotropics materials, Ann. Physics, 240-250.

[13] Yang, L., Xu, J., Du, K., Zhang, X. (2017), Recent development on viscosity and thermal conductivity of nanofluids, Powder Technology, 317, 348-369, DOI: 10.1016/j.poetec.2017.04.061.

[14] Ratheesh, R. (2013), Experimental analysis on heat transfer enhancement of double pipe heat exchanger using aluminium oxide – water nanofluid and baffled twisted tape inserts, Dissertation.

[15] Sundar, L. S., Sharma, K. V. (2010), Turbulent Heat Transfer and Friction Factor of Al2O3 nanofluid in a Circular Tube with twisted tape inserts, International Journal of Heat and Mass Transfer, 15(4), 1409-1416, DOI: 10.1615/jenhheattransf.v15.i4.50.

[16] Das, S. K., Putra. N., Thiesen. P., Roetzel. W. (2003), Temperature Dependence of Thermal Conductivity Enhancement for Nanofluids, Journal of Heat Transfer, 125(4), 567, DOI: 10.1115/1.1571080.

[17] Xuan, Y., Roetzel, W. (2000), Conceptions for heat transfer correlation of nanofluids, International Journal of Heat and Mass Transfer, 43(19), 3701-3707, DOI: 10.1016/s00179310(99)00369-5.

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[18] Haddad, Z., Abid, C., Oztop, H.F., Mataoui, A. (2014), A review on how the researchers prepare their nanofluids, International Journal of Thermal Sciences, 76, 168-189. DOI: 10.1016/j.ijthermalsci.2013.08.010.

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Grey Relational Analysis for Wire-EDMed HCHCr using Taguchi’s Technique 1

K. Srujay Varma1, Shaik Riyaaz Uddien1,a, G. Narendar1, V. Durga Prasad2 1 – Department of Mechanical Eng., Osmania University, Hyderabad, Telangana, India 2 – Department of Mechanical Eng., SRKR Engineering College, Andhra Pradesh, India a – dfmriyaaz@gmail.com DOI 10.2412/mmse.31.28.864 provided by Seo4U.link Keywords: HCHCr, copper electrode, wire EDM, Taguchi’s and grey relational analysis.

ABSTRACT. In this study, effect of machining process parameters viz pulse-on time, pulse-off time, current and servovoltage for machining High Carbon High Chromium Steel (HCHCr) using copper electrode in wire EDM was investigated. High Carbon High Chromium steels have low machinability comparing to other steels and so wire EDM machinability was investigated in this work. Experiments were conducted according to Taguchi’s technique by varying the machining process parameters at three levels. This statistical technique helps in reducing cost and time by limiting the number of experiments. Interested output parameters are Material Removal Rate, Surface Roughness and Vickers Hardness.

Grey Relational Analysis was performed to find out optimized set of input parameters for achieving better output responses. It was observed that parameters of experiment 1 are highly influencing for obtaining optimized output responses.

Introduction. HCHCr stands for High Carbon High Chromium steel comes under one of the three series of cold work group, which has many applications in low temperature cutting and forming processes. Mainly used as punches, dies, rolling dies, finishing rolls for tyre mills etc., This material was chosen as area of interest because it has low machinability comparing to other steels [1], [2], [3], [4]. Wire-Electrical Discharge Machining (wEDM) is an extension of the die-sink EDM which has capability to cut complicated shapes on tough metals with excellent surface finish and low residual stresses [5], [6]. It advantages includes less processing time and less tool cost. A conductive material acts as a wire electrode and work piece gets eroded by series of discrete sparks between the work piece and wire electrode separated by a thin film of dielectric fluid. Dielectric fluid flashes away the eroded material and it also acts as a coolant. Because of its less cutting forces, its applications has been extended to machine metal foams used in heat exchangers and slicing silicon wafers used in solar cells and microelectronic components. An important aspect while machining using wire-EDM is the selection of electrode material. There are various conductive materials that can be used as electrodes but the more frequently used electrode material is copper. So copper was chosen as electrode in this study [7], [8]. Taguchi method based on orthogonal array was used for designing experiments in MINITAB 17 Software [9], [10] and Grey Relational Analysis was conducted to find out the optimized input parameters for obtaining best output responses [11], [12].

Experimental method. The workpiece material, electrode wire and machine used to carry out the experiments are described below. Design factors and response variable as well as methodology implemented for the experimentation is also outlined.

Material and Equipment used The wire EDM used to carry out the experiments was Wire EDM CNC Sprint Cut 734 (Electranica Sprint Cut 734) from Electrionica Ltd, Pune as shown in Fig 1. Dielectric fluid used in this machine is de-ionised water and copper wire of diameter 0.25 mm is taken as electrode material. HCHCr steel substrates of dimension 100 x 50 x 10 mm were considered for machining. Vickers Hardness Tester © 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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with diamond indenter and Surface-SJ 301 surface roughness tester made by Mitutoyo Company were used.

Experimental Design Taguchi method based on orthogonal array was used to design experiments in this study. The process parameters were selected depending upon machine, cutting tool and work piece capability. The input process parameters taken in this experiment are pulse-on time (Ton), pulse-off time (Ton), current (Ip) and servo voltage (SV) as shown in Table 1.

Table 1. Input process parameters of Wired EDM. S.NO.

Process Parameters

Level 1

Level 2

Level 3

1

Pulse-on Time (Ton)

100

105

110

2

Pulse-off Time (Toff)

55

59

63

3

Peak Current (Ip)

10

11

12

4

Servo Voltage (Sv)

10

55

90

Experimental Procedure The number of experiments was limited to 9 according to L9 orthogonal array using Taguchi’s statistical technique. The experiments were carried out by varying process parameters at three levels. After conducting experiments, the substrates were taken out, dried and measured for Material Removal Rate (mm3/min), Hardness (HV) and Surface Roughness (µm) were measured. Material Removal Rate (MRR) was calculated using the formula in equation (1).

MRR = VR/TM

(1)

where VR – volume of material removed after machining; TM – machining time.

Table 2. Experimental readings.

Actual values Exp No 1 2 3 4 5 6 7 8 9

MRR

Hardness

Surface Roughness

Ton

Toff

Ip

SV (mm3/min) HV

µm

100 100 100 105 105 105 110 110 110

55 59 63 55 59 63 55 59 63

10 11 12 11 12 10 12 10 11

10 55 90 90 10 55 55 90 10

2.695 3.497 3.855 3.8 2.8 3.32 3.45 3.82 3.82

0.0658 0.1976 0.2045 0.2272 0.0946 0.3073 0.3246 0.3719 0.1515

33 34 32 34 33 34 34 34 29

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The surface roughness tester is used to measure the roughness on the work piece after machining.

This observation helped in finding how the experiment conditions are affecting the surface roughness.

Then hardness of the surface was tested using micro hardness tester having Vickers diamond indenter and indenter is pressed into the materials surface with a penetrator and a weight of 1000 gms. The result of applying the load with a penetrator is an indent or permanent deformation of material surface caused by the shape of the indentor. The values obtained for MRR, Surface Roughness and Hardness are shown in Table 2.

Results and discussions: Grey Relational Analysis was performed on the data obtained from experiments.

Grey Relational Analysis In grey relational analysis first normalized data for the responses should be generated considering the lower the better and higher the better criterion this process is known as Grey relational generation.

There are four steps for performing grey relational analysis as shown in stepwise.

1) MRR and Hardness should follow the higher the better criterion, which can be expressed as xi (k) = [yi (k) – min yi (k)] /[max yi (k) – min yi (k)]

(2)

Surface Roughness follow the lower the better criterion, which can be expressed as xi (k) = [max yi (k) – yi (k) ] / [max yi (k) – min yi (k)]

(3)

Normalized data of responses after step 1 is shown in table 3.

Table 3. Normalized data of responses.

S.NO

MRR (x1),

Surface Roughness (x2), Hardness (x3), (HRC)

(mm3/min)

(Ra)

1

0

1

0.8

2

0.4305

0.3086

1

3

0.4531

0

0.6

4

0.5272

0.0474

1

5

0.0940

0.9094

0.8

6

0.7889

0.4612

1

7

0.8454

0.3491

1

8

1

0.0301

1

9

0.2799

0.0301

0

2) Let the normalized data of MRR may be represented with k=1, that of surface roughness with k=2 and that of hardness with k=3

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∆0j = ║x0 (k) – xi (k) ║= difference of absolute value x0 (k) and xi (k)

(4)

Here x0 (k) = 1, let delta = difference of absolute value.

The values obtained after step 2 is deviation sequence is shown in table 4.

Table 4. Deviation sequence.

S.NO

MRR (x1), (mm3/min) Surface Roughness (x2), (Ra)

Hardness (x3), (HRC)

1

1

0

0.2

2

0.5695

0.6914

0

3

0.5469

1

0.4

4

0.4728

0.9526

0

5

0.906

0.0906

0.2

6

0.2111

0.5388

0

7

0.1546

0.6509

0

8

0

0.9699

0

9

0.7201

0.9699

1

3) The Grey Relational Coefficient ξi (k) can be calculated as ξi (k) = [∆min + ψ ∆max] / [∆0i (k) + ψ ∆max] .

Table 5. Grey Relational Coefficient.

S.NO

MRR (mm3/min)

SR (Ra)

Hardness (HRC)

1

0.3333

1

0.7142

2

0.4675

0.4196

1

3

0.4776

0.3333

0.555

4

0.5139

0.3442

1

5

0.3556

0.8471

0.7142

6

0.7031

0.4813

1

7

0.7638

0.4344

1

8

1

0.3401

1

9

0.4098

0.3401

0.333

Let GRC = Grey Relational Coefficient After averaging the grey relational coefficients, the grey relational grade γi can be computed as:

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(5)

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γi = 1/n ∑nk=1 ξi (k) Let Grey Relational Grade be represented as GRG. Table 6. GRC and GRG table.

S.NO

MRR (mm3/min) GRC1

SR (Ra) GRC2

Hardness (HRC) GRC3

GRG

1

0.3333

1

0.7142

0.6825 1

2

0.4004

0.7098

0.8571

0.6577 3

3

0.4261

0.5843

0.7564

0.5889 9

4

0.4480

0.5242

0.8173

0.5965 8

5

0.4295

0.5888

0.79668

0.6049 7

6

0.4751

0.5709

0.8305

0.6255 5

7

0.5164

0.5514

0.8547

0.6408 4

8

0.5768

0.525

0.8729

0.6582 2

9

0.5582

0.5044

0.8129

0.6251 6

Rank

It is observed from the GRC and GRG table that rank 1 was obtained for experiment 1, which represents the parameters chosen for experiment 1 gives better results combining all three-output responses.

Summary. The number of experiments to be conducted was reduced following L9 orthogonal array of Taguchi Method which in turn reduced experimental cost and time. The best combination of obtaining optimized output was found using Grey Relational Analysis. It was found as TON = 100, TOFF = 55, IP = 10 and SV = 10, which are the parameters used for conducting experiment 1.

Acknowledgement: I would like to specially thank Prof. G. Narendar, Osmania University, Hyderabad and Prof. V. Durga Prasad, SRKR Engineering College, Andhra Pradesh for spending your valuable time to guide me during my project.

References [1] G. Ugrasen, H. V. Ravindra, G. V. Naveen Prakash, and Y. N. Theertha Prasad, “Optimization of Process Parameters in Wire EDM of HCHCr Material Using Taguchi’s Technique,” Mater. Today Proc., vol. 2, no. 4–5, pp. 2443–2452, 2015.

[2] “Comparison of HCHCr Steel and Carbide Punch and Die Increase its Strength and Life by Tin & Ceramics coating,” pp. 281–286, 2014.

[3] R. J. Naik, S. C. Kulkarni, and A. Pawar, “Charactarization and Surface Roughness Study Of Hchcr Material To Prepare Precision Stamping Punch,” vol. 8354, no. 4, pp. 77–90, 2015.

[4] J. D. Verhoeven, “Steel Metallurgy for the Non-Metallurgist,” p. 203, 2007.

[5] G. Dongre, S. Zaware, U. Dabade, and S. S. Joshi, “Multi-objective optimization for silicon wafer slicing using wire-EDM process,” Mater. Sci. Semicond. Process., vol. 39, pp. 793–806, 2015.

[6] K. Zakaria, Z. Ismail, N. Redzuan, and K. W. Dalgarno, “Effect of Wire EDM Cutting Parameters for Evaluating of Additive Manufacturing Hybrid Metal Material,” Procedia Manuf., vol. 2, no.

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February, pp. 532–537, 2015.

[7] P. Srinivasa Rao, K. Ramji, and B. Satyanarayana, “Effect of wire EDM conditions on generation of residual stresses in machining of aluminum 2014 T6 alloy,” Alexandria Eng. J., vol. 55, no. 2, pp.

1077–1084, 2016.

[8] P. Khajornrungruang, K. Kimura, and W. Chenwei, “Analysis of Effects of Cutting Parameters of Wire Electrical Discharge Machining on Material Removal Rate and Surface Integrity,” 5th Natl.

Conf. Process. Charact. Mater., p. 115, 2016.

[9] S. Tilekar, S. S. Das, and P. K. Patowari, “Process Parameter Optimization of Wire EDM on Aluminum and Mild Steel by Using Taguchi Method,” Procedia Mater. Sci., vol. 5, pp. 2577–2584, 2014.

[10] M. Durairaj, D. Sudharsun, and N. Swamynathan, “Analysis of process parameters in wire EDM with stainless steel using single objective Taguchi method and multi objective grey relational grade,” Procedia Eng., vol. 64, pp. 868–877, 2013.

[11] M. Durairaj and S. Gowri, “Optimization of Inconel 600 Alloy Micro Turning Process Using Grey Relational Analysis,” Adv. Mater. Res., vol. 576, pp. 548–551, 2012.

[12] V. Xxx, S. Shahane, and S. S. Pande, “Development of a Thermo-Physical Model for Multispark Wire EDM Process,” Procedia Manuf., vol. XXX, pp. 1–15, 2016.

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Investigation on Embllishment of Metal Nanoparticles on Graphene Nanosheets and Its Sensing Applications 1

V. Ramalakshmi1, J. Balavijayalakshmi2,a 1 – PhD Scholar, Department of Physics, PSGR Krishnammal College for Women, Coimbatore, Tamilnadu, India 2 – Assistant Professor, Department of Physics, PSGR Krishnammal College for Women, Coimbatore, Tamilnadu, India a – balavijayalakshmiroopa@gmail.com DOI 10.2412/mmse.1.22.725 provided by Seo4U.link

Keywords: graphene oxide, reduced graphene oxide, cyclodextrin, silver nanoparticles, sensor, O-Nitrophenol.

ABSTRACT. In the present work, β-cyclodextrin functionalized reduced graphene oxide-silver nanocomposites (GO-βCD-Ag) are successfully synthesized using wet chemical technique. The GO-β-CD nanocomposites are firstly synthesized via hydrazine reduction. The different concentrations (0.002 M, 0.004 M, 0.006 M, 0.008 M and 0.01 M) of silver nanoparticles are embellished on the GO-β-CD surface by the chemical reduction of silver nitrate with sodium borohydrate as a reducing agent. The synthesized GO-β-CD-Ag nanocomposites are characterized using XRD, SEM and EDAX techniques. The XRD results confirmed that the β-CD molecules are effectively coated on the rGO surface and also the Ag nanoparticles with an average size of 23 nm are uniformly decorated on the GO-β-CD surface. The GO-βCD-Ag nanocomposites modified glassy carbon electrode is employed for the selective determination of o-Nitrophenol.

Cyclic voltammetry test is performed to determine the presence o-Nitrophenol compound. The result shows the oxidation and reduction potential for o-Nitrophenol at -0.25 V and -0.45 V respectively, suggests the successful determination of o-Nitrophenol by using the GO-CD-Ag nanocomposite modified electrode.

Introduction. Phenols and vicarious phenolic compounds in natural water gives a loathsome taste and odour to drinking water and have a toxic effects on animals, humans and plants even at a small concentrations [1]. Nitrophenols are more important chemicals widely used in industrial, agricultural and defence applications. Nitrophenols are used as an intermediate compound for the manufacture of explosives, pharmaceuticals, pesticides, pigments, dyes, corrosion inhibitors and photographic chemicals [2]. These are produced as an intermediate by microbial hydrolysis of several organophosphorus pesticides such as during the photo degradation of pesticides [1]. o-Nitrophenol (o-NP), specially, poses an apparent health risks since it is toxic to mammals, microorganisms and anaerobic bacteria. Toxicity of o-Nitrophenol is due to the nitro group being easily reduced by enzymes to the nitro anion radical, nitroso and hydroxylamine derivatives [3].

