Br. J. Anal. Chem., 2018, 5 (20), 1-1 DOI: 10.30744/brjac.2179-3425.2018.5.20.1-1
Editorial
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Quo Vadis, Analytical Chemistry? Marco Aurélio Zezzi Arruda Full Professor Institute of Chemistry,University of Campinas (Unicamp), SP, Brazil zezzi@unicamp.br This title is paraphrased from an article published in 2016 by Prof. Miguel Valcárcel, one of the most renowned experts in analytical chemistry in the world, in which he puts in evidence analytical chemistry as a dynamic scientific area. As science is always reinvented, all scientific areas need to be readapted from time to time to remain active, producing knowledge with quality, and to meet the needs of their community and overall society. Thus, the issue of transdisciplinarity is visibly clear today. Within this context, and particularizing analytical chemistry, methods based on biological based-systems are gaining more and more attention, so that this year's Nobel Prize in chemistry was focused in such a direction. Thus, bioanalytical methods, focusing on bioaccessibility, nanomaterials, single cell evaluation, (bio)imaging, omics, health care, and microfabrication, are some examples that should be further explored within analytical chemistry in a more regionalized context, including in Brazil and Latin America. It is a fact that such applications are more present in regions such as North America, Europe, and Asia. Nonetheless, they would be most welcome in more regionalized contexts, such as tropical diseases and regionalized food samples, but with an export appeal, among others. Thus, combining the useful with the latest trends, analytical chemistry can contribute, effectively and with novelty, to the solution of regional problems, which is important for our society. Thus, trying to answer the initial question, analytical chemistry will go to where real problems exist (whether inside or outside the laboratory), always aiding society, environment, and academia. The articles that compose this volume of the BrJAC exemplify, in part, the question Quo Vadis, Analytical Chemistry? So enjoy the read!!
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Br. J. Anal. Chem., 2018, 5 (20), pp 2-6 DOI: 10.30744/brjac.2179-3425.2018.5.20.2-6
Interview
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Professor Nelson Stradiotto, whose career has been marked by an effective contribution in the training of human resources for science, recently spoke with BrJAC Nelson Ramos Stradiotto Full Professor at the Institute of Chemistry, São Paulo State University (UNESP) Araraquara, SP, BR nrstradi@iq.unesp.br Prof. Dr. Nelson Ramos Stradiotto is a chemist who graduated in 1969 from the University of São Paulo (USP), Brazil. In 1975 he became a Master in Physical Chemistry and in 1980 a Doctor in Physical Chemistry while at USP. In 1991 he presented his free-docency thesis and in 1994 he became a Full Professor at USP. He was a professor of chemistry from 1971 to 1998 at USP and from 1998 to 2015 at the São Paulo State University “Júlio de Mesquita Filho” (UNESP), Brazil. He conducted postdoctoral work from 1983 to 1984 at the University of Southampton, UK, and was a visiting researcher at the Universities of Loughborough (1992–1994) and Oxford (2008–2009), UK. He is currently a volunteer professor at UNESP and a visiting professor at the Fluminense Federal University, Volta Redonda, RJ, Brazil. He has excelled in the development of research in the fields of Analytical Chemistry and Physicochemistry, with his specialty in Electrochemistry and Electroanalysis. The subject of his current research is related to sensors, electrochemical detectors coupled to chromatographic techniques, and electroanalytical methods in the bioenergy area, with emphasis on biofuels, bioproducts, biomass, and bio-refineries. In addition, he has been a prominent professor, having contributed to the scientific careers of more than 50 students, more than 30 masters and more than 20 doctors. He also published more than 150 scientific papers, 5 book chapters and 2 books, and presented more than 300 papers in annals of scientific congresses. With his critical and balanced thinking, he has assisted university institutions in finding solutions for technical and administrative issues, in the development of scientific knowledge, and in the training of human resources. As a result of the respect of his peers, he was nominated to coordinate the “Bioenergy Project”, developed at UNESP jointly with the University of Campinas (UNICAMP) and USP, as well as representing UNESP at the Institute of Studies Brazil Europe (IBE). When was your first contact with chemistry? Did you have any influence, such as a teacher? My first interest in science was manifested by reading the comic magazine (cartoon/magazine made with drawings) entitled “Ciência em Quadrinhos” (Science in Comics) published between 1953 and 1958 by “Editora Brasil-América” (Ebal). It was a magazine that explained concepts of physics such as electricity and nuclear energy, as well as topics such as the history of civilization and the animal world. However, my first real contact with chemistry was during the Technical Course in Industrial Chemistry, at the “Associação de Ensino de Ribeirão Preto” (Teaching Association of Ribeirão Preto), where I studied as a scholarship student. There, it was vital to maintain a high academic standard, which was difficult because of the highly demanding nature of the course. We had excellent teachers, namely Prof. João Alvares da Costa who, along with the other teachers of this secondary school, showed us the greatness and beauty of chemistry. 2