These derivatives are responsible for the cytotoxic, mutagenic and carcinogenic properties of nitro compounds. The detection and analysis of nitrophenols in both waste and potable water is most important. Nitrophenols are usually detected by chromatographic techniques sometimes coupled with mass spectrometry and spectrophotometry [4]. These approaches are relatively expensive, because of high analytical cost, lengthy sample preparation and analysis times, which are not advisable for insitu measurements. Electrochemical methods are low on cost and depend on short analysis time in comparison with some of the known accustomed methods [1]. These techniques are also distinguished by high sensitivity, good selectivity, rapid response, and the instruments are roughly simple with the feasibility of miniaturization for in-situ measurements. Electrochemical analysis of nitrophenol on a bare electrode usually has the problem of fouling and low sensitivity [1]. There is need to sought for new materials that can be used as electrode modifiers in the bid to enhance the electrochemical reduction or degradation of phenol and minimisation of electrode fouling. In this present work, a © 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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nanocomposite of beta cyclodextrin functionalized reduced graphene oxide / silver nanoparticles are used.

Graphene is a one-atom thick and two-dimensional closely packed honeycomb lattice. It has received plentiful inspections from both the experimental and theoretical scientific communities. Graphene is an excellent electrode material, due to the property such as large specific surface area, strong mechanical strength, excellent conductivity and electrocatalytic activity [5].

Cyclodextrins (CDs) are cyclic oligosaccharides consisting of six, seven, or eight glucopyranose units, which are toroidal in shape with a hydrophobic inner cavity and a hydrophilic exterior. CDs have enchanted great significance due to their ability to incorporate suitable guest molecules into the hydrophobic cavity [6]. Because of these unique properties of graphene and beta cyclodextrin, the đ?&#x203A;˝CD-graphene nanocomposite shows significantly improved electrochemical sensing performance compared to the unmodified graphene nanosheets. đ?&#x203A;˝-cyclodextrin functionalized graphene nanosheets decorated with silver nanoparticles modified glassy carbon electrode (GO-CD-Ag/GCE) is fabricated for the determination of o-NP. Due to the unique properties of graphene, CDs, silver nanoparticles, the GO-CD-Ag modified glassy carbon electrode exhibits excellent supramolecular recognition and shows high electrochemical response to o- NP compared with that of the bare GCE, GO/GCE, GO-CD/GCE, GO-Ag/GCE. Experimental.

Materials and methods. Nitrophenol isomer, Graphite and đ?&#x203A;˝-Cyclodextrin (đ?&#x203A;˝-CD), hydrazine hydrate solution (50 wt.%), and ammonia solution (25â&#x20AC;&#x201C;28wt.%) are obtained from sigma aldrich and are dissolved in water. Silver nitrate powder and sodium borohydrate are purchased from Himedia, Coimbatore. All the chemicals are of analytical grade and used without further purification.

Methods.

Synthesis of graphene oxide. Graphene oxide (GO) is synthesized from natural graphite powder by modified Hummerâ&#x20AC;&#x2122;s method. The fine powder of natural graphite (2.0 g) and sodium nitrate (1.0 g) are taken in a beaker containing 23 ml of concentrated H2SO4. The reaction mixture is kept under ice bath condition (below 200 C) with continuous magnetic stirring for 1 hour. Then, potassium permanganate is added pinch wisely into the reaction suspension. The rate of addition of reducing agent is rigorously controlled to keep the reaction temperature lower than 200C. The reaction mixture is then stirred for 12 hours at 350C. The resultant reaction suspension is drenched into 1000 ml of beaker containing 500 ml of distilled water. Finally, the reaction mixture is treated with 5 ml of hydrogen peroxide solution to remove the presence of unconsumed permanganate in the reaction mixture. Finally, the reaction suspension is centrifuged with concentrated HCl followed by distilled water and dried under vacuum for 12 hours at 600 C ([7-9]).

Synthesis of Beta-cyclodextrin-graphene-Ag nanocomposites. The graphene-cyclodextrin nanocomposites are synthesized by taking 50 mg of graphene oxide in a beaker containing 50 ml of water, then dispersed using ultrasonicator for 1 hour to obtain a homogeneous brown suspension.

Beta-cyclodextrin of about 0.6 g is taken in a 50 ml of water and stirred for 2 hours. The dispersed beta cyclodextrin solution is then added into graphene oxide suspension. After the addition of hydrazine hydrate and ammonia, the pH of the reaction suspension is adjusted to 10 by using HCl. Then, the reaction mixture is stirred for 4 hours at 600 C and the reaction suspension is washed thoroughly using deionised water and dispersed in a 50 ml of water.

About 0.002 M of AgNO3 is taken in a 50 ml of water and stirred for 2 hours. The dispersed silver nitrate solution is then added drop wise into the dispersed GO-CD suspension. 0.5 M of sodium borohydrate (NaBH4) is taken in a 30 ml of water and stirred for 2 hours. The dispersed NaBH4 solution is then added into the above reaction mixture to reduce silver nitrate into silver nanoparticles.

The reaction suspension is then allowed to stirrer for 4 hours at 800 C. Finally, the reaction mixture is centrifuged using distilled water and dried under vacuum for 4 hours at 600 C ([10], [11]).

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Results and discussion. Structural analysis

Fig. 1. XRD spectra of (a) graphene oxide (b) reduced graphene oxide.

The X-ray diffraction spectra of synthesized graphene oxide and reduced graphene oxide are shown in the Fig. 1 (a-b). The disclosures of the diffraction peaks are done by comparing the obtained XRD spectra with JCPDS card no 41-1487. The broad band (for graphene oxide) obtained at 10.30 corresponding to an interlayer distance of 0.85 nm and has been assigned to the (002) reflection plane, which confirms the formation of graphene oxide by the oxidation of natural graphite using modified Hummerâ&#x20AC;&#x2122;s method. The diffraction peak at 42.30 corresponds to the (001) orientation may arise due to the incomplete oxidation of graphite materials. Graphene oxide has a higher interlayer distance due to the introduction of oxygen functional groups and water molecules between the graphene layers.

The reduction of graphene oxide to reduced graphene oxide is also confirmed by the XRD analysis.

Fig. 1 (b). Shows the diffraction peak of reduced graphene oxide obtained at 23.70 corresponding to an interlayer spacing of 0.3 nm ([12], [13]). It is evidenced from the XRD analysis that the sharp peak observed at 10.30 disappeared and shifted to 23.70, thereby confirming the reduction of graphene oxide. The shift in the diffraction peaks from graphene oxide to reduced graphene oxide decreases the interlayer distance of graphene layers, which may due to the removal of oxygen functional groups, resulting in restacking of the reduced graphene oxide sheets ([7], [14]).

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Fig. 2. XRD spectra of (a) 0.002 M (b) 0.004 M (c) 0.006 M (d) 0.008 M (e) 0.01 M of cyclodextrin functionalized graphene oxide-silver nanocomposites.

The decoration of silver nanoparticles on the surface of cyclodextrin functionalized graphene oxide surface (GO-CD-Ag) is also investigated by XRD analysis. Fig. 2 (a-e) shows the decoration of different concentrations (0.002 M, 0.004 M, 0.006 M, 0.008 M and 0.01 M) of silver nanoparticles on the polymer functionalized graphene oxide surface. The GO-CD-Ag nanocomposites shows the prominent diffraction peaks at 2θ values of 37.7°, 43.9°, 64.1°, and 77.1° and are well matched with reference to the JCPDS card number 04-0783. The obtained diffraction peaks corresponds to the (111), (200), (220), (311) crystalline planes of face-centered cubic silver nanoparticles respectively [15]. The diffraction peak intensity of graphene oxide at 10.3° is observed to be decreased after the decoration of silver nanoparticles on the GO-CD surface. This confirms that the silver nanoparticles are well dispersed and are attached onto the layers of GO-CD surface. The sharp peak observed at 37.70 confirms that the synthesized nanoparticles are composed of pure crystalline silver nanoparticles. A high intensity diffraction peak (002) of graphene oxide has been observed from the XRD analysis for 0.002 M of GO-CD-Ag nanocomposites and with the continuous increment in the concentration of silver from 0.002 M to 0.01 M, the diffraction peak intensity is found to be decreased.

The decrease in the diffraction peak intensity may be due to the decoration of silver nanoparticles on the surface of cyclodextrin functionalized graphene oxide and also due to the reduction of GO to rGO [16].

It is observed from the XRD analysis that the diffraction peaks intensity corresponding to silver nanoparticles are increasing with the increase in the silver concentrations from 0.002 M to 0.01 M, thereby confirming the high crystalline fcc structure of silver nanoparticles are decorated on the surface of cyclodextrin functionalized graphene oxide. The crystallite size of the silver nanoparticles are calculated by Debye-Scherrer equation and are found to be 18.6 nm, 21.1 nm, 23.5 nm, 23.4 nm and 23.6 nm for 0.002M, 0.004 M, 0.006 M, 0.008 M and 0.01 M respectively. The crystallite size of the synthesized silver nanoparticles increases from 0.002 M to 0.006 M concentration of silver decorated on GO-CD surface and with the continuous increment in the concentration of silver, the MMSE Journal. Open Access www.mmse.xyz

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crystallite size of the synthesized silver nanoparticles remains unchanged, thereby indicating that the adsorption capacity of silver nanoparticles on the GO-CD surface reached the saturation. It is also observed that at high loading of silver nanoparticles on the surface of cyclodextrin functionalized graphene oxide, the metal nanoparticles intercalate with GO, thereby increasing its d spacing, resulting in the broadening and decrease of GO peak intensity. On the other hand, by decreasing the concentration of silver nanoparticles loading on GO-CD surface, the d spacing of GO decreases and the GO peak intensity increases sharply, indicating that the intercalation of silver nanoparticles with the oxygen functional groups of graphene oxide decreases and thus decreasing the distance between the graphene layers. The functionalization of the GO surface with the cyclodextrin and silver nanoparticles prevents the restacking of graphene oxide nanomaterial [17].

Scanning electron microscopy analysis

(a)

(b)

Fig. 3. (a) SEM images of graphene oxide (b) reduced graphene oxide.

The morphology of synthesized graphene oxide and reduced graphene oxide samples are investigated using SEM analysis and are shown in Fig. 3 (a) and (b) respectively. SEM images clearly show that, the synthesized graphene oxide and reduced graphene oxide are in layered structures, which provides a large rough surface for the modifications of surface with silver and polymer nanocomposites [18].

From the Fig. 3 (a) and (b), it is also observed that, the wall thickness of the reduced graphene oxide is less than graphene oxide. SEM analysis also suggests that the more number of layers are removed from graphene oxide and thus confirms the formation of reduced graphene oxide [12].

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(a)

(b)

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(c)

(d)

(e) Fig. 4. SEM micrographs of (a) 0.002 M (b) 0.004 M (c) 0.006 M (d) 0.008 M (e) 0.01 M of silver nanoparticles decorated cyclodextrin functionalized graphene oxide nanocomposites Fig. 4 (a-e) shows the SEM images of different concentrations (0.002 M, 0.004 M, 0.006 M, 0.008 M and 0.01 M) of silver nanoparticles decorated cyclodextrin functionalized graphene oxide nanocomposites. It is observed from the Fig. 4., that silver nanoparticles are well dispersed on the surface and edges of the GO-CD nanocomposites, which indicates a strong interaction between graphene oxide and silver nanoparticles. The shape of the nanoparticles is found to be spherical in shape. It is also observed that the numbers of dispersion of silver nanoparticles on the surface of GOCD nanocomposites are found to be increased with the increase in the concentrations from 0.002 M to 0.006 M of silver. It is further observed that for 0.008 M and 0.01 M concentrations of silver, the MMSE Journal. Open Access www.mmse.xyz

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number of dispersion of silver nanoparticles on the surface of cyclodextrin functionalized graphene oxide is found to be decreased and slightly aggregated which indicates that the loading concentration of silver nanoparticles on the GO-CD surface reaches its saturation, which could also be evidenced from EDAX analysis. By observing the SEM image of GO-CD-Ag nanocomposites it is confirmed that, the maximum dispersion capability of silver nanoparticles on the GO-CD surface is 0.006 M concentration of silver and continuous increment in the concentration of silver leads to the aggregation and loses its property. SEM analysis also confirmed that the 0.006 M concentrations of silver nanoparticles are highly dispersed on the large surface area of GO-CD without any aggregations. This helps to enhance the catalytic activity and sensor sensitivity of synthesized GOCD-Ag nanocomposites [19].

Energy dispersive spectroscopy analysis.

(a)

(b)

(c)

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(e) Fig. 5. EDAX images of (a) 0.002 M (b) 0.004 M (c) 0.006 M (d) 0.008 M (e) 0.01 M of silver nanoparticles decorated cyclodextrin functionalized graphene oxide nanocomposites.

The EDAX analysis is used to determine the atomic percentage and composite formation in the produced nanomaterials. The EDAX spectra of 0.002 M, 0.004 M, 0.006 M, 0.008 M and 0.01 M concentrations of synthesized nanocomposites are shown in the Fig. 5 (a-e). The EDAX spectra confirm the presence of carbon, oxygen and silver elements in the synthesized nanocomposites. This analysis also confirms the presence of silver nanoparticles on the surface of GO-CD nanocomposites.

The presence of oxygen peaks indicates that the oxygen functional groups generated during the synthesis of GO remains even after the synthesis of GO-CD-Ag nanocomposites. The atomic weight percentage of oxygen in 0.002 M, 0.004 M, 0.006 M, 0.008 M and 0.01 M concentrations are 25.63 %, 26.41 %, 23.71 %, 22.09 % and 23.57 %, respectively. The atomic weight percentage of silver in 0.002 M, 0.004 M, 0.006 M, 0.008 M and 0.01 M concentrations are 2.78 %, 4.08 %, 4.72 %, 4.53 % and 4.63 %, respectively. It is confirmed from the EDAX analysis that with the increase in the concentration of silver from 0.002 M to 0.006 M, the number of silver atoms on the GO-CD surface increases and with the continuous increment in the concentration of silver above 0.006 M, the presence of silver atoms on the surface of GO-CD decreases, which could also be evidenced from SEM analysis [19]. The appearance of other peaks observed in the EDAX spectra may be attributed to the presence of cyclodextrin molecules functionalized with graphene oxide surface.

Cyclic voltametry analysis.

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Fig. 6. Cyclic voltagramm of 10 mm of o-Nitrophenol at (a) bare GCE (b) GO (c) GO-CD (d) GOAg nanocomposites.

The voltammetric behaviour of 10 mM o-Nitrophenol at the (a) bare GCE, (b) GO/GCE, (c) GOCD/GCE, (d) GO-Ag/GCE, are investigated in 0.1 M of pH 7.0 phosphate buffer solutions and are shown in the Fig. 6 (a-d). It is observed from the Fig. 6 (a) that, there is no significant oxidation and reduction peaks corresponding to o-Nitrophenol for the bare GCE, thereby confirming that there is no electro-active behaviour between bare GCE and o-nitrophenol. But the GO modified GCE as shown in Figure.6(b), shows the better electrochemical behaviour for the sensing of o-Nitrophenol molecules than the bare GCE, which may be attributed to the excellent conductivity and large surface area of graphene oxide. The GO-CD nanocomposites modified GCE shows the remarkable peak currents for the sensing of o-Nitrophenol at the oxidation and reduction potential range around -0.38 V and -0.7. The observed peak current is higher than the other two electrodes such as GO/GCE and bare GCE for o-Nitrophenol. This demonstrates that cyclodextrin molecules on the surface of graphene oxide with high supramolecular recognition capability form the host-guest complexes with o-Nitrophenol. Figure.6 (d) shows the electrochemical behaviour of GO-Ag nanocomposites modified GCE for o-Nitrophenol [20]. It shows a better electrochemical conductivity towards oNitrophenol than the above three electrodes such as bare GCE, GO/GCE and GO-CD/GCE. Hence it is evident that by combining the property of graphene oxide, cyclodextrin and silver nanoparticles, an excellent electrochemical property could be achieved.

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Fig. 7. Cyclic voltagramm of 10 mm of o-Nitrophenol at (a) 0.002 M (b) 0.004 M (c) 0.006 M (d) 0.008 M (e) 0.01 M of silver nanoparticles decorated cyclodextrin functionalized graphene oxide.