Br. J. Anal. Chem., 2018, 5 (20), pp 7-8 DOI: 10.30744/brjac.2179-3425.2018.5.20.7-8
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Nano-Strategies in Analytical Chemistry Henrique E. Toma Full professor Institute of Chemistry, University of São Paulo (USP), SP, Brazil henetoma@iq.usp.br
Nanotechnology is impacting all the areas of Science, providing high performance materials and techniques, and introducing new concepts from the nanoscale. In particular, the great development of the electronic and scanning probe microscopies brought about chemical analysis into a new dimension, allowing to probe directly the composition and properties of the samples at the atomic/molecular level. Even classic optical microscopy has been renewed by incorporating dark field and confocal design, laser sources for excitation, and CCD detectors for recording the electronic and vibrational spectra of micro/ nanosize samples. Such advances allowed to access the molecular map from the hyperspectral images of the samples, by storing a complete spectrum into every single pixel. A typical example is the classical Feigl's spot test analysis of nickel(II) and palladium(II) with dimethylglyoxime (Hdmg). [Ni(Hdmg)2] is a red planar complex, susceptible to attack of acids, while [Pd(Hdmg)2] has a yellow color, and is acid resistant. While the red color of the [Ni(Hdmg)2] disappears when exposed to acids, palladium ions, even in trace amounts, are able to protect the complex, preserving its original color. This fact has been explored by Feigl to develop a specific analytical test for palladium. Confocal Raman microscopy studies revealed that [Ni(Hdmg)2] consists of wires of stacked molecules, with an external hydrophobic coating of methyl groups, leaving only the extremities exposed to the attack of acids. According to the hyperspectral images, this is the site occupied by the palladium complex, thus explaining the protection mechanism involved in Feigl's test [1]. Surface plasmon resonance (SPR) is being currently explored in analytical chemistry as a very sensitive technique for investigating adsorption and molecular interactions, specially at the electrodes. It is based on the interaction of the surface plasmons of metals such as gold, with the light evanescent waves projected at specific angles, and can be easily adapted to monitor the electrochemical processes at the surface. A similar plasmon resonance effect is observed in the interaction of gold plasmonic nanoparticles with light, leading to an enhancement of the local electric fields and light scattering, responsible for the rise of strong colors which can be monitored spectrophotometrically. The coupling of plasmonic nanoparticles can be chemically induced, giving rise to new extinction bands in the visible. This effect has been successfully explored in chemical and biochemical analysis, extending in many orders of magnitude the sensibility of the analytical tests. Plasmonic nanoparticles also exhibit strong surface enhanced Raman effect or SERS [2,3]. Such effect involves three mechanisms: a) electromagnetic, typical of physical adsorption of the analytes, and b) chemical, involving the interaction of the analytes with the surface by means of charge-transfer or resonance absorption interactions. The electromagnetic effect is less specific, leading to a general enhancement of the adsorbed molecule vibrational peaks, while the charge-transfer and resonance Raman effects respond to specific chromophores in the molecules. Both mechanisms provide interesting analytical applications in chemistry and biology. In many favorable cases, the combined mechanisms lead to a huge enhancement of the Raman signals, up to 14 orders of magnitude, reaching the single molecule detection limit.
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Nowadays, the use of nanoparticles in Electroanalytical Chemistry is already a very common practice. As a matter of fact, nanoparticles provide very large surface areas and can be suitably functionalized for coating electrodes and improving their chemical and electrochemical performance. Typical nanoparticle cores are made up of inorganic materials such as gold, silver, TiO2, Fe3O4 (magnetite) and γ-Fe2O3 (maghemite). Carbon nanomaterials also employed in electroanalytical chemistry comprise activated carbon, carbon nanotubes, fullerenes, graphene, graphene oxide, reduced graphene oxide, nanodiamonds and carbon quantum dots [4]. A special case is provided by the functionalized Fe3O4 superparamagnetic nanoparticles. After interacting directly with the analytes in solution, they can be magnetically confined at the electrode surface, with the aid of an external miniature strong magnet (e.g. Nd2Fe14B). The magnetic confinement approach [5] increases the electrochemical response, similarly to the classical stripping methods in analytical chemistry; however, it has a much broader and general use, allowing to explore the preconcentration effect for any species and electrode materials (gold, platinum, carbon, etc.). Such process has also proved very efficient as a greener alternative for hydrometallurgy [6]. Similarly, superparamagnetic nanoparticles have also been successfully employed as versatile support for catalysts, particularly the enzymes, for analytical purposes and industrial processing [7].