Fig. 7 (e-i) shows the reduction of o-Nitrophenol at the synthesized (a) 0.002 M, (b) 0.004 M, (c) 0.006 M, (d) 0.008 M and (e) 0.01 M of GO-CD-Ag/GCE nanocomposites by cyclic voltammetry in MMSE Journal. Open Access www.mmse.xyz

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0.1 M of Phosphate Buffer Solution (PBS) solution containing 10 mM of o-Nitrophenol. It is observed from the Fig. 7 (a-e), that all the concentrations of silver decorated cyclodextrin functionalized graphene oxide modified GCE shows the electrochemical response toward o-Nitrophenol. The cyclic voltagramm of 0.002 M of GO-CD-Ag nanocomposites modified on the GCE surface is illustrated in the Fig. 7 (a). It shows a low redox peak current corresponding to the redox potential around -0.25 V and -0.45 V, due to its deficient electrocatalysis with the o-Nitrophenol compound. But it is observed that by further increment in the concentration of silver from 0.002 M to 0.006 M, the GO-CDAg/GCE exhibits a higher reduction peak current, confirming the higher electrocatalytic activity of nanocomposites with the o-Nitrophenol [20]. This increase in the redox peak current may be attributed to the increase in the concentration of silver nanoparticles decorated on the GO-CD surface and also the excellent electrocatalytic activity of nanocomposites towards o-Nitrphenol. Furthermore, with the continuous increment in the concentrations of silver for 0.008 M and 0.01 M, the redox peak current corresponding to o-Nitrophenol is found to be decreased. This remarkable decrement in the redox peak current may be due to the aggregation of silver nanoparticles decorated on the GO-CD surface as also evidenced from SEM and EDAX analysis [21]. It is further evident from the cyclic voltammetry analysis that the 0.006 M concentration of silver decorated GO-CD nanocomposites has better electrochemical behaviour and high redox peak current than the other concentrations of silver modified GO-CD surface and thereby confirming that the adsorption of silver nanoparticles on the GO-CD surface reaches its maximum.

Summary. The present work describes the synthesis and decoration of GO-CD nanocomposites surface using different concentrations (0.002 M, 0.004 M, 0.006 M, 0.008 M and 0.01 M) of silver nanoparticles and the ultrasensitive electrochemical detection of o-Nitrophenol. The XRD results revealed that the synthesized silver nanoparticles are in high crystalline fcc structure and the average crystallite sizes of the silver nanoparticles are found to be from 18 nm to 23 nm. XRD analysis also confirmed the maximum silver adsorption capacity of GO-CD nanocomposites surface is for 0.006 M of silver concentration, which is in good agreement with SEM and EDAX analysis. SEM analysis showed the spherical shapes of the silver nanoparticles that are embellished on the surface of GO-CD nanocomposites surface. The electrochemical behaviour of the synthesized nanocomposites (GO-CDAg) is tested against o-Nitrophenol. The entire concentrations (0.002 M, 0.004 M, 0.006 M, 0.008 M, and 0.01 M) of GO-CD-Ag modified electrode showed a good electrochemical performance for the sensing of o-Nitrophenol. The maximum redox peak current for the sensing of o-Nitrophenol is obtained for the concentration of 0.006 M of silver decorated on the surface of GO-CD nanocomposites. It may concluded from the different characteristic analyses that the nanocomposites synthesized using 0.006 M concentration of silver are more effective compared to other concentrations of silver embellished on the GO-CD surface.

References [1] Thabile Ndlovu, A. Omotayo Arotiba, W. Rui Krause, B. Bhekie Mamba (2010), Electrochemical Detection of o-Nitrophenol on a Poly(propyleneimine)-gold Nanocomposite Modified Glassy Carbon Electrode, Int. J. Electrochem. Sci, 5, 1179-1186.

[2] M. Mohammed Rahmana, M. Hadi Marwania, K. Faisal Algethami, M. Abdullah Asiria, A. Salem Hameed, Basma Alhogbi (2017), Ultra-sensitive p-nitrophenol sensing performances based on various Ag2O conjugated carbon material composites, Environmental Nanotechnology, Monitoring & Management, 8, 73-82, DOI: 10.1016/j.enmm.2017.05.002.

[3] D. P. Zhang, W. L. Wu, H. Y. Long, Y. C. Liu, Z. S. Yang (2008), Voltammetric Behaviour of oNitrophenol and Damage to DNA, International Journal of Molecular Science, 9(3), 316-326.

[4] C. Zhou, Z. Liu, Y. Dong, D. Li (2009), Electrochemical Behavior of o-Nitrophenol at Hexagonal Mesoporous Silica Modified Carbon Paste Electrodes, Electroanalysis, 21(7), 853-858, DOI: 10.1002/elan.200804480.

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[5] Shanshan WANG, Yang LI, Xiaobin FAN, Fengbao ZHANG, Guoliang ZHANG (2014), βCyclodextrin functionalized graphene oxide: an efficient and recyclable adsorbent for the removal of dye pollutants, Front. Chem. Sci. Eng, 9(1), 77-83, DOI: 10.1007/s11705-014-1450-x 2014.

[6] Xin Chen, G. Stephen Parker, Gang Zou, Wei Su, Qijin Zhang (2010), β-CyclodextrinFunctionalized Silver Nanoparticles for the Naked Eye Detection of Aromatic Isomers, ACS Nano., 4(11), 6387-6394, DOI: 10.1021/nn1016605.

[7] Paulchamy, G. Arthi, B. D. Lignesh (2015), Simple Approach to Stepwise Synthesis of Graphene Oxide Nanomaterial, Journal of Nanomed Nanotechnol, 6(1), DOI: 10.4172/2157-7439.1000253.

[8] Huawen Hu, H. John Xin, Hong Hu, Xiaowen Wang, Xinkun Lu (2014), Organic LiquidsResponsive β-Cyclodextrin-Functionalized Graphene-Based Fluorescence Probe: Label-Free Selective Detection of Tetrahydrofuran, Molecules, 19(6), 7459-7479, DOI: 10.3390/molecules19067459.

[9] Abolfazl Heydari, Hassan Sheibanic (2016), Facile polymerization of β-cyclodextrin functionalized graphene or graphene oxide nanosheets using citric acid crosslinker by in-situ melt polycondensation for enhanced electrochemical performance, The Royal Society of Chemistry, 6(12), 9760-9771, DOI: 10.1039/C5RA24685G. [10] Yujing Guo, Shaojun Guo, Jiangtao Ren, Yueming Zhai, Shaojun Dong, Erkang Wang (2010), Cyclodextrin Functionalized Graphene Nanosheets with High Supramolecular Recognition Capability: Synthesis and Host-Guest Inclusion for Enhanced Electrochemical Performance, ACS Nano, 4(7), 4001-4010, DOI: 10.1021/nn100939n.

[11] Ming Chen, Yang Meng, Wang Zhang, Jun Zhou, Ju Xie, Guowang Diao (2013), β-Cyclodextrin polymer functionalized reduced-graphene oxide: Application for electrochemical determination imidacloprid, Electrochimical Acta, 108, 1-9, DOI: 10.1016/j.electacta.2013.06.050.

[12] Foo Wah Low, Chin Wei Lain, Sharifah Bee Abd Hamid (2015), Easy preparation of ultrathin reduced graphene oxide sheets at a high stirring speed, Ceramics International, 41(4), 5798-5806, DOI: 10.1016/j.ceramint.2015.01.008.

[13] Ning Cao, Yuan Zhang (2015), Study of Reduced Graphene Oxide Preparation by Hummers’ Method and Related Characterization, Journal of Nanomaterials, 2015, DOI: 10.1155/2015/168125.

[14] Soumen Dutta, Chaiti Ray, Sougata Sarkar, Mukul Pradhan, Yuichi Negishi, Tarasankar Pal (2013), Silver Nanoparticle Decorated Reduced Graphene Oxide (rGO) Nanosheet: A Platform for SERS Based Low-Level Detection of Uranyl Ion, ACS Appl. Mater. Interfaces, 5(17), 8724-8732, DOI: 10.1021/am4025017.

[15] Ana Carolina Mazarin de Moraes, Bruna Araujo Lima, Andreia Fonseca de Faria, Marcelo Brocchi, Oswaldo Luiz Alves (2015), Graphene oxide-silver nanocomposite as a promising biocidal agent against methicillin-resistant Staphylococcus aureus, International Journal of Nanomedicine, 10, 68-47-6861, DOI: 10.2147/IJN.S90660.

[16] Xiu-Zhi Tang, Xiaofeng Li, Zongwei Cao, Jinglei Yang, Huan Wang, Xue Pu, Zhong-Zhen Yu (2013), Synthesis of graphene decorated with silver nanoparticles by simultaneous reduction of graphene oxide and silver ions with glucose, Carbon, 59, 93-99, DOI: 10.1016/j.carbon.2013.02.058.

[17] R. Manash Das, K. Rupak Sarma, Ratul Saikia, S. Vinayak Kale, V. Manjusha Shelke, Pinaki Sengupta (2011), Synthesis of silver nanoparticles in an aqueous suspension of graphene oxide sheets and its antimicrobial activity, Colloids and Surfaces B: Biointerfaces, 83(1), 16-22, DOI: 10.1016/j.colsurfb.2010.10.033.

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[19] Riyaz Ahmad Dar, G. Ninad Khare, P. Daniel Cole, P. Shashi Karna, Ashwini Kumar Srivastav (2014), Green synthesis of a silver nanoparticleâ&#x20AC;&#x201C;graphene oxide composite and its application for As(III) detection, RSC Adv, 4(28), 14432-14440, DOI: 10.1039/c4ra00934g.

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Co-Dopands on Hydroxyapatite in Structural, Morphology And in Antibacterial Activity 1

S. Helen1, A. Ruban Kumar1,a 1 – Center for Crystal Growth, Department of Physics, VIT University, Vellore, India a – arubankumarvit@gmail.com DOI 10.2412/mmse.41.32.305 provided by Seo4U.link

Keywords: calcium phosphate, Mg/Zn chloride, FESEM, precipitate method.

ABSTRACT. Hydroxyapatite is calcium phosphate mineral substituted with Mg/Zn anion using precipitate method which indicates the changes in structure using X-ray diffraction. The functional groups of the material shows the bonds and morphology were analyzed using Field Emission Scanning Electron Microscopy. The application of ions doped in hydroxyapatite, which gives antibacterial activity for improving medical application due to its biocompatibility.

Introduction. Material with more stable with high dense which is insoluble in Calcium Phosphates is Hydroxyapatite (Hap) in two crystal forms Monoclinic and Hexagonal. In practical hexagonal is important because monoclinic form is destable with small amount of foreign ions. Ionic substitution used to improve the biological performance of calcium phosphates developing the applications in biomedical field [1]. The ions Zn, Cu, Sr provide crystallinity also it increase antimicrobial, Ag-Zn ions substituted using microwave refluxing method used for biomedical applications [2]. Ag has higher Antibacterial activity with less toxicity but it is limited due to its high cost and discoloration.

A Zn ion has antibacterial activity with less toxicity with color stability, heat resistance in low cost.

Hap substituted with single and also as co-do pants investigating photo luminous using Mn with Sb and compatibility, corrosion resistance using Zn doped Si, Ag improves mechanical and biological behaviour of Hap by substituting Zn with F-Ti incorporate in Ag with Hap provides bioactivity and bio compatibility as nanotubes using for implantations. TiO2 doped Ag has potential application on photo catalysts, oxidation on gas sensors, cell membranes, toxic contamination on water to CO 2 [38]. Co-do pants varying different anions affects structure and morphology of Hap. Mg, Zn ions are trace elements present in human body due to properties (ie. formation of bones) using Sol-gel method with high purity. The Mg ion increases the solubility and reduces the lattice parameters improves crystallinity by increasing Mg ratio and Zn ion gives changes in morphology, increase stability to materials which reduces thermal stability. Morphology may be irregular form agglomeration by increasing Zn content. Ions with less ionic radius, which give stability to the Hap and increase the solubility with decrease in lattice parameters. Ceramic materials with different anions used for surface modification to improve both mechanical and corrosion property for implantation. Zn acetate added with Hap, which improves antibacterial activity using extraction method, provides oral hygiene products. Ag with Zn oxides using plant extract which increase the antibacterial activity and also it kills the cancer cells [9]. Ions Ag-Zn nitrates on Hap determines their benefit on biomedical applications. Previous studies focused on individual substitution of ions in Hap also with co-do pants but varying different anions not yet reported based on the medical applications. Ionic substitution improves properties of hydroxyapatite.

Various methods are used for synthesizing Hap such as sol-gel method [10], hydrothermal method [11-12], micro wave irradiation [13-14], electro deposition method [15], precipitate method [16© 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0

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17]. Wet precipitate method were used in order to avoid carbonate into mg doped Hap. In addition, the product up to 5.7% was similar to biological apatite without toxicity. As mentioned above there are various reports on ion substituted Hap but differing anions on hap substituted were rare. The paper focused on hydroxyapatite substituted with Mg/Zn chloride, which enhance property of Hap and used in various applications such as in implantation, anti-bacterial activity, sensors. The Zn is the bioactive material increase bioactivity and used as an antimicrobial activity.

Material and Methods. Calcium nitrate tetra hydrate (Ca (NO3)2.4H2O) Mw 236.15 with Diammonium hydrogen phosphate (NH4)2HPO4, Mw 132.06, Ammonium hydroxide (NH4OH), Magnesium Chloride hexa hydrate (MgCl2 .6H2O), Zinc chloride (Zn Cl2. H2O), Mw 136.29.

Preparation of Hydroxyapatite. Calcium nitrate tetra hydrate dissolve in 50 ml of Millipore water and Di-ammonium hydrogen phosphate dissolved in 50 ml of water. (NH4)2HPO4 added drop wise to (Ca (NO3)2.4H2O) maintain pH at 9 using NH4OH.The obtained precipitate washed with distilled water several times and dried at 80°C (Ca / P) grinded using mortar pestle for different characterizations. The Mg/Zn chloride was doped using same procedure in Calcium nitrate (Ca+ X) /P (X-Mg/Zn chloride) as in given Table 1.

Table 1. Elemental Composition of Samples.

Sample code

CN

NHP

MZN

MZC

MZCL

CN

1

-

-

-

-

NHP

-

0.67

-

-

-

MZCL

0.98

0.67

0.01

0.01

0.01

CL6

0.96

0.67

0.02

0.02

0.02

Result and Discussions. The addition of dopands into Hap gives structural changes, crystal linty.

XRD shows broad peaks which indicate amorphous material forms nano-size particles (Fig. 1). The JCPDS (09-0432) for hydroxyapatite shows sharp peaks as well crystallinity and doping Chloride ions shows just increase in intensity (i.e. broad peaks) with decrease in lattice parameter may be due to smaller ions incorporate into Hap. The Mg in Ca II site which decrease c-axis, which shows decrease in crystallinity used in various applications such as coatings to carry drugs and also improved bone induction. The increase in a and decrease in c due to the Cl ion as reported in paper [18]. The changes in lattice parameter and in volume due to the anions which showing that chloride increases a and decrease in c [18]. And also volume shows decrease for the components and hkl value of the peaks 002, 211, 310, 222 were shown in XRD analysis with 2-theta values mentioned in Table 2.

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Fig. 1. XRD graph of Pure Hap and Mg/Zn chloride (0.01 & 0.02).

Table 2. Lattice parameters and volume.

Sample

2ď ą value

Unit cell Volume(V) parameters

HAP(09-0432)

-

a

c

Hap

31.77

9.418

6.884

528.80

CL

31.87

9.415

6.886

528.61

9.412

6.887

528.56

CL6

FTIR. In this FTIR analysis (Fig. 2) which shows the functional group of the material, the value 500-560 indicates vibration mode of PO4-3, value between 565-570 shows bending mode of PO4-3 and between 1000-1040 shows stretching mode of PO4-3. Assymetric stretching of PO4-3 between 1030-1120 and values at 1650-1065 indicates OH deformation and 632-634 and in 3500 indicates OH vibration mode.

FESEM. FESEM gives the morphology of the samples in nm range gives particle size 50-70 nm and for MZCL 44-64 nm. The agglomeration with small elongation in spherical shape may due to Zn ion in Hap [3]. No morphology changes by decreasing the dopants concentration as shown in Fig 3.

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Fig. 2. FTIR Spectra.

Fig. 3. FESEM for pure Hap and doped Hap with (0.01 & 0.02) concentration.

Antibacterial Activity. The antibacterial activity test analyzed by well diffusion method using Mueller Hinton agar using 100ml of water and sterilized poured into petriplates and solidification MMSE Journal. Open Access www.mmse.xyz

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using the pathogenic bacterial strains E.Coli and S.aureas. The plates were kept at hot air oven in 37° C for 24 hours incubation. The plates were read after 24 hours which shows that pure Hap does not exhibit but doped with Mg/Zn chloride exhibit 18-24 mm in E.coli and in S.aureas form 15-20 mm (Fig. 4).

Fig. 4. Antibacterial activity for a) pure Hap and doped Hap b) s.aureas and c) E.coli.

The results occur due to the metal ions interaction with proteins or interaction with antibacterial membranes causes structural change and porousness.

Summary. In this present work co-dopands Mg/Zn chloride with hydroxyapatite gives the structural changes which confirmed by XRD and functional groups of different vibration modes were shown in FTIR. The morphology changes with spherical elongation gives through FESEM and antibacterial exhibit 18-24 mm in E.Coli and 15-20 mm in S.aureaus, which can used in various applications.