REFERENCES 1. Huila, M. F. G.; Lukin, N.; Parussulo, A. L. A.; Oliveira, P. V.; Kyohara, P. K.; Araki, K.; Toma, H. E. Anal. Chem., 2012, 84, pp 3067-3069. 2. Grasseschi, D.; Toma, H. E. Coord. Chem. Rev., 2017, 333, pp 108 -131. 3. Aroca, R. F. Surface -Enhanced Vibrational Spectroscopy, John Wiley & Sons, Ltd., Chichester, 2006. 4. Canevari, T. C.; Cincotto, F. H.; Gomes, D.; Landers, R.; Toma, H. E. Electroanalysis, 2017, 29, pp 1968-1975. 5. Condomitti, U.; Zuin, A.; Novaki, M. A.; Araki, K.; Toma, H. E. Electrochem. Commun., 2011, 13, pp 72-74. 6. Toma, H. E. Green Chem., 2015, 17, pp 2027-2041. 7. Netto, C. G. C. M.; Toma, H. E.; Andrade, L. H. J. Mol. Catal. B: Enzym., 2013, 85-86, pp 71-92.
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Br. J. Anal. Chem., 2018, 5 (20), PP 9-11 DOI: 10.30744/brjac.2179-3425.2018.5.20.9-11
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A Current Shot and Re-thinking of Antioxidant Research Strategy
Alessandra Durazzo, PhD Researcher CREA - Research Centre for Food and Nutrition, Roma, IT alessandra.durazzo@crea.gov.it ORCID: http://orcid.org/0000-0002-774 7-9107
Massimo Lucarini, PhD Researcher CREA - Research Centre for Food and Nutrition, Roma, IT massimo.lucarini@crea.gov.it ORCID: http://orcid.org/0000-0001-6178-9779
Antioxidant properties are an expression of the interactions between bioactive molecules and other components of a food matrix and they can be considered as the first action for the comprehension of potential beneficial properties of food matrices in the perspective of healthy choices. ln this regard, it is important to underline how the identification, isolation, and quantification of biologically active compounds present in food matrices is required as starting point in the study of antioxidant properties and this is followed by assessment of their interactions. The actual possibilities for approaching a study about antioxidant properties in foods are summarized and described in Table 1. A "study approach" is intended here as the direction of a research strategy and a design to indicate the features that one wants to investigate.
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Table I. The main workflow for investigation of antioxidant properties
Study Approach
Description
Study and development of a model system of interactions.
Monitoring pure bioactive compounds, standards, and their related mixtures leads to the development of a model system for interactions. The interactions can give a combined and synergistic effect, an antagonistic effect, or no additional effect. This behavior was generally affected by different variables such as the chemical structure and profile of antioxidants and also the nature and characteristics of the food matrix.
Study of extractable and non-extractable compounds.
Antioxidants arise as easily extractable compounds -free forms that are soluble in aqueous-organic solvents- and as less extractable compounds -bound forms that remain in the residue of aqueous-organic extract. In the last decade, the occurrence of antioxidants in raw and cooked foodstuffs and in processed products has been studied. Due to the concomitant action of different factors, it is difficult to identify and categorize the main trends in the contribution of extractable and non extractable compounds to the total antioxidant capacity in main food groups. In general, research has pointed out that analysis of compounds remaining in residues is required. Particular attention should be given to high fat food matrices and complex food matrices.
Study of bioactive compounds-rich extracts.
Isolation of bioactive compounds-rich extracts and determination of their contribution to the antioxidant properties of a food matrix should be carried out. For each food, one or more fractions can be isolated and qualitatively and quantitatively characterized . In this way, the minor or major contributors to the antioxidant properties can be identified. The information from all fractions could be considered as an indicator of the antioxidant properties of a food matrix.