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Journal of Alloys and Compounds, 645, 478-486, DOI: 10.1016/j.jallcom.2015.05.064.

[15] D. Gopia, E. Shinyjoya, L. Kav (2015), Influence of ionic substitution in improving the biological property of carbon nanotubes reinforced hydroxyapatite composite coating on titanium for orthopedicapplications, CeramicsInternational, 41, 5454–5463, DOI: 10.1016/j.ceramint.2014.12.114.

[16] G.S. Kumar, A. Thamizhavel, Y.Yokogawa, S.N. Kalkura, E.K. Girija (2012), Synthesis, characterization and in vitro studies of zinc and carbonate co-substituted nano-hydroxyapatite for biomedical applications, Materials Chemistry and Physics, 134(2), 1127-1135, DOI: 10.1016/j.matchemphys.2012.04.005.

[17] M. Šupová (2015), Substituted hydroxyapatite for biomedical applications: a review, Ceramics international, 41(8), 9203-9231, DOI: 10.1016/j.ceramint.2015.03.316.

[18] Y. Tang, H.F. Chappell, M.T. Dove, R.J. Reeder, Y.J. Lee (2009), Zinc incorporation into hydroxyapatite. Biomaterials, 30(15), 2864-2872, DOI: 10.1016/j.biomaterials.2009.01.043.

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First-Principles Study on the Electrical Properties of Cu2GeSe3 Compound 1

Devi Prasadh P.S.1,a, B. K. Sarkar2,b, A. Arulgnanam3,c 1 – Department of Physics, Dr. Mahalingam College of Engineering & Technology, Pollachi, Coimbatore, India 2 – Department of Physics, Galgotias University, Greater Noida, India 3 – Department of Physics, St. John’s College, Palayamkottai, Tamilnadu, India a – psdprasadh@gmail.com b – bks@physics.org.in c – gospelin@gmail.com DOI 10.2412/mmse.98.61.409 provided by Seo4U.link

Keywords: semiconductors, density functional theory, FP-LAPW+lo.

ABSTRACT. Electronic properties of Cu2GeSe3 are calculated using the full potential linearized augmented plane wave plus local orbitals method. In this paper, we discuss the Cu2GeSe3 compound with the full-potential linearaugmented plane wave (FP-LAPW) method within the framework of the density functional theory (DFT) for electronic properties using the WIEN2k code. The calculated equilibrium lattice is in reasonable agreement with the experimental data. The electronic structures indicate that CuGaSe3 is a semiconductor with a direct band gap of 0.81802eV. Furthermore, other experiments and theory also show that this material has a direct band gap. It is noted that there is quite strong hybridization between Ga3d and S3s orbitals, which belongs to the (GaS 2). The complex dielectric functions are calculated, which are in good agreement with the available experimental results.

Introduction. The ternary compound Cu2GeSe3 belongs to the quaternary diamond-like where AI = Cu, BVI = Ge, and CVI = S, semiconductors with universal composition Se or Te. This is one of the two probable groups of the three-fold normal derivatives of the AIIBVI binary compounds [1]. The compounds Cu2GeVI3 have fascinating semiconducting, optical and electronic properties, and because of low band gap these materials are widely applied in photovoltaic and AO devices in the near infrared region [2]. These types of compounds have low melting points, which can be reduced with the addition of the atomic number of anions [3].

Cu2GeSe3 melts in the range between 760°C and 788°C [4–6]. The structure of this compound has been investigated by single crystal X-ray diffraction method by E. Parthé and J. Garín in the year 1971 [7]. This compound has orthorhombic Imm2, with unit cell parameters of a = 11.869 Å, b = 3.960 Å, c = 5.485 Å. Earlier studies of the electrical properties [8] highlighted that Cu2GeSe3 displays semiconductor behaviour at liquid nitrogen and at room temperature shows metallic behaviour. Thermal and structural properties of Cu2GeSe3 were also investigated [9]. Debye’s temperature, Young’s modulus, specific heat, etc. were obtained from the measurement of thermal expansion, micro-hardness and velocity of ultrasonic waves. Regarding the applicability of ternary compound as AO material, it is more significant to offer much importance on the search of optical properties. The characterization of Cu2GeSe3 is a little in literature. In this paper we present the electronic properties Cu2GeSe3 has been produced.

Computational method. The experimental procedure to grow Cu2GeSe3 single crystal using the conventional Bridgeman method has been discussed earlier [10]. The electronic properties were performed in the framework of Density Functional Theory (DFT). To calculate this property, we have taken the full potential linearized augmented plane wave plus local orbitals (FP-LAPW+lo) as © 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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implemented in the WIEN2k code [11-12]. We have used the generalized gradient approximation (GGA) as parameterized by Perdew, Burke and Ernzerhof (PBE) to describe the exchange and correlation effects [13]. Cu2GeSe3 compounds crystallize in the zinc-blende structure with space group F-43 m. The calculations were through with RMTkmax = 9, to accomplish energy Eigen value convergence. RMT is the smallest radius of the muffin-tin (MT) spheres and kmax is the maximum value of the wave vector. The corresponding values of muffin-tin radii (RMT) for Cu, Ge and Se were taken in atomic units for the calculation. The Gmax parameter was taken to be 14.0 Bohr-1. The wave function has been expanded inside the atomic spheres with the maximum value of the angular momentum lmax as 10. The irreducible Brillouin zone (BZ) of the zinc-blende structure has been decomposed into a matrix of 10×10×10 Monkhorst–Pack k-points [14]. The iteration procedure is continued with total energy and charge convergence to 0.0001Ry and 0.001e, respectively.

Results & discussions.

Electronic properties. It is found that, Cu2GeSe3 has two types of anion-centered tetrahedral structure. The 2a-site Se atoms are surrounded by two Cu and two Ge atoms, and the 4c-site Se atoms bond with three Cu, and one Ge atoms. Cu and Ge atoms occupy 4c and 2b sites, correspondingly.

The electronic band structure of Cu2GeSe3 has been calculated. The calculated band structure for Cu2GeSe3 at equilibrium is shown in figure 1. The band profiles are almost similar all the quaternary diamond-like semiconductors, with some minute differences.

Fig. 1. Shows the Band Structure of Cu2GeSe3.

The band structure confirms the direct energy gap between the top of the valence band and the bottom of conduction band at Γ point. This is the regular performance related to the increase of the lattice parameters, which was also found for other II-VI compounds. The calculated band gap is underestimated in contrast with experimental results, because of the simple form of GGA, which cannot account the quasi particle self-energy. The electronic structures specify that Cu2GeSe3 is a semMMSE Journal. Open Access www.mmse.xyz

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iconductor with a direct band gap of 0.81802 eV. Furthermore, other experiments and theory also show that this material has a direct band gap [10]. It is noted that there is quite strong hybridization between Ge3d and Se3s orbitals, which belongs to the GeSe3. The complex dielectric functions are calculated, which are in good agreement with the available experimental results. From optical absorption measurements [15] the temperature deviation of the band gap Eg of Cu2GeSe3 showed band-to-band direct transition with Eg around 0.78 eV at room temperature.

The total density of states (DOS) for Cu2GeSe3 is shown in figure 2. The computed Cu2GeSe3 shows the metallic ground state. Almost the same DOS has been received for diamond-like semiconductors such as CuGaSe2, CuGaS2, Cu2ZnSnS4 [16, 17] The first structure in the total DOS is small and centred at around -15.1 eV for Cu2GeSe3. This structure arises because of the s states and it corresponds to the lowest lying band with the dispersion in the region around the ᴦ point in the Brillouin zone.

Fig. 2. Shows the total Density of States of Cu2GeSe3.

There is a wide spread in DOS in the energy range starts from -2.55eV energy. From the figure 2, it is clearly seen that the DOS from -15.5 eV to 12 eV it is mostly composed of Cu-d, Se-p and Ge-s and Ge-p states. The valance band which is nearer to the Fermi level is mostly made up of Cu-d and Se-p states and also it is seen that the conduction band is mostly from Ge-s and Se-p states. Also it is identified that Cu-d state is disconnected in to two parts. The primary part in DOS in the energy range starts from -5.9 eV to -3.15 eV energy and the next structure appears at -9.85 eV. The crossing between Cu-d and Se-p state is pretty small, representing a little weak covalent p-d bonding.

Summary. This chapter reports a systematic study of the electronic properties of Cu2GeSe3 has been studied with FP-LAPW + lo method in the framework of density functional theory (DFT). The generalized gradient approximation (GGA) was considered for the exchange and correlation effects calculations. The results from FP-LAPW + lo method were generally satisfactory with the experimental data in comparison to other calculation methods. From the band structure it confirmed the direct energy gap between the top of the valence band and the bottom of conduction band at Γ point.

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References [1] J.M. Delgado (1998), Crystal Chemistry of Diamond-like and other Derivative Semiconducting Compounds, Inst. Phys. Conf., 152, 45-51.

[2] L. K. Samanta (1987), On some properties of I2-IV-VI3 compounds, phys stat. sol. (a), 100(1), K93 – K97, DOI: 10.1002/pssa.2211000165.

[3] L. I. Berger, V. Prochukhan (1969), Ternary Diamond-Like Semiconductors, Consultants Bureau, 1- 121.

[4] E. P. Rogarocha, A. N. Melikhova, N. M. Panasenco (1975), Neorg. Mater., 11, 839.

[5] I. D. Olekseyuk, L. V. Piskach, O. V. Parasyuk, O. M. Melńiyk, T. A. Lyskovetz (2000), Single crystal preparation and crystal structure of the Cu2Zn/Cd,Hg/SnSe4 compounds, J. Alloys Compd.

298, 203, DOI: 10.1016/S0925-8388(02)00006-3.

[6] M. A. Villarreal, B. J. Fernández, M. Pirela, A. Velásquez-Velásquez, A. J. Mora, G. E. Delgado (2003), Rev. Mex. Fís., 49, 198 - 200.

[7] E. Parthé, J. Garín (1971), Zinkblende- und Wurtzitüberstrukturen bei ternären Chalkogeniden der Zusammensetzung 12463, Monastsh. Chem., 102, 1197 – 1208, DOI: MOCMB7 [8] B.J. Fern´andez, G. Marcano, D.B. Bracho (1995), III Latin American Workshop Magnetism, Magnetics Materials and their Applications, M´erida-Venezuela, 280.

[9] L.I. Berger, N.A. Bulenkov (1964), Electrical, thermal, and elastic properties of a number of semiconducting compounds of the type AI2BIVCVI3, Izv. Akad. Nauk SSSR, Ser. Fiz 28.

[10] Bimal Kumar Sarkar, Ajay Singh Verma, P.S. Deviprasad (2011), Temperature induced band gap shrinkage in Cu2GeSe3: Role of electron–phonon interaction, Physica B, 406, 2847 – 2850, DOI: 10.1016/j.physb.2011.04.045.

[11] G. K. H. Madsen, P. Blaha, K. Schwarz, E. Sjöstedt, L. Nordström (2001), Efficient linearization of the augmented plane wave method, Phys. Rev. B, 64(19), 195134, DOI: 10.1103/PhysRevB.64.195134.

[12] K. Schwarz, P. Blaha, G.K.H. Madsen (2002), Electronic structure calculations of solids using the WIEN2k package for material science, Comp. Phys.Commun., 147(1), 71–76, DOI: 10.1016/S0010-4655(02)00206-0.

[13] J. P. Perdew, K. Burke, M. Ernzerhof (1996), Generalized gradient approximation made simple, Phys. Rev. Lett., 77, 3865–3868, DOI: 10.1103/PhysRevLett.77.3865.

[14] H.J. Monkhorst, J. D. Pack (1976), Special points for Brillouin-zone integrations, Phys. Rev. B., 13(12), 5188–5192, DOI: 10.1103/PhysRevB.13.5188.

[15] G. Marcano, L. Nieves (2000), Temperature dependence of the fundamental absorption edge in Cu2GeSe3, J. Appl. Phys., 87, 1284 – 1286, DOI: 10.1063/1.372010.

[16] M. I. Alonso, K. Wakita, J. Pascual, M. Garriga, N. Yamamoto (2001), Optical functions and electronic structure of CuInSe2, CuGaSe2, CuInS2, and CuGaS2, Phys. Rev. B, 63(7), 075203, DOI: 10.1103/PhysRevB.63.075203.

[17] Joachim Paier, Ryoji Asahi, Akihiro Nagoya, Georg Kresse (2009), Cu2ZnSnS4 as a potential photovoltaic material: A hybrid Hartree-Fock density functional theory study, Phys. Rev. B, 79(11), 115126, DOI: 10.1103/PhysRevB.79.115126.

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Impedance Behavior of Pb1-xCoxFe12O19 Obtained by Sol-Gel Auto Combustion Method 1

S. Prathap1,a, W. Madhuri1,b 1 – Ceramic Composites Laboratory, Center for Crystal Growth, VIT university, Vellore, Tamilnadu, India a – Spj244@gmail.com, b – madhuriw12@gmail.com DOI 10.2412/mmse.16.77.153 provided by Seo4U.link

Keywords: impedance spectroscopy, sol-gel, microwave sintering, hexaferrites.

ABSTRACT. Pb1-xCoxFe12O19 (x=0.25, 0.50 and 0.75) ceramics are synthesized by sol-gel auto-combustion technique and sintered at a temperature of 900 oC for 45 min using microwave furnace. The X-ray analysis confirms single phase hexagonal structure and the crystallite sizes are found to be varying between 34-54 nm. The Nyquist plots exhibited two relaxation region: one is attributed to electrode polarization, while the other is attributed to the effect of grain and grain boundary on the electrical properties of the present series.

Introduction. The hexagonal ferrites have the general formula M-Fe12O19 (M = Ba, Sr and Pb).

These hexaferrites have got potential applications in various fields due to large coercive field [1].

The electrical and magnetic properties of hexagonal ferrites are affected by the synthesis technique, chemical stability, substituent cations and average crystalline size [2]. Alamelu et al [3] investigations dielectric and impedance properties of M-type hexaferrites of Sr hexaferrites and reported that the non-magnetic properties such as impedance spectroscopy, dielectric constant and loss almost depend upon the preparation technique, sintering temperature and time and doping element [3]. The present article focuses on the structural and impedance behaviors of cobalt doped Pb1-xCoxFe12O19 synthesized by sol-gel auto-combustion technique followed by microwave sintering.

Experimental Procedure. In order to prepare M-type Pb1-xCoxFe12O19, Pb (NO3)2, Co (NO3)2.6H2O, Fe (NO3)3.9H2O, C6H8O7 and distilled water are taken as the raw materials. Three different molar ratios of Pb1-xCoxFe12O19 are chosen as 0.75:0.25:12, 0.50:0.50:12, 0.25:0.75:12, and are synthesized according the procedure mentioned in our earlier work [4]. The samples are characterized using X-ray diffractometer (XRD, BRUKER, λCuKα= 0.14518nm) and HIOKI 3532-50 LCR HiTESTER (Japan) for structural and impedance properties respectively.

Results and Discussions.

Structural properties. The XRD patterns of the synthesized cobalt doped lead hexaferrites material is presented in Fig. 1. The observed diffraction maxima and obtained miller indices (h k l) are corresponding to the diffraction lines of hexagonal structure. The products have the peak corresponding to basis of the lead hexaferrites (hexagonal; space group P 63/mmc) [4]. The lattice parameters (a=b & c), crystallite size (D), unit cell volume (icell), X-ray density (ρx), bulk density (ρb) by Archimedes law and porosity (P) are calculated and tabulated in Table.1 using the standard formulae [4]. The crystallite size is found to be varying between 34-54nm. Irregular variation of lattice parameter reflects on X-ray density and unit cell volume. The bulk density is increasing with increase of ‘x’ value due to decrease of iron atoms while the porosity decreases slightly. © 2017 The Authors. Published by Magnolithe GmbH. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/

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Fig. 1. XRD spectra of Pb1-xCoxFe12O19 (x= 0.25, 0.50 & 0.75).

Table 1. XRD data of cobalt doped Pb1-x CoxFe12O19.

0.25

0.50

0.75

D (nm)

34

34.6

54.6

a = b (nm)

0.5343

0.5687

0.5809

c (nm)

2.164

2.459

2.278

Vcell (nm)3

0.6587

0.6931

0.6522

ρx (g/cm3)

5.274

5.206

5.513

ρb (g/cm3)

4.302

4.573

4.389

Porosity (P)

0.350

0.261

0.287

c/a

3.655

4.322

3.902

Impedance Spectroscopy Analysis. In order to understand the dielectric relaxation behaviors of Pb1-xCoxFe12O19, the impedance spectra is recorded in the frequency range 100Hz to5MHz and temperature 483 to 543K. Impedance spectroscopy gives information about grains and grain boundaries. The effect of these relaxations is better understood from complex plane analysis of impedance [3]. In this regard Cole-Cole plots are drawn (Fig. 2) for complex impedance i.e., between Z' and Z" at various temperatures. The inquest plots exhibit semicircle arcs. With their centers below real Z’ axis indicating non-Debye type relaxations [3, 5]. Hence, this result also confirms the single semi-conducting with a spike attached attributing to the dominance of grain resistance in the material nature. It happens owing to the contribution of conductivity of grain and grain boundary.

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Fig. 2. Shows Cole–Cole plot for all hexaferrites compositions.

Summary. Cobalt substituted lead hexaferrites are synthesized by sol–gel method by changing Co content in the range of x = 0.25–0.75 with lead. XRD analysis confirms that sample has a hexagonal structure with P63/mmc space group. The impedance plot highlights the existence of single semicircle arc at all temperatures indicating the presence of grain conduction in the material.

Acknowledgements. This work was financially supported by Rajiv Gandhi National Fellowship grant no RGNF-2014-15-SC-TAM-64671, UGC New Delhi. Authors are thankful to prof.

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S. Kalainathan for providing LCR bridge facility. Authors also acknowledge SIF at SAS, VIT University and Vellore for XRD facility.

References [1] Shahid Hussain, Asghari Maqsood (2008), Structural and electrical properties of Pb-doped Srhexa ferrites, Journal of Alloys and Compounds, 466 (1-2), 293-298, DOI: 10.1016/j.jallcom.2007.11.074.

[2] Faiza Aen, Shanhida B, Niazi, M.U. Islam, Mukhtar Ahmed, M. U. Rana (2011), Effect of holmium on the magnetic and electrical properties of barium based W-type hexagonal ferrites, Ceramics International, 37 (6), 1725-1729, DOI: 10.1016/j.ceramint.2010.10.006.

[3] K. Alamelu Mangai, K. Tamizh Selvi, M. Priya, M. Rathnakumari, P. Sureshkumar (2017), Impedance and modulus spectroscopy studies of cobalt substituted strontium hexaferrite ceramics, J Mater Sci: Mater Electron, 28 (18), 13445-13454, DOI: 10.1007/s10854-017-7183-0.

[4] S. Prathap, W Madhuri (2017), Multiferroic properties of microwave sintered PbFe12−xO19−δ, Journal of magnetism and magnetic material, 430, 114-122, DOI: 10.1016/j.jmmm.2016.12.116.

[5] K. Chandra Babu, W. Madhuri (2016), Microwave assisted solid state reaction method: Investigations on electrical and magnetic properties NiMgZn ferrites, Material chemistry and physics, 181, 432-443, DOI: 10.1016/j.matchemphys.2016.06.079.

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I I. Mec hani cal Eng i neeri n g & Phys ic s M M S E J o u r n a l V o l . 1 4

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Design Validation of the Working Surface of a Sheep’s Foot Roller for Compaction of Freshly Prepared Soil D. Artemenko1, a, V. Nastoyaschiy1, V. Darienko1 1 – Central Ukrainian National Technical University, Kropivnitskiy, Ukraine a – ingenerdu@gmail.com DOI 10.2412/mmse.6.16.975 provided by Seo4U.link

Keywords: roller drum, compaction of the soil, a foot of the roller, the working surface of the roller, a mathematical model of the roller interaction with the soil.

ABSTRACT. It is determined that the main factors which influence the process of soil compaction are the design of the roller working element and physical and mechanical characteristics of the soil. The process of interaction between the roller and the soil was studied with the help of math modelling. It was defined that the character of the contact pressure distribution under the roller surface corresponds to its design characteristics. A modified design of the roller drum and foot was introduced.

Introduction. Preparation of the construction site plays an important role in modern civil engineering work during the process of constructing buildings of agricultural purposes. One of the main stages is the preparatory compaction of the soil under the future foundation of the building and approach tracks. This technique allows avoiding such a negative phenomenon as surface subsidence and with time the building foundation and approach tracks ruining. A lot of construction equipment is used in this process and rollers of different types are the most popular machines (static [1], vibrating smooth wheeled rollers [2], vibrating pneumatic tired rollers [3]). Sheep’s foot rollers, both of static and vibratory type, are considered to be the most effective as they are suitable for compaction of different types of soils. The main problem of construction rollers is unsatisfying compaction of the freshly prepared soil of the construction site for upcoming work. According to the specification documents [4-6] it is recommended to compact the soil of the site repeated layer by layer to make it ready for the construction work. It increases power consumption and prime cost of construction activity and also decreases general speed of work. For this reason it is important to increase operational efficiency of the roller for the preparatory compaction of the soil to the maximum depth and uniformity across the width.

Analysis of latest research. Static smooth wheeled rollers are the most popular rollers used for compaction of soil today. During his research Kushnarev A.S. [7] has found out that the smooth drum of the roller does not meet the requirements for the formation of the uniform compactness of the soil across the width and in depth.

Saveliev S.V. [8], while analyzing the work of smooth wheeled rollers, concludes that such a design does not provide the required state of the soil and it decreases their efficiency. This is the reason why this type of rollers is used in modern construction activity less and less. He thinks pneumatic tired rollers are more effective and their working surface has more opportunities for adjusting for compaction specifications. Usage of vibrating pneumatic tired rollers can essentially improve the soil compacting process and decrease its prime cost. The main disadvantage of such rollers is their low workability on non-cohesive soils. It greatly reduces their multipurposeness.

Improving the design of a construction roller, Dudkin M.V. [9] suggests changing its exterior outline in plane motion. He thinks it can greatly influence the uniformity of soil compaction.

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In work [10] special attention is paid to the work of sheep’s foot rollers and the peculiarities of their “feet”. It was concluded that such rollers are better than smooth wheeled rollers for compacting the clayed soils.

Litvinenko T.V. [11] comes to a conclusion that sheep’s foot rollers can be used for compaction lumpy soils. Feet crush lumps and make soil homogeneous over its thickness. It is useless to compact the upper layer of the earth fill with these rollers because the feet stir the soil. In this case it is better to use smooth wheeled rollers which make the surface smooth and even.

To be able to improve the design of construction rollers further we need clear understanding of how their working characteristics are formed. Experimental research [12, 13] proved the existence of stress fields and deformation of the inner soil body under the influence of compacting machines and because of this it is possible to say that their classification defines the main characteristic of the compacting process. So, designing the required working surface of a roller and its foot, one can substantially influence the quality of technical implementation of the process, especially providing uniform compaction of the soil across the width and in depth.

Work objective: improvement of uniform soil compaction across the width of the drum coverage and to the maximum depth through justification of a sheep’s foot roller working surface design.

For achieving the objectives we solved the following problems: to analyze the design of modern sheep’s foot rollers to identify their advantages and disadvantages in the process of work; to design an updated sheep’s foot roller based on the detected disadvantages in the work of their drum and feet; to prepare a mathematical model of the updated sheep’s foot roller work and specify in general the character of contact pressure distribution under its working surface.

Statement of basic material.

The analysis of modern sheep’s foot rollers work showed that both the design of the roller drum itself and the geometric form of the roller foot influence the quality of performance. The main disadvantages of the existing working elements are not uniform distribution of the soil compaction across the width and stirring of the soil by feet due to their design peculiarities. Thus it is necessary to continue further studies on validation of sheep’s foot rollers working surfaces.

To avoid above mentioned disadvantages we introduced a roller [14], depicted in a two-level fig. 1; the first level (a roller drum) designed for the uniform compaction of the upper layer of the soil, the second level consists of the feet for the uniform compaction of the lower layer of the soil. The roller in question consists of side frames 1 with working arch curved surface 2, covered by overlapping barrel-shaped feet 3 placed on it on a spiral curve (further we consider that the drum and foot surface has an elliptical section).

Fig. 1. A sheep’s foot roller: 1 – side frames, 2 – working surface, 3 – feet MMSE Journal. Open Access www.mmse.xyz

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Work process of the suggested sheep’s foot roller goes on in such a way: in the process the working surface 2 compact the upper layer of the soil uniformly and feet 3 placed on it on a spiral curve compact the lower layer of the soil uniformly providing uniform compaction of the soil across the width and in maximum depth.

The main factor with the help of which it is possible to define if the suggested design meets the requirements for the formation of the uniform compaction in the roller operating process is the character of the distribution of the load per surface unit across the width and to the depth.

It is possible to use methods of continuum mechanics [7, 12, 15] for creating a math modelling of the interaction process between a sheep’s foot roller and soil in order to get the picture of the contact pressure distribution under it. Researches in continuum mechanics show that the hypothesis of continuity has a slight deviation from the results of the experimental research. That is why the soil can be regarded as a quasihomogeneous continuum the performance of which under pressure is defined by the balance of stress, deformation and their derivatives over time.

The interaction of the roller with the soil can be presented as the contact process of two objects which have different deformation moduli. A similar problem is considered in general in the theory of elasticity [16]. Due to symmetry a three-dimensional problem of the roller interaction with the soil can be narrowed down to a solution of a plain problem in which forms of the objects in contact are described with the help of functions: y1  f1 x  and y2  f 2 x  , where

y  y1  y2  f1 x   f 2 x 

(1)

On contact intervals y  0 :

f1  x   f 2  x   0

(2)

As the result of compression the objects get axil motion along ОY :

1

and

 2 . Then   1   2

is drawing of the compressed objects together.

Apart from the mentioned movement, spring-like movements are observed too U 1 and U 2 along axis ОX . Final complete spring-like movement along axіs ОY equals:

1  2    f1 x  U1   f 2 x  U 2 

(3)

In case of slight displacement along axis ОX there is:

f1 x  U1   f1 x  and f 2 x  U1   f 2 x  , from which:

1  2    f1 x   f 2 x  MMSE Journal. Open Access www.mmse.xyz

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(4)

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Without taking into consideration the friction force we deal with the soil as a linear elastic environment to the border line of which standard pressure is applied pt  . We use famous in the theory of elasticity Flamant problem (fig. 2).

Fig. 2. The problem chart of standard force action on a spring half plane border.

Let us intercept a linear element on the contact line from point x  t to x  t  dt , where the force pt dt acts. Under the influence of concentrated force P the movement on the border of the contact line is:

   pt ln

1 С, tx

(5)

where С  const – a constant;

t  x – distance between points of axis ОX with abscissas x and t ;

 – elasticity composite index, which characterizes deformation properties of interacting materials:



where

2  1  2 , Ed

(6)

Е d – deformation modulus (it has dimension Н/м2);

 – poisson’s ratio.

Force pt dt , applied to the border of half plane at the point x  t , causes in it elementary move in the direction of the force action:

d   pt ln

1 dt  С , tx

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Movements 1 and  2 on the section of the contact line of the roller with the soil can be defined with the help of formulas:

1  1  pt  ln L

1 dt  С , tx

2   2  pt  ln L

1 dt  С , tx

(8)

(9)

Taking into account total displacement and comparing right parts of the formulas (8), (9) and (4) we get an integral equation for pressure px  , which is the main one for solving plane contact problem of the theory of elasticity [16]:

1   2  pt ln L

where

1 dt  С  f1 x   f 2 x  , tx

(10)

1  pt  ln t  x dt  f x  – is a function which depends on the form of pressing objects and L

their deformation properties;

L – contact line of the roller with the soil.

From equation (10), we have:

f x  

С  f1 x   f 2 x  , 1   2

(11)

In equation (10) function f x  is considered to be given in the middle of the contact line border of the roller with the soil and defined from the statement of the problem.

Because the surface of the roller and the foot taken for the research has arch curved shape, we see its profile as a part of ellipse. In this case we can narrow down the problem to the definition of elliptically shaped deformer efficiency on the soil ground (fig. 3).

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Fig. 3. Flow pattern for an elliptical deformer working on the soil ground.

In our case the sheep’s foot roller profile (fig. 3) is described in an equation:

f x   ae 

aе 2 be  x 2 , bе

(12)

where bе – semimajor axis;

aе – semiminor axis;

x – the coordinate.

In this situation the solving of the main contact problem equation of the elasticity theory makes it possible to get the pressure law under the working surface of the roller:

px  

С

br 1   2  2

be  x 2 , 2

(13)

where br  2be – the length of the contact area between the roller and the soil;

1 – deformation constant of the roller material;  2 – deformation constant of the soil.

As the real size of the deformer is unknown we will do the further research in relative units which depend on the roller surface material and physical and mechanical characteristics of the soil.

We reduce (13) to:

p z   K 1  z 2 ,

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where K 

С

br 1   2  2

- constant coefficient;

z

x . be

Based on (14) we get the function characteristic curve in relative units (fig. 4).

Fig. 4. General drawing of contact pressure on contact surface.

It is possible to see in fig. 4 that the character of the contact pressure distribution corresponds with the design peculiarities of the deformer. As the result, we can state that the geometry dimensions of the deformer are the main conditions which influence the final result – the formation of the necessary soil compaction on the whole contact area.

The math modelling under consideration makes it possible to take into account not only the characteristics of the roller working surface material, but its linear dimensions too while designing an updated sheep’s foot roller. It is also possible to confirm that the coefficient K, which includes deformation properties of interacting materials 1 and  2 , and the deformer linear dimensions (elliptic surface elements bе and

aе ), directly influence contact pressure level px  .

In general, if improved overlapping feet are placed on the drum surface we can state that the character of the contact pressure distribution across the width will look as in fig. 5.

Fig. 5. Scheme of the contact pressure distribution after the pass of the sheep’s foot part of the roller.

If to take into consideration that the drum surface also has an elliptical shape, which has much larger size than for the foot, we can say that the character of the contact pressure distribution on the contact surface will be the same with the above mentioned results.

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The research results show that the character of pressure distribution under the suggested sheep’s foot roller meets the requirements of the standardized documents as for the compaction of freshly prepared soil for the future construction site. But to define the rational value of the updated roller design parameters, additional experimental research with the help of simulation modelling and methods of planning an experiment is required.

Summary. 1. The analysis of the modern sheep’s foot rollers operating allowed to define that their design does not meet all the requirements for getting maximum compaction of the soil across the width and to the depth per minimum passes and that is why we introduced a new design of a sheep’s foot roller and formulated a math modelling of its work.

2. The suggested math modelling of the sheep’s foot roller work allows defining the character of the contact pressure distribution depending on the design characteristics of the roller elements and physical and mechanical characteristics of the soil.

3. Modulus of deformation and coefficient of lateral expansion are its main characteristics which serve for the choosing technological and design factors of the sheep’s foot roller.

4. Efficiency of the suggested compaction roller design is provided because thanks to the working surface and feet design it is possible to provide homogeneous compaction of the soil across the width and to the maximum depth and reduce the number of passes of the roller for the required compaction of the soil.

References [1] Construction machinery. Reference book in 2 volumes. Ed. V.A. Bauman, F.A. Lapira. Т.1 Machines for the construction of industrial, civil, hydraulic structures and roads. Ed. 4 th, revised and supplemented (in Russian). – Moscow, Mechanical Engineering, P. 136. (1976).

[2] Bondakov, B.F., Varganov, S.A., Garber, M.R. and other (1973). Handbook of road machine designer. Edition 2nd, reworked and supplemented (in Russian). – Moscow: Mechanical engineering, P. 245.

[3] Artemev, K.A. (1982). Road machines. Machines for the installation of pavements (in Russian).

– Moscow: Mechanical engineering, 349 P. [4] SBS (State building standards) V.1.2-5: 2007 (2007). Scientific and technical support of construction objects (in Ukraine). - Kyiv: Minregionstroy of Ukraine, 13 P. [5] SBS (State building standards) V.2.1-10-2009 (2012). Basics and foundations of buildings and structures. Basic design points. With changes №1 and №2 (in Ukraine). - Kyiv: Minregionstroy of Ukraine, 161 P. [6] SBS (State building standards) V.2.3-4: 2015 (2015). Constructions of transport. Roads (in Ukraine). - Kyiv: Minregionstroy of Ukraine, 91 P. [7] Kushnarev, A.S., Kochev, V.I. (1989). Mechanical and technological basis of soil cultivation (in Russian). – Kyiv: Harvest, 144 P. [8] Saveliev, S.V. (2014). Development of the theory and improvement of the construction of vibrating rollers with pneumatic working bodies: abstract the dissertation of the doctor of technical sciences (in Russian). – Omsk: Siberian Road Institute, 33 P. [9] Dudkin, M.V. (2010). Increase of efficiency of consolidation process on the basis of perfection of road’s designs skating rinks: the dissertation of the doctor of technical sciences (in Russian). – Almatyi: KazATK, 355 P. [10] Teleshev, V.I., Vatin, N.I., Marchuk, A.N., Komarinskiy, M.V. (2012). Hydrotechnical works.