In recent years, these types of approaches are being carried out in several studies and in works along various food groups and at different levels of the food chain and also in less common foods. In particular, the importance of both extractable and non-extractable antioxidants has reached a consensus in the scientific community and the development and assessment of new methodologies has been achieved. Nowadays researches, in the perspective of circular economy and biorefinery, on extractable and non-extractable antioxidants in food wastes [1,2], as well as in direction of nutraceutical applications [3, 4] are addressed. Generally, studies on the evaluation of antioxidant properties should be integrated into a multidisciplinary and innovative study design for food research, where innovative and green procedures and technologies are combined with statistical methods. For instance, applications of infrared spectroscopy coupled with chemometrics applied to extractable and non-extractable compounds are emerging [5,6]. Also, a proper assessment of the contribution of extractable and non-extractable compounds in the dietary intake is required [7]. The overall goal is the development of dedicated databases as well as the inclusion of extractable and non-extractable compounds in harmonized food composition databases in order to an adequate dietary intake assessment. Studies on this direction are carried out in eBASIS [8].
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P o in t o f V iew
B r. J . A na l. C he ,m2.01 8, 5 (20), p p 0 0 -00 D O I: 10 .3 07 4 4 /b rjac .2 17 -34 9 25 .2 0 18 .5 .20 .i-f
REFERENCES 1. Esparza-Martínez, F. J.; Miranda-López, R.; Guzman-Maldonado, S. H. Ind. C rop. Prod., 2016, 84, pp 1-6. 2. Leão, D .P .; Franca, A . S.; O liveira, L. S. .; B astos, R .; C oim bra, M. A . F ood C hem., 2017, 225 , pp 146 -153. 3. González-Sarrías, A.; Espín, J. C; Tomás-Barberán, F. A . Trends in F ood S. ci . T echnol, 2017, 69, pp 281-288. 4. Y an, S .; S hao, H .; Z hou, Z .; W ang, Q .; Z hao, L.; Y ang, X . J. F unct. F oods, 2018, 42, pp 129 -136. 5. dos S antos G rasel, F .; Ferrão, M. F .; W . olf, C. R . S pectrochim . A cta , P art A, 2016, 153, pp 94-101. 6. Nogales-Bueno, J.; Baca-Bocanegra, B.; Rooney, A.; Miguel, J.; Hernández-Hierro, J. M..; H eredia, F . J.; B yrne, H . J. T alanta, 2017, 167, pp 44-50. 7. P into, P .; S anto, C . N . E ur. J. N utr. , 2017, 56, pp 1393-1408. 8. D urazzo, A .; P lum b, J.; Lucarini, M .; F ernandez-Lopez, G .; C am illi, E .; T urrini, A .; F ing las, P .; M arletta, L. E xtractable and -non extractable antioxidants at the interface of eB A S IS structur e: database developm ent and expansion. P oster . presented at: E uroFIR : F ood F orum , 2018, B russels, B elg ium .
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Br. J. Anal. Chem., 2018, 5 (20), pp 12-13 DOI: 10.30744/brjac.2179-3425.2018.5.20.12-13
Letter
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Nanoscience and Nanotechnology - A True Revolution in the Way of Thinking Nature Aldo José Gorgatti Zarbin Full Professor - Materials Chemistry Group (GQM) Department of Chemistry - Federal University of Paraná (UFPR) Centro Politécnico, Curitiba, PR, Brazil aldozarbin@ufpr.br The scientific knowledge produced in the last decades of the 20th century were strongly characterised by coming and the consolidation of a novel way to treat the matter, reaching for an understanding of the innovative phenomena and properties arising from the bottom. Nanoscience and Nanotechnology (N&N) represented a true revolution in the way of thinking nature, and brought us a myriad of possibilities for the application of so-called nanomaterials in novel technological devices and systems. Nanoscience can be understood as the science dealing with the phenomenon whereby the properties of materials are strongly dependent on their size. Materials with particles below a critical size – in the range of nanometres – present properties that are different from the same materials as a bulk, which means that unique materials (and new properties) can be designed simply by selecting different particle sizes. Notwithstanding the paper published by Michael Faraday in 1857, in which the different colours of colloidal gold (blue, purple, green) were associated with the different sizes of gold particles (which in the personal opinion of the signatory of this letter represents the outset of the N&N), or the lecture given by Richard Feynman during the 29th Meeting of the American Physical Society in 1959 calling on scientists to dedicate more efforts to the understanding of matter at very small sizes, the relationship between size and properties started to become important only at the end of the 1980s, reaching a boom in the last decade of the twentieth century that remains to date. Nanoscience brought with it nanotechnology, in which products, systems and devices produced by it represent the fastest growing market in the world nowadays. The global nanotechnology market was approximately US$ 39.2 million in 2016 and is expected to reach 90.5 billion by 2021 and exceed 125 billion by 2024, according the Research and Markets company report released in 2018. Nanoscience and nanotechnology represent a perfect example of inter- and trans-discipline fields. It is not excessive to say that N&N passes through all of the knowledge areas and directly impacts almost all fields: energy, medicine, agriculture, environment, goods and services, manufacturing, personal care, health, electronics, textiles, chemicals, computers, materials, communication, transportation, defence, entertainment… and so on. As expected, chemistry has played a central role in all of the steps of N&N development and consolidation. First, by solving the core problem related to the synthesis of stable nanomaterials. Chemists have been developing several creative strategies to work around the intrinsic thermodynamic instability of nanomaterials, and have making the preparation of different materials in a nanometric scale possible, with rigorous control of the size dispersion and stability. Second, chemists have been working together with physicists, engineers, biologists, material scientists, and mathematicians, among others, to help to understand the physical phenomena behind the experimental data, as well as the development of novel and sophisticated characterisation techniques. Nanochemistry belongs to all the traditional subfields of chemistry, with analytical chemistry being one of the most participative. The global community of analytical chemists quickly understood the importance
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and inďŹ nite number of possibilities of that emerging knowledge and incorporated it to their day-to-day work. Novel sensors showing unbelievable detection limits of single molecules have been produced; classical problems have been solved, multi-detection techniques have been developed, and a new challenge has been proposed: the detection and understanding of the environmental and health issues directly associated with these novel classes of nanomaterials. Following the global tendency, Brazilian analytical chemists have also been presenting important contributions in the N&N, and this special edition of the Brazilian Journal of Analytical Chemistry is a clear demonstration of that. As a materials chemist who has dedicated his entire scientiďŹ c work to dierent aspects of the synthesis, characterisation and application of nanomaterials (including several directly related to Analytical Chemistry), I am very proud to recognise the strength of this community, as well as the beauty, originality and relevance of nanoscience and nanotechnology associated with analytical chemistry developed in Brazil. Congratulations to the editors for the initiative.
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Br. J. Anal. Chem., 2018, 5 (20), pp 14-16 DOI: 10.30744/brjac.2179-3425.2018.5.20.14-16
Letter
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Shouldn't we be using more capillary electrophoresis nowadays? José Roberto Rodrigues de Souza School of Pharmaceutical Science University of São Paulo (USP), SP, Brazil roberto_souza@usp.br
Maria Segunda Aurora Prado Professor at the School of Pharmaceutical Science University of São Paulo (USP), SP, Brazil msaprad06@usp.br
Capillary Electrophoresis (CE) has been used for different and specific applications presenting also some specific advantages, but it is still an underestimated technique in the analytical fields. We have explored recent applications and advantages of CE use in Science and some comparisons to other techniques. The search for greener methods and technologies, which could avoid unnecessary use of chemicals and toxic substances, is an important and current issue in Science. Capillary Electrophoresis (CE) is nowadays still an underestimated technique in the analytical field. Many papers have described the advantages of the technique in comparison with high performance liquid chromatography (HPLC) for some cases. Some of those could be described as composing of a relatively simple equipment, cheap capillary columns, fast separations, wide spectrum of analytes types that can be analyzed, simple sample preparation and maybe one of its best advantages is that it is a much cleaner method compared to HPLC [1,2]. Regarding the use of organic solvents, CE will require lower amounts compared to HPLC, and many analyses can be conducted only in aqueous media. CE can also be coupled to many detection formats such as MS detection, UV absorbance, electrochemical and others, what makes it so useful as HPLC, sometimes for the same applications. HPLC is undoubtedly a powerful technique that has multiple applications but CE has gained more attention in the last years due to its advantages and for specific applications. We have listed some of its recent applications in different analytical fields (Table I). Wang et al. [2] have reviewed CE applications for vitamins analysis. They observed that Microemulsion electrokinetic chromatography (MEEKC) or Capillary electrochromatography (CEC) were the best CE techniques to analyze fat-soluble vitamins and could be used in the simultaneous determination of watersoluble and fat-soluble vitamins even though vitamins analysis by CE showed to be limited in its sensitivity.