Part 1. General construction issues. Earthwork and concrete work. Textbook for high schools (in Russian). – Moscow: Publishing house ASV, 448 P. MMSE Journal. Open Access www.mmse.xyz

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[11] Litvinenko, T.V. (2016). Sealanting of soils in road embankment provided their durability is guaranteed: the dissertation of the candidate of technical sciences (in Ukraine). – Poltava: PNTU Im. Yu. Kondratyuka, 210 P. [12] Degraf, G.A. (1966). Some results of studies of stresses in soil. Bulletin of Agricultural Science (in Russian). - Alma–Ata, № 10, P. 87 – 89.

[13] Boytsev, A.V. (2017). The method of justifying the parameters of rollers of a road roller with an isotropic force action on an asphalt-concrete mixture: the dissertation of the candidate of technical sciences (in Russian). – Saint Petersburg, SPbPU Petra Velikogo, 142 P. [14] Sealant roller: Patent № 108147 U Ukraine, Е01С19/28 / Artemenko, D.Yu., Nastoyaschiy, V.A., Antonyuk, O.M. (in Ukraine). – № 201511733; stated 27.11.2015; painted 11.07.2016, bulletin № 13, 3 P. (2016).

[15] Vodyanik, I.I. (1990). Impact of running systems on soil. Scientific basis (in Russian). – Moscow: Agropromizdat, 173 P. [16] Shtaerman, I.Ya. (1949). The contact problem of the theory of elasticity (in Russian). – Moscow: Gostekhizdat, 162 P.

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Feature-Based Discretization of a Turbine Disk for Probabilistic Risk Assessment Michael A. Thomas1, Jace Carter1, Lloyd Matson1, Tarun Goswami1 1 – Damage Tolerance and Probabilistic Lifing of Materials Center, Wright State University, Dayton, USA DOI 10.2412/mmse.21.86.70 provided by Seo4U.link

Keywords: discretization, turbine disk, probabilistic risk assessment, principal stress, mathematical model.

ABSTRACT. There is an economic need to extend the useful life of jet engine rotors. Retirement-for-Cause (RFC) is a lifing method that allows for the continued operation of components passed traditional life limits. Under RFC, an extension of damage tolerance, components are deemed safe for a further service interval using non-destructive inspections (NDI) for crack like defe cts. As components are kept in-service beyond their designed service life it is essential that the probability of failure (POF), or risk, of continued service is known. Under current FAA rotor design certification practices the component POF is analyzed using a probabilistic framework focused on only the life limiting crack location. This method generates conservative approximations of the operational risk, also known as a relative risk.

The proposed method for a feature-based discretization allows for a transition from the relative risk towards an absolute risk. The general guidelines, for the discretization, have been established through performance of probabilistic assessments of a representative turbine disk. The discretization is performed by initially separating the representative turbine disk into various features. These features are then discretized through the introduction of defect locations in response to the stress gradient topology. Once the discretization of the disk is completed, a fracture mechanics-based probabilistic assessment is performed utilizing DARWIN®. DARWIN® is a fracture mechanics based probabilistic assessment software package developed by Southwest Research Institute, SwRI®. The POF of the features are obtained through the statistical combination of the defect location POFs. The representative turbine disk POF is likewise obtained by the statistical combination of the feature POFs. The probabilistic assessment results for the two methods, the life limiting and discretization, are compared for the representative turbine disk.

Introduction. With an aging aircraft fleet there is an economic benefit to safely extending the useful life of aircraft engine components beyond the low-cycle-fatigue limit. However, the extension of component life causes an increase in the component probability-of-failure (POF) hence the risk of continued service must be quantified [1]. Historically, safe life methods are utilized to establish the operating limits for turbine engine components. Safe life methods establish a low cycle fatigue, LCF, operating life which certifies that only 1 in 1,000 disks develop a life-limiting crack [2, 14]. However, this method came into question after the uncontained engine failure which led to the deadly crash in Sioux City, Iowa of 1989 [4]. After the accident the Federal Aviation Administration, FAA, urged OEM’s to investigate the possibility of incorporating a damage tolerance life method to account for inherent flaws, which could lead to failure of an engine, for certification of new rotor designs [3-6].

The damage tolerance lifing method assumes that all components and materials have inherent flaws and conservatively determines the inspection interval required to prevent these flaws from growing to a critical size which may lead to failures, like that in Sioux City [1, 2, and 4]. For the purpose of quantifying the operating risk utilizing damage tolerance methods South West Research Institute, SWRI, developed the Design Assessment of Reliability With Inspection (DARWIN®) software package. DARWIN® is a probabilistic fracture mechanics program which utilizes damage tolerance concepts to determine the POF of a component with inherent defects subjected to cyclic loading conditions [7]. DARWIN® is recognized and approved for use by the FAA for new rotor design certification [1]. However, the current lifing methods employed in DARWIN® and outlined by the FAA for the risk assessment of high energy rotors provide conservative risk values which ensure that the cumulative POF is less than 1 in a 1,000 components over the operational safe life [13].

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Safe life and damage tolerance conservatively predetermines the operating life of components, retiring them regardless whether there is a cause [1, 10]. Therefore, to safely extend the operational life of components a method of retirement-for-cause (RFC) is being investigated by the U.S. Air Force.

Under RFC, components are only removed from service if a crack like defect is detected by a nondestructive inspection (NDI) [10]. RFC allows for the utilization of a greater percentage of the component life while reducing the life cycle cost [9]. RFC utilizes damage tolerance concepts to allow for safe extension of component life beyond the accepted LCF limit. Safe life is utilized to establish the LCF limit, which specifies the safe life of components at three standard deviations below the mean fatigue limit [13]. The LCF limit must be established for RFC such that LCF induced damage can be accounted for. Meanwhile, damage tolerance concepts establish the necessary safe inspection intervals [1]. The safe inspection interval (SII) must be determined to ensure that the LCF induced defects, also called flaws, do not have time to grow to a critical length. However, as components are kept in-service beyond the LCF limit of the material the risk of failure increases [1, 9]. Therefore, before RFC can be implemented the increased risk must be quantified and the conservatism of the probabilistic risk assessment must be minimized. A DARWIN® fracture mechanics based probabilistic risk assessment is performed to quantify the risk of component usage.

To move forward with RFC a more accurate risk value must be attained. DARWIN® produces a relative risk [7, 8], thus one way to reduce the conservatism of the probabilistic risk assessment is by moving towards an absolute risk. One method for accomplishing this is through the discretization of the turbine disk for use in the probabilistic risk assessment. The current lifing methods utilize the lifelimiting location of the life-limiting feature to assess the risk for the component [7, 8]. The life-limiting location is based on the maximum stress location of the component, in which the max principal stress is extended through and applied to the entire surface area of the life-limiting feature [7, 8].

Conversely, the discretization method utilizes the stress gradient topology to capture the effects of the stress gradient, of the feature, on the POF of the component. As the stress gradient of a feature increases, the discretization produces a lower risk, thus removing conservatism from the risk determination. This produces a more accurate risk value, called an absolute risk, for each feature of the component. This report will cover the methodology for establishing the discretization of the turbine disk, for use in the retirement for cause approach. Thus establishing the method for quantifying the risk associated with the safe life extension of turbine engine components. Next the creation and establishment of the finite element model for use in the discretization and probabilistic risk assessment will be discussed.

Finite Element Model. This section covers the generation and establishment of the representative turbine disk finite element model. The three dimensional finite element model and stress analysis of the representative turbine disk, for use in DARWIN®, can be created using Abaqus® or Ansys® [7, 8]. The stress results were then compared to expected results to validate the solutions of the finite element analysis (FEA) simulation. The model output database file, .odb, was then converted, to a DARWIN® compatible version, utilizing the conversion software of the DARWIN® software package [7, 8].

For the purpose of the proposed method the 3-D finite element model was created via Abaqus/CAE®.

The geometry and loading conditions of the turbine disk were provided by the U.S. Air Force. The Abaqus/CAE® generated visualization of the 3-D representative turbine disk model has been provided in Fig. 1. Due to the high operating temperatures of turbine disks Inconel 718 was selected to be utilized as the material of the representative turbine disk. The material properties of Inconel 718 were obtained from the High Temp Metals Inc. [11] and Military Handbook, MIL-HDBK-5H [12].

Once the finite element model, material properties, and loading/boundary conditions were established, the finite element analysis was performed. A standard mesh convergence study was performed to ensure convergence of the analysis results.

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Fig. 1. Abaqus®/CAE generated visualization of the representative turbine disk.

The maximum principal stress results were obtained, as shown in Fig. 2, from the finite element analysis for comparison to the expected values. To validate the finite element analysis results for the representative turbine disk the max principal stresses at key locations were compared to expected stress values provided by the U.S. Air Force. The highest max principal stress was determined to be in the inlet air slot, shown in Fig. 3, which was where the max value was expected to be. The lowest max principal stress was expected and found in the inlet bolt hole.

Fig. 2. Abaqus®/Implicit max principal stresses obtain from FEA.

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Fig. 3. Abaqus®/Implicit stress results for max principal stresses at the inlet air slot.

The converged and validated representative turbine disk finite element model was then converted for utilization by DARWIN® for the discretization and probabilistic risk assessment. The DARWIN® software package contains a conversion code which upgrades the output database, .odb, file into a DARWIN® compatible file, *.upgraded.odb [7, 8], to perform the fracture mechanics based probabilistic risk assessment of the representative turbine disk. Next, the proposed methodology and general guidelines for the establishment of the feature-based discretization of a representative turbine disk for the determination of an absolute risk value will be developed.

Feature-based Discretization of a Turbine Disk. This section will cover the method for discretizing the representative turbine disk for the probabilistic risk assessment. A feature-based discretization of the representative turbine disk is necessary to move from the relative risk, of the life-limiting approach developed by the FAA, to an absolute risk, resulting from the stress gradient topology based discretization approach developed in this report. To establish the feature-based discretization of the representative turbine disk the finite element model was characterized by the eight major features as shown in Fig. 4. The defect locations were introduced in response to the stress gradient topology of each feature to establish the feature-based discretization of the component. A 2-D slice is generated for each defect location to establish a corresponding zone for the definition of the fracture mechanics plate and the associated variable analysis parameters [7]. The defect occurrence rate of the feature is established by the geometry of the feature and the anomaly distribution. The defect occurrence rate is utilized to move from the conditional POF to the unconditional POF [7, 8], thus accounting for the inherent flaws in the materials and components [2, 4].

The eight major features, as shown in Fig. 4, were established based on geometry to allow for the consistent discretization of the representative turbine disk model. The features of the model include: the inlet and outlet bolt holes, air slots, and webs, along with the hub and hub web. The general guidelines for the establishment of the defect locations for these features are provided in further detail in the next section.

Defect locations. The representative turbine disk features were discretized thru introduction of defect locations, which were constructed on the stress gradient topology. General guidelines for the discretization of features based on the stress gradient topology have been established. These recommendations are meant as a general starting point, further refinement may be necessary to attain convergence, which is discussed in further detail in section 5.

The defect locations, also called zones [7, 8], are the points of interest, in a particular component feature, in which defects (cracks) are permitted to grow in the fracture mechanics plate for the probabilistic risk assessment of the feature [7, 8]. The defect locations are established for the model and are assumed to be of equal risk [4, 8]. Thus, each defect location should have similar POF risk contribution factors (RCF) for a given component feature [8]. The defect locations of the component features were established such that the associate area encompasses an approximately univariant stress MMSE Journal. Open Access www.mmse.xyz

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gradient. Through performance of the probabilistic risk assessment and experience some general guidelines were established for the introduction of the defect locations.

Fig. 4. Turbine disk model feature nomenclature.

As a general guideline for the turbine disk features it was established that in the high stress gradient regions, where the stresses produce stress intensities above the stress intensity threshold, for every 1 ksi in the transverse direction of the circular feature a defect location set was necessary. Meanwhile, in low stress gradient regions, where the stresses produce intensity factors below the stress intensity threshold, a defect location set is necessary only every 15 ksi in the transverse direction of the circular feature. The defect location sets should contain corner crack type defect locations at the edges of the circular feature and any number of surface crack type defect locations on the surface between the edges. As a general guideline it was determined that for a variation of 1.5 ksi thru the circular feature one surface defect was required for the defect location set.

The same approach was determined to be appropriate for the establishment of the defect locations, or zones, within the “web” features, which are not fully treated as circular features. For these features the stress gradient and geometry line of symmetry was utilized as the transverse direction for the general guidelines. This allows for the same guidelines, which have been established for the circular features, to be utilized for the “web” features as well. The max principal stresses and the corresponding defect locations for each of the turbine disk features have been provided in Figs. 5-12 for the converged risk assessment model.

The creation of the defect locations are both feature and stress gradient dependent. The hub and hub web were found to have truly univariant stress gradients, which results in a single defect location set required through these features, as seen in Figs. 5 and 6. respectively. These were the only two features which were found to have a truly univariant stress gradient. The remaining features were found to have bivariant stress gradients. Thus, dictating the development of an extensive method for establishing the feature-based discretization of the remaining features; to ensure that the defect location surface areas meet the assumption of univariant stress gradient at each defect location.

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Fig. 5. Max principal stresses and the defect locations of the hub.

Fig. 6. Max principal stresses and the defect locations in hub web.

The inlet air slots and bolt holes were found to have bivariant stress gradients. This produces the need for multiple defect location sets for the circular features, shown in Figs. 7 and 8 respectively, to meet the assumption that the stress gradient of each defect location should be univariant. These features were also found to be symmetric about the transverse direction centerline of the feature with respect to the max principal stresses, which can also be seen in the stress Fig. of Figs. 7 and 8. The symmetry of the feature stress gradients allows for the establishment of fewer defect locations to fully define the total surface of the feature. This leads to an increase in the computational efficiency of the feature probabilistic risk assessment.

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Fig. 7. Max principal stresses and the defect locations in inlet air slot.

Fig. 8. Max principal stresses and the defect locations in inlet bolt hole.

The symmetry of the max principal stresses and the stress gradients were also identified in the inlet web. As was found with the inlet air slots and bolt holes this decreases the number of defect locations needed to define the feature, thus increasing the computational efficiency of the model. The bivariant stress gradients of the inlet web lead to the necessity of multiple defect location sets to generate the discretization such that the surface area associated with each defect location could be treated as having a univariant stress gradient. The max principal stresses and defect locations established for the inlet web have been provided in Fig. 9.

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Fig. 9. Max principal stresses and the defect locations in inlet web.

The bivariant stress gradients of the max principal stresses were also identified in the outlet air slot, bolt hole, and web features. The defect locations were established in the same manner as was done for the corresponding inlet features. The stress gradients and resulting defect location have been provided in Figs. 10-12.

Fig. 10. Max principal stresses and the defect locations in outlet air slot.

Fig. 11. Max principal stresses and the defect locations in outlet bolt hole.

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Fig. 12. Max principal stresses and the defect locations in outlet web.

Zone definitions. Once the defect locations of each of the features have been established 2-D slices were generated at each of the defect locations [7]. These 2-D slices are then utilized to establish the zone definitions. The zone definitions are comprised of the crack type selection, plate definition, and determination of the variable analysis parameters [7, 8]. For the purposes of the proposed discretization method the crack types were selected such that the fracture mechanics plates are defined in terms of the defect location’s surface area. The fracture mechanics plate definition consists of the establishment of the fracture mechanics plate and the associated surface area of the defect location [7]. The variable analysis parameters include the inspection schedules and zone properties, which consist of the material fatigue crack growth (FCG), and anomaly distribution to be utilized for each defect location.

Crack type. There are several crack types available in DARWIN® to describe the crack associated with each defect location of the feature. The crack type was utilized to establish the fracture mechanics plate for the POF determination of each defect location. For the turbine disk model two crack types were utilized. The crack types were selected as univariant cracks, utilizing the assumption that after the discretization, each of the defect locations and associated surface areas have univariant stress gradients. Therefore, the univariant surface crack type SC17 and the univariant corner crack type CC11 were chosen for use in the probabilistic risk assessment of the representative turbine disk. These crack types have the capability to be defined in part by the surface area associated with the defect location as part of the fracture mechanic plate definition in DARWIN® [7, 8]. Now that the crack type has been selected the variable analysis parameters and the fracture mechanics plate definitions can be established.

Variable analysis parameters. The variable analysis parameters consist of the necessary input parameters required for the determination of the turbine disk POF. These variable input parameters can be provided such that variability in the inspection schedules and properties can be captured to ascertain the effect on the POF. The variable analysis parameters provide the definitions for the inspections, the material FCG data, and the anomaly distribution.

The inspection input parameter consists of assigning an inspection schedule and POD curve, which simulates the capabilities of the NDI techniques, to the defect location’s zone definition. There are several predefined POD curves available within DARWIN®. For the assessment performed under the proposed discretization methodology the default 400 MV 50% confidence level Eddy Current inspection POD curve, Fig. 13, was utilized [6, 7]. The inspection intervals and standard deviations can also be varied to established standards for the inspection schedules. The inspection schedule was employed as outlined in the FAA AC 33.70-2 [6]. The inspection schedule was established assuming MMSE Journal. Open Access www.mmse.xyz

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100% of fleet components are inspected at the 4,000 and 8,000 flight cycles with an end life of 20,000 flight cycles. This inspection schedule was chosen for the ability to later compare the results with those obtained by performing the life-limiting approach as outline by the FAA AC 33.70-2 [6].

Fig. 13. Default AIA 400 MV 50% confidence level Eddy Current POD curve [6, 7].

The material FCG analysis parameter was utilized in the fracture mechanics formulation for the determination of the POF of the individual defect locations. Experimental FCG data for Inconel 718 was collected from literature and compiled to establish a database of the material FCG [1, 15, and 16]. A statistical analysis was performed on the experimental data, utilizing the JMPÂŽ statistical software package, to establish the mean and Âą3Ď&#x192; of the material FCG data. A plot of the experimental material FCG data and the results from the JMPÂŽ statistical analysis have been provided in Fig. 14.

The upper dotted line represents the -3Ď&#x192; of the data; while the lower dotted line represents the +3Ď&#x192; of the data. The solid line thru the middle of the experimental data is the mean FCG data. The Paris equations for the material FCG mean and Âą3Ď&#x192; lines, equations 1-3, were determined from the JMPÂŽ statistical analysis shown in Fig. 14. For the probabilistic assessment of the representative turbine disk the Inconel 718 FCG data and resulting mean Paris equation, equation 2, were utilized. đ?&#x2018;&#x192;đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018;&#x161;đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019;đ?&#x2018;&#x203A;đ?&#x2018;Ą = 1 â&#x2C6;&#x2019; â&#x2C6;?8đ?&#x2018;&#x2013;=1(1 â&#x2C6;&#x2019; đ?&#x2018;&#x192;đ?&#x2018;&#x2013; ) đ?&#x2018;&#x20AC;đ?&#x2018;&#x2019;đ?&#x2018;&#x17D;đ?&#x2018;&#x203A;:

+3đ?&#x153;&#x17D;:

đ?&#x2018;&#x2018;đ?&#x2018;&#x17D;

= 1.034đ??¸(â&#x2C6;&#x2019;9)(â&#x2C6;&#x2020;đ??ž)2.95

(2)

= 6.801đ??¸(â&#x2C6;&#x2019;10)(â&#x2C6;&#x2020;đ??ž)2.95

(3)

đ?&#x2018;&#x2018;đ?&#x2018;

đ?&#x2018;&#x2018;đ?&#x2018;&#x17D; đ?&#x2018;&#x2018;đ?&#x2018;

(1)

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Fig. 14. Inconel 718 FCG data with mean and ±3σ lines.

The anomaly distribution analysis parameter is utilized to establish the manufacturing induced anomaly distribution curve for the occurrence of alpha particles in Inconel 718. For the surface damage probabilistic risk assessment the default anomaly distribution for circular features was established and is available in DARWIN® [7, 8]. The default anomaly distribution has been provided in Fig. 15. This anomaly distribution was utilized as the base curve for the assessment of the representative turbine disk. For the feature-based discretization method a frequency reduction factor was utilized to adjust the default anomaly distribution based on the L/D ratio [7], which is discussed in section 3.3.1 in further detail.

Fig. 15. Default circular feature anomaly distribution curve [7, 8].

Plate definition. The plate definition tab of the zone definition allows for the generation of the fracture mechanics plate for utilization in the fracture mechanics based probabilistic risk assessment being performed by DARWIN® [7, 8]. The plate should be created such that it closely approximates the feature geometry [7]. It may be necessary to adjust the plate gradient angle such that the plate crack propagation direction is perpendicular to both the surface and the surface stress gradients [8].

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Once the fracture mechanics plate has been generated it is necessary to determine the surface area associated with the defect location.

The formulations necessary for the determination of the surface areas are geometry specific. The surface area associated with each defect location is necessary in the establishment of the unconditional POF [8], which is discussed in further detail in section 3.3.2. The surface area formulations were derived and established for the various geometries found in the representative turbine disk model. For a different turbine disk model it may be necessary to establish additional surface area formulations.

For the surface area of a circular feature, such as the hub, in which there is only one defect location set thru the feature the surface area formulation is a result of the lateral surface area of a cylinder with the equation, đ?&#x2018;&#x2020;đ??´ = 2đ?&#x153;&#x2039;đ?&#x2018;&#x;đ?&#x2018;Ą

(4)

where r â&#x20AC;&#x201C; is the radius of the circular feature; t â&#x20AC;&#x201C; is the thru thickness associated with that defect location.

Given a circular feature, such as the air slots or bolt holes, in which multiple defect location sets thru the feature are present, the surface area formulation results from the equations for arc length and law of cosine. These equations are combined and result in the following equation for the surface area,

đ?&#x2018;&#x2020;đ??´2 = 2 [

đ?&#x153;&#x2039;đ?&#x2018;&#x;

2 +â&#x2C6;&#x2020;đ?&#x2018;§ 2 ) 2đ?&#x2018;&#x; 2 â&#x2C6;&#x2019;(â&#x2C6;&#x2020;đ?&#x2018;Ś12 12

2 +â&#x2C6;&#x2020;đ?&#x2018;§ 2 ) 2đ?&#x2018;&#x; 2 â&#x2C6;&#x2019;(â&#x2C6;&#x2020;đ?&#x2018;Ś23 23

2đ?&#x2018;&#x; 2

2đ?&#x2018;&#x; 2

đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018; â&#x2C6;&#x2019;1 ( 360

) + đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018; â&#x2C6;&#x2019;1 (

)] đ?&#x2018;Ą

(5)

where r â&#x20AC;&#x201C; is the radius of the circular feature; t â&#x20AC;&#x201C; is the thru feature thickness associated with the defect; â&#x2C6;&#x2020;đ?&#x2018;Ś â&#x20AC;&#x201C; is the feature transient global coordinate; â&#x2C6;&#x2020;đ?&#x2018;§ â&#x20AC;&#x201C; is the feature radial global coordinate.

The subscripts 1, 2, and 3 refer to the defect locations. This surface area formulation was also utilized for the determination of the associated surface areas of the inlet web defect locations.

Given a disk like feature, such as the hub web or outlet web, the surface area formulation can be expressed by the equation for a truncated cone. This surface area formulation can be expressed as,

đ?&#x2018;&#x2020;đ??´2 = đ?&#x153;&#x2039; [(đ?&#x2018;&#x;1 + đ?&#x2018;&#x;2 )

2 +â&#x2C6;&#x2020;đ?&#x2018;Ś 2 â&#x2C6;&#x161;â&#x2C6;&#x2020;đ?&#x2018;Ľ12 12

2

+ (đ?&#x2018;&#x;2 + đ?&#x2018;&#x;3 )

2 +â&#x2C6;&#x2020;đ?&#x2018;Ś 2 â&#x2C6;&#x161;â&#x2C6;&#x2020;đ?&#x2018;Ľ23 23

2

]

(6)

where r â&#x20AC;&#x201C; is the feature radius;

â&#x2C6;&#x2020;đ?&#x2018;Ľ and â&#x2C6;&#x2020;đ?&#x2018;Ś â&#x20AC;&#x201C; are the global coordinates.

The subscript values 1, 2, and 3 refer to the defect locations of interest.

These surface area formulations were utilized to approximate the surface areas associated with each of the defect locations in the various features of the representative turbine disk model. The surface MMSE Journal. Open Access www.mmse.xyz

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areas are then utilized to establish the area effect [7], as discussed in section 3.3, for the determination of the unconditional POF from the conditional POF [7, 8], as discussed in greater detail in section 4.

Defect occurrence rate. The final aspect of the DARWINŽ probabilistic analysis is the establishment of the defect occurrence rate, also known as the volume or area effect. To move from the conditional POF to the unconditional POF the defect occurrence rate must be established. The defect occurrence rate utilizes the anomaly distribution, frequency reduction factor, and the surface area associated with the defect location [6, 7, and 8]. The frequency reduction factor, ν, is utilized to alter the anomaly distribution to account for the effect of the slenderness ratio of the circular features on the risk computations [8]. This adjustment gives the defect occurrence rate per area, which is multiplied by the surface area to obtain the total defect occurrence rate for the respective defect location.

This means that the defect occurrence rate can be different between defect locations. The defect occurrence rate is then applied to the conditional POF to form the unconditional POF. Frequency reduction factor, đ??&#x201A;. The frequency reduction factor is utilized to adjust the anomaly distribution to account for the effect of the slenderness of circular-hole features [8]. DARWIN generates the frequency reduction factor from the plate definition supplied within the zone definition of the defect location [7, 8]. This default formulation works for the developed life-limiting approach.

However, the DARWINÂŽ formulation was insufficient for use with the discretized approach developed within this report. The issue occurred in the surface area associated with the defect location.

DARWINÂŽ appears to assume that the surface area provided is for the entire feature not for a fraction of the feature, as is the case for the discretization method proposed in this report.

The discretization approach utilizes the surface areas associated with the individual defect locations not the feature surface area. To account for this the frequency reduction factor was established externally. The frequency reduction factor is a piecewise parameter, as shown in Fig. 16, which is dependent on the slenderness ratio of the feature [8], which can easily be obtained from the turbine disk geometry. Once the slenderness ratio of the feature of interest is known the frequency reduction factor can be obtained. The frequency reduction factor is formulated as [6, 7, and 8], 0.04

đ?&#x153;&#x2C6; = {0.04 Ă&#x2014;

(10.729â&#x2C6;&#x2014;(đ??żâ &#x201E; â&#x2C6;&#x2019;1 ) đ??ˇ ) đ?&#x2018;&#x2019;

1.0

< 1.0 đ??ż đ?&#x2018;&#x201C;đ?&#x2018;&#x153;đ?&#x2018;&#x; â &#x201E;đ??ˇ â&#x2030;Ľ 1.0, â&#x2030;¤ 1.3 > 1.3

Fig. 16. Plot of frequency reduction factor versus L/D ratio [7, 8].

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(7)

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For the representative turbine disk the frequency reduction factors were established for each of the features. For the circular features, such as the inlet and outlet air-slots and bolt-holes, and the hub, a reduction factor of 0.04 was obtained. The web features are turned surfaces which generate a much smaller occurrence rate of anomalies. For the web features a value of 0.0025 was established from assessment investigation, experience, and information obtained from engineers at Wright Patterson AFB. This frequency reduction value ensures that the web POFâ&#x20AC;&#x2122;s are below the life limiting inlet airslot feature POF. Once the frequency reduction factor has been established the defect occurrence rate can be determined.

Defect occurrence rate, Îą. The defect occurrence rate must be established to move from the conditional POF to the unconditional POF. The defect occurrence rate is defined by the frequency reduction factor, the anomaly distribution, and the surface area associated with the defect location [7, 8]. The exceedance rate associated with the minimum crack length of the anomaly distribution was utilized to define the defect occurrence proportional to a unit surface area [8]. The surface area associated with each defect location was then necessary to define the defect occurrence as a rate. The defect occurrence rate for the discretization method can be expressed as, đ?&#x203A;źđ?&#x2018;§đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019; = đ?&#x153;?đ?&#x2018;&#x201C;đ?&#x2018;&#x2019;đ?&#x2018;&#x17D;đ?&#x2018;Ąđ?&#x2018;˘đ?&#x2018;&#x;đ?&#x2018;&#x2019; Ă&#x2014; đ?&#x2018; đ?&#x2018;&#x2018; [đ?&#x2018;&#x17D;đ?&#x2018;&#x161;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A; ] Ă&#x2014; đ?&#x2018;&#x2020;đ??´đ?&#x2018;§đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019;

(8)

where đ?&#x153;?đ?&#x2018;&#x201C;đ?&#x2018;&#x2019;đ?&#x2018;&#x17D;đ?&#x2018;Ąđ?&#x2018;˘đ?&#x2018;&#x;đ?&#x2018;&#x2019; â&#x20AC;&#x201C; is the frequency reduction factor of the feature;

đ?&#x2018;&#x2020;đ??´đ?&#x2018;§đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019; â&#x20AC;&#x201C; is the surface area associated with the defect location; đ?&#x2018; đ?&#x2018;&#x2018; [đ?&#x2018;&#x17D;đ?&#x2018;&#x161;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A; ] â&#x20AC;&#x201C; is the exceedance/đ?&#x2018;&#x2013;đ?&#x2018;&#x203A;2 of the minimum crack length of the anomaly distribution [8].

Probabilistic risk determination The fracture mechanics based probabilistic risk assessment was performed in DARWINÂŽ. The probabilistic risk assessment was established by performing a Monte Carlo simulation on each defect location for the fracture mechanics determination of the conditional POF for the representative turbine disk model [7, 8], which was established in sections 2 and 3. From the Monte Carlo simulation the conditional POF was obtained for each defect location of a particular feature. Once the conditional POF was obtained for each of the features, it was essential to determine the unconditional POF. The unconditional POF was established externally via a MATLAB code which was developed. The unconditional POF can be expressed as, đ?&#x2018;˘ đ?&#x2018;&#x192;đ?&#x2018;§đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019; = đ?&#x2018;&#x192;đ?&#x2018;? Ă&#x2014; đ?&#x203A;źđ?&#x2018;§đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019;

(9)

đ?&#x2018;˘ where đ?&#x2018;&#x192;đ?&#x2018;§đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019; â&#x20AC;&#x201C; is the unconditional POF;

đ?&#x2018;&#x192;đ?&#x2018;? â&#x20AC;&#x201C; is the conditional POF; đ?&#x203A;źđ?&#x2018;§đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019; â&#x20AC;&#x201C; the defect occurrence rate [7, 8].

Once the unconditional POF has been determined for each defect location for a feature, the feature risk can be established. The feature risk is established by statistical means, assuming mutually exclusive events [17, 18], as defined in section 4.1. After the representative turbine disk feature risks have been quantified the overall turbine disk component risk can be determined. The disk risk determination was established utilizing a statistical combination of the feature POFâ&#x20AC;&#x2122;s [17, 18], provided in section 4.2.

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Probabilistic feature risk. The probabilistic assessment of the discretized turbine disk yields a POF results for the defect locations. To obtain the total feature risk the POFâ&#x20AC;&#x2122;s of the individual defect locations, as shown for the inlet air-slot in Fig. 17, are statistically combined. The statistical combination is established for a mutually exclusive and/or case [17, 18]. With the statistical combination the feature POF can be expressed as,

đ?&#x2018;&#x192;đ?&#x2018;&#x201C;đ?&#x2018;&#x2019;đ?&#x2018;&#x17D;đ?&#x2018;Ąđ?&#x2018;˘đ?&#x2018;&#x;đ?&#x2018;&#x2019; = 1 â&#x2C6;&#x2019; â&#x2C6;?đ?&#x2018;&#x203A;đ?&#x2018;&#x2013;=1(1 â&#x2C6;&#x2019; đ?&#x2018;&#x192;đ?&#x2018;&#x2013; )

(10)

where i â&#x20AC;&#x201C; is the zone index; Pi â&#x20AC;&#x201C; is the zone POF [17, 18].

This formulation provides a means for establishing the discretized POF of the feature, as shown in Fig. 18 for the inlet air-slot.

Fig. 17. Defect Location Risk w/ Inspection, Inlet Air-slot.

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Fig. 18. Statistical Feature Risk w/ inspection, Inlet Air-slot.

Probabilistic component risk. Once the turbine disk model risk is obtained for the features, the discretized component POF can be obtained. As was done for the feature POF the component POF can be obtained by statistically combining the feature POFâ&#x20AC;&#x2122;s by, đ?&#x2018;&#x192;đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018;&#x161;đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018;&#x2019;đ?&#x2018;&#x203A;đ?&#x2018;Ą = 1 â&#x2C6;&#x2019; â&#x2C6;?8đ?&#x2018;&#x2013;=1(1 â&#x2C6;&#x2019; đ?&#x2018;&#x192;đ?&#x2018;&#x2013; )

(11)

where i â&#x20AC;&#x201C; is the feature index; Pi â&#x20AC;&#x201C; is the feature based POF [17, 18].

The individual feature risks, shown in Fig. 19, are statistically combined to form the turbine disk risk, as shown in Fig. 20.

Fig. 19. Plot of each feature risk with in-service inspections.

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Fig. 20. Plot of total disk risk with in-service inspections.

Feature probability-of-fracture convergence and credibility check. The previous sections have provided the methodology for establishing the discretization and probabilistic risk determination.

This section establishes the methodology utilized for establishing convergence and a credibility check of the discretization of the representative turbine disk model. The convergence studies were performed on the discretization of the representative turbine disk features to ensure the POF results have reach a singular POF solution per flight cycle. Two convergence studies were performed on the probabilistic risk assessment of the representative turbine disk.

One study was performed to determine the required number of samples for the Monte Carlo simulation to ensure convergence of the POF per flight cycle. The second convergence study was performed to establish the number, or density, of defect locations utilized for the discretization of the representative turbine disk model. The credibility check of the discretization method was performed by comparing the results obtained from the discretization method with the FAAâ&#x20AC;&#x2122;s life limiting method. The convergence study is necessary to establish the accuracy of the POF results obtained from the probabilistic risk assessment of the turbine disk. Meanwhile, the credibility check was established to evaluate the discretization method in comparison with the FAAâ&#x20AC;&#x2122;s life-limiting method.

Feature probability-of-fracture convergence. A convergence study of the discretized representative turbine disk was necessary to ensure that the POF of the defect locations and the features approach the risk solution limit. Two convergence studies of the POF for the turbine disk are necessary.

The first convergence study required was on the number of Monte Carlo samples utilized in the probabilistic risk assessment. The second convergence study that was necessary was for the feature POF based on the number, or density, of defect locations. These two convergence studies provide evidence which ensures that the model results are converging to a singular solution per flight cycle.

The first convergence study that was performed was on the number of Monte Carlo samples for the probabilistic risk assessment [7, 8]. This convergence study was performed to ensure that the number of random Monte Carlo samples were adequate to capture the POF of the defect location. According to Immarigeon and Graham, there should be enough samples to ensure that 1 in 1,000 components develop a life-limiting crack [2, 14]. The convergence study of the number of samples for the Monte Carlo simulation was performed. It was determined that a Monte Carlo simulation with 100,000 samples was adequate for the probabilistic risk assessment of the representative turbine disk.

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Next, a convergence study was performed on the number of defect locations within a given feature.

However, there is more to the convergence study than just adding more defect locations. According to Millwater et. all, the identification of the defect locations requiring refinement is a key ingredient for the refinement [3]. For the probabilistic risk assessment, the defect locations should have nearly equal risk contribution factors (RCF) [3]. An initial run was performed for each feature and the feature POF was obtained. From the POF results of the probabilistic risk assessment a pie chart of the defect locations RCF’s was created, i.e. the inlet air slot as shown in Fig. 21.

Defect locations which have RCF’s greater than 5%, also called the RCF limit, are candidates for refinement [3]. For the risk assessment of the inlet air-slot containing 30 defect locations, as shown in Fig. 21, there is a large piece of the pie associated with one defect location, well above the RCF limit. To reduce the RCF at this defect location the area associated with the defect location was split into two, thus adding another defect location to the feature.

Fig. 21. Defect location POF contribution factors for refinement of the inlet air slot.

This method of refinement was performed for all defect locations with RCF’s greater than the RCF limit. The new surface areas were then determined and associated to the new defect locations and a new probabilistic risk assessment was performed. By investigating the effect of the refinement on the POF per flight cycle a check for convergence can be made. Fig. 22 and 23 show the POF versus flight cycles for the probabilistic risk assessment of the inlet air slot. From the Figs. 22-23 it can be seen that the POF has not converged to a solution for the 30 and 32 defect location risk assessments.

Therefore, the defect location refinement was repeated resulting in 40 defect locations. From the Figs. it can be seen that at this point the defect location RCF’s are nearly equal with no exceedance of the

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RCF limit. Correspondingly, the POF has reached convergence to a solution, as can be seen in Figs.

22 and 23.

Fig. 22. Convergence Plot of POF versus Flights for inlet air slot without inspection.

Fig. 23. Convergence Plot of POF versus Flights for inlet air slot with inspection.

This confirms that convergence of the feature risk has been attained. The convergence procedure was repeated for each of the features which make up the representative turbine disk. Once the Convergence of the Monte Carlo simulation and the feature risk of the component have been obtained the representative turbine disk POF can be established, in accordance with equation 11 of section 4.2.

This generates the overall risk, or POF, for the component. Next, the component POF for the discretization of the representative turbine disk can be compared with the component POF results from the life-limiting approach recognized by the FAA. Feature probability-of-fracture credibility check. To check the credibility of the discretization method developed within this report, the POF results for the discretized representative turbine disk are compared to the results obtained from the FAA, life-limiting, method. The probabilistic risk assessment was performed for both the discretized method and the life-limiting method utilizing DARWINÂŽ. All analysis input parameters were established similarly for both methods. Therefore, the MMSE Journal. Open Access www.mmse.xyz

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only difference in the probabilistic risk assessment was the use of either the life-limiting location of a feature or the discretized feature, containing multiple defect locations.

The FAA’s prescribed method utilizes the life-limiting location of a feature to establish the operational risk of the turbine disk. The life-limiting location of a feature is the location of the highest stress in the feature [6, 8]. Table 1 shows the probabilistic risk results for the life-limiting location of each of the representative turbine disk features. Of these, the FAA methodology utilizes only the most lifelimiting location to define the component POF [6]. Unlike the discretization method, the FAA lifelimiting method takes the entire surface area of the feature and the highest max principal stress, called the life-limiting stress, and projects it throughout the feature [6, 8]. This means that the entire feature is defined by a single defect location, the life-limiting stress location, associated with the entire surface area of the feature. In the case of the representative turbine disk this corresponds to the inlet air slot. Through the life-limiting location approach the component risk, which corresponds to the inlet air slot POF, was determined to be 2.06E-6.

The FAA life-limiting method provides a relative risk value, which does not account for the stress gradient topology of a particular feature. The discretization method allows for the stress gradient topology to be captured in the risk assessment, thus moving towards an absolute risk value. This is important as the U.S. Air Force considers the use of RFC to safely extend component operational life beyond the LCF limit of the safe life method.

The discretization of the representative turbine disk was established in section 3, with the probabilistic risk determination defined in section 4. The feature risk values obtained from the probabilistic risk assessment of the representative turbine disk are provided in table 1. The resulting operational risk of the inlet air slot was found to be 4.84E-7. This risk value is smaller in comparison to the inlet air-slot risk value obtained by the FAA life-limiting method. The change in the risk results from the discretization method’s ability to capture the stress gradient topology producing a more accurate risk for the feature. Whereas, the FAA life-limiting method assumed the limiting stress was constant throughout the entire surface area of the feature. Fig. 24 exhibits the difference in the feature RCF’s for the probabilistic risk assessment. As can be seen the life-limiting method employed by the FAA utilizes only one defect location to describe the entire turbine disk, while the discretized method provides a more equal contribution of all features to the component risk value.

One very interesting result to be mentioned is that the turbine disk POF for the discretization method was close to the FAA life-limiting method. There are many possible factors which may have led to this result. For example, the web features utilized the same default anomaly distribution as the circular-hole features. The difference was that the frequency reduction factor was established based on experience and a best guess. A change to the web anomaly distribution or frequency reduction factor could result in a change in the similarity of risk values. Therefore, a conclusion cannot be easily drawn on this happenstance; rather it could be a coincidence of the approximation of some of the analysis parameters of the probabilistic risk assessment. A conclusion that can be drawn though is the fact that the risks of the features are lower for the discretization method than that of the life-limiting approach. This occurred because the discretization method accounts for the stress gradient topology which removes some level of conservatism from the risk assessment in an effort to move towards an absolute risk value. Regardless, this information provides a credibility check for the proposed methodology, the discretization of a turbine disk for probabilistic risk assessment.

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Table 1. Comparison of the end life POF with inspection for the life limiting approach and the proposed discretization approach to the probabilistic risk assessment of the representative turbine disk.

Fig. 24. Feature contribution charts for the life limiting and discretization methods for the probabilistic risk assessment of the representative turbine disk.

Summary. There is an economic benefit to safely extend the operational life of turbine engine components. Advances in computational tools and scientific knowledge have provided the capability to determine the probabilistic risk involved in operational usage of turbine engine components. One such computational tool that has been developed is the probabilistic risk assessment software package DARWINÂŽ, the Design Assessment of Reliability With INspection. This program was created in conjunction with the FAA to establish a damage tolerance approach extension of the safe life method.

The endeavor to establish a damage tolerance approach was a result from the accident at Sioux City in 1989, in which a catastrophic engine failure occurred due to manufacturing induced anomalies that degraded the integrity of a high energy rotor disk [4]. The damage tolerance approach and DARWINÂŽ were developed to establish the capability to utilize NDI techniques and account for the manufacturing induced anomalies [4, 6, and 7]. However, the safe life and the damage tolerance approaches provide conservative approximations for the operational risk of turbine engine components.

To safely extend the operational life of turbine engine components the conservatism of the current lifing methods must be reduced. The proposed method establishes the capability to reduce the conservatism of the lifing methods by moving from the relative risk calculations to an absolute risk calculation through the feature based discretization of a turbine disk. The discretization provides the means to capture the max principal stress gradient topology of the component features for the probabilistic risk assessment. For the feature based discretization, the turbine disk is initially separated into the major component features. These features are then discretized through the introduction of defect locations, which were constructed by means of the max principal stress gradient MMSE Journal. Open Access www.mmse.xyz

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topology. These defect locations are placed such that the surface area associate with each defect location exhibits a univariant stress gradient.

Some general guidelines, for the introduction of the defect locations, were developed through the investigation of the discretization of a representative turbine disk. For the turbine disk features it was established that in the high stress gradient regions, where the stresses produce stress intensities above the stress intensity threshold, for every 1 ksi in the transverse direction of the feature a defect location set was necessary. Yet, in low stress gradient regions, where the stresses produce intensity factors below the stress intensity threshold, a defect location set was necessary only every 15 ksi in the transverse direction of the feature. The defect location sets should contain corner crack type defect locations at the edges of the feature and any number of surface crack type defect locations on the surface between the edges. As a general guideline it was determined that, for a defect location set, every 1.5 ksi thru the feature only one surface defect was required. These guidelines are meant to provide a starting point for the assessment, further refinement of the defect locations may be necessary to obtain convergence.

For the discretization of a representative turbine disk a convergence study was performed to ensure the assessment reaches the solution. The convergence study was performed utilizing the risk contribution factor, RCF, of the defect locations in a particular feature. If the RCF of a defect location exceeded the RCF limit, approximately 5%, then the surface area of that defect location was divided into two areas and a new defect location was introduced. The feature POF, which was established by the statistical combination of the risks of all defect locations in the feature, was utilized to verify convergence. Once all defect locations have RCF values below the RCF limit or the feature risk no longer changes then convergence was obtained.

A credibility check of the proposed method for the discretization of a turbine disk for the probabilistic risk assessment was performed by comparing the risk results with those obtained by performing the FAA recognized life-limiting approach. It was shown that the probabilistic risk for the discretization of the turbine disk was close to, yet lower than the results obtained from the life-limiting approach.

This was expected due to the move from a relative risk to an absolute risk of service for the representative turbine disk. This report provides the method and approach for the reduction of the conservatism found in current lifing methods. The discretization method can be employed in the investigation for the safe extension of turbine engine components operational life beyond the LCF limit.

Nomenclature AC – Advisory Circular

AFB–

Air Force Base

CC11 – Univariant Corner Crack type, DAR- D – Feature diameter WIN® DARWIN® – Design Assessment for Reliabil- FAA – Federal Aviation Administration ity With INspection FCG – Fatigue Crack Growth

FEA – Finite Element Analysis

L – Feature length, or depth

LCF –.Low Cycle Fatigue

NDI – Non-Destructive Inspection

POD – Probability Of Detection

POF – Probability-Of-Fracture (Failure)

RCF – Risk Contribution Factor

RFC – Retirement For Cause

SA – Surface Area

SC17 – Univariant Surface Crack type, DAR- SWRI WIN® odb – Output database file

– South West Research Institute

r – Radius

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đ?&#x2018;&#x17D;đ?&#x2018;&#x161;đ?&#x2018;&#x2013;đ?&#x2018;&#x203A; â&#x20AC;&#x201C; Minimum crack size of the anomaly dis-

t â&#x20AC;&#x201C; Thickness

tribution

đ?&#x2018; đ?&#x2018;&#x2018; â&#x20AC;&#x201C; Exceedance rate from the anomaly distri- Pcomponent â&#x20AC;&#x201C;Component level probability-offailure

bution

Pfeature â&#x20AC;&#x201C; Feature level probability-of-failure Pi â&#x20AC;&#x201C; Defect location probability-of-failure Pc â&#x20AC;&#x201C;Conditional probability-of-failure

Pu â&#x20AC;&#x201C; Unconditional probability-of-failure

đ?&#x2018;&#x2018;đ?&#x2018;&#x17D;

Îą â&#x20AC;&#x201C; Defect occurrence rate

đ?&#x2018;&#x2018;đ?&#x2018;

â&#x20AC;&#x201C; Fatigue

Î&#x201D;đ??ž

crack growth rate

â&#x20AC;&#x201C; Change in

stress intensity factor

Î&#x201D;đ?&#x2018;Ľ â&#x20AC;&#x201C; Change in global x-direction

Î&#x201D;đ?&#x2018;Ś â&#x20AC;&#x201C; Change in global y-direction

Î&#x201D;đ?&#x2018;§ â&#x20AC;&#x201C; Change in global z-direction

ν â&#x20AC;&#x201C; Frequency reduction factor

-3Ď&#x192; â&#x20AC;&#x201C; Lower 3 standard deviation, value of lower confidence bound

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[2] Immarigeon, J-P., Koul, A.K., Beres, W., Au, P., Fahr, A., Wallace, W., Patnaik, P.C., Thamburaj, R., â&#x20AC;&#x153;The Aging Engines: An Operatorâ&#x20AC;&#x2122;s Perspectiveâ&#x20AC;?, NATO-RTO-AVT Lecture Series 218, October 2000.

[3] Millwater, H., Enright, M., Fitch, S., â&#x20AC;&#x153;Convergent Zone Refinement Method for Risk Assessment of Gas Turbine Disks Subject to Low-Frequency Metallurgical Defectsâ&#x20AC;?, Journal of Engineering for Gas Turbine and Power, July 2007, Vol. 129.

[4] â&#x20AC;&#x153;Damage Tolerance for High Energy Turbine Engine Rotorsâ&#x20AC;?, Federal Aviation Administration Advisory Circular 33.14-1.

[5] â&#x20AC;&#x153;Guidance Material for Aircraft Engine Life-Limited Parts Requirementsâ&#x20AC;?, Federal Aviation Administration Advisory Circular 33.70-1.

[6] â&#x20AC;&#x153;Damage Tolerance of Hole Features in High-Energy Turbine Engine Rotorsâ&#x20AC;?, Federal Aviation Administration Advisory Circular 33.70-2.

[7] Southwest Research Institute, â&#x20AC;&#x153;DARWIN 7.0 Userâ&#x20AC;&#x2122;s Manualâ&#x20AC;? 2010.

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[9] Vukelich, S., â&#x20AC;&#x153;Engine Life Extension Through the Use of Structural Assessment, Non-Destructive Inspection, and Material Characterizationâ&#x20AC;?, NATO-RTO-MP-079(11) Lecture Series, October 2001.

[10] Immarigeon, J-P., Koul, A.K., Beres, W., Au, P., Fahr, A., Wallace, W., Patnaik, P.C., THamburaj, R., â&#x20AC;&#x153;Life Cycle Management Strategies for Aging Enginesâ&#x20AC;?, NATO-RTO-MP-079(11) Lecture Series, October 2001.

[11] High Temp Materials, â&#x20AC;&#x153;Inconel 718 Technical Dataâ&#x20AC;?, High Temp Materials, September 2011, http://www.hightempmetals.com/techdata/hitempInconel718data.php [12] Metallic Materials and Elements for Aerospace Vehicle Structuresâ&#x20AC;?, MIL-HDBK-5H, 1998 [13] Tong, Yu C., â&#x20AC;&#x153;Literature Review on Aircraft Structural Risk and Reliability Analysisâ&#x20AC;?, DSTOTR-1110, February 2001.

[14] Graham, A.D., Mallinson, G.D., Tong, Y.C., â&#x20AC;&#x153;NERF-A Tool for Aircraft Structural Risk Analysisâ&#x20AC;?, ICASP8, Manly, December 1999.

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[15] Harmon, D. M., and Saff, C. R. “Damage Tolerance Analysis for Manned Hypervelocity Vehicle.” Vol. I, Wright Research and Development Center, Wright-Patterson Air Force Base, Ohio, pg.

1-164, Sept. 1989.

[16] Oyelakin, J.O., “On The Fracture and Fatigue Crack Growth of Thin Sheets of Nanocrystalline Metal Alloys”, University of Illinois, 2010.

[17] Kappas, J., “Review of Risk and Reliability Methods for Aircraft Gas Turbine Engines”, DSTOTR-1306, May 2002.

[18] Millwater, H.R., Osborn, R.W., “Probabilistic Sensitivities for Fatigue Analysis of Turbine Engine Disks”, International Journal of Rotating Machinery, Article ID 28487, Volume 2006.

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