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Table I – Recent applications in Capillary Electrophoresis
Hemoglobinopathy screening
You-Qiong et al., 2016
Vitamin analysis
W ang et al., 2018
Serum N-glycans identification
Snyder et al., 2017
Clinical metabolomics
Ramautar, 2016
Enantioseparation
Zhang, 2018
Serum proteins analysis
Regenite & Siede, 2018
Drug discovery
Farcaş et al., 2017 F
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CE has also been used for serum analyses [1,3]. You-Qiong et al. [1] conducted a study to compare detection and quantification of hemoglobin New York by CE and HPLC. All 15 cases (100%) were detected by CE, whereas none was detected by HPLC so, they concluded that CE may be the preferred method for hemoglobinopathy screening in areas with high prevalence of Hb New York. Another important application of CE coupled with mass spectrometry is its use in clinical metabolomics. Ramauter [4] reviewed its use to screen metabolites in biological samples. Enantioseparation has also been studied by CE. Zhang et al. [5] have analyzed the use of ionic liquids (ILs) for CE separation in different modes. They reported that chiral ILs was superior than achiral ones because chiral ILs can usually bring extra enantio recognition capability to the separation. Regeniter & Siede [6] reviewed CE applications for serum protein analysis and they highlighted some CE advantages over agarose electrophoresis. They reviewed the basic concepts to correctly identify irregularities, monoclonal and oligoclonal peaks. According to them, detection of monoclonal components has been largely improved by capillary electrophoresis and it estimates monoclonal peaks more accurately. CE also provided higher resolution and increases sensitivity for the recognition of monoclonal proteins. Drug discovery theme has also been studied with CE applications. Farcaş et al. [7] have recently overviewed the use of CE in this context. They confirmed the low use of CE in this field though it has been seen as a very efficient and resolutive separation technique. Reasons for that were reported to be the relatively low number of experienced CE practitioners, the maturity of HPLC in the pharmaceutical industry and some intrinsic limitations of the technique. They reviewed the use of CE for bioassays, drug-plasma interactions and drug metabolism studies. Some interesting CE applications in this field would be to use a portion of its capillary as a micro-reactor, the study of protein–protein interactions and its use to determine the affinity of a tested drug for the targeted protein. Other CE advantages include high throughput, high speed and low quantities of samples and reagents requirements, making CE a cost-effective technique. Additionally, CE enables the study of non-covalent interactions directly in solution under near physiological conditions. As have been reported in this note, CE represents an efficient, clean and cost-effective technique for many applications. More attention should be paid by the researchers to the use of this technique in their studies and the use in the pharmaceutical industry should be promoted. One of its more important advantages to be pointed is the much lower use of organic solvents and this is becoming a big issue in many research labs. In that way, the search for greener methods is of urgent importance and the increase in the use of CE analytical methods can offer its contribution.
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Br. J. Anal. C hem , 2018 . , 5 (20), pp 00-00 D O I: 10.30744/brjac.2179 -3425.2018.5.20 .i-f
REFERENCE S 1. You-Q iong, L.; Hui -Ping, H.; Zhi -Zhon g, C. Clin. Chem . Lab. M ed., 2016 . , 54 (1), pp 91-95. 2. W ang, X.; Li, K.; Yao, L.; W ang, C.; Van Schepdael, A. J. Pharm . Biom ed. Anal., 2018, 147, pp 278 -287. 3. Snyder, C. M.; Zhou, X .; Karty, J. A.; Fonslow, B. R.; Novotny, M. V.; Jacobson, S. C. J. Chrom atog . . A, 2017, 1523 , pp 127-139. 4. Ram autar, R. Capillary Electrophoresis –Mass Spectro m etry for Clinical M etabolom ics. In: Makowski, G. S. (Ed.). Advances in Clinical Chem istry , v. 74, Elsevier, 2016 , pp 1-34. 5. Zhang, Q . TrAC, Trends Anal. Chem ., 2018 , 100 , pp 145 -154. 6. Regeniter, A.; Siede, W . H. Clin . Biochem., 2018 , 51, pp 48-55. 7. Farcaş, E.; Pochet, L.; Crom m en, J.; Servais, AC.; Fillet, M. J. Pharm . Biom ed. Anal . , 2017, 144, pp 195-212 .
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Br. J. Anal. Chem., 2018, 5 (20), pp 17-25 DOI: 10.30744/brjac.2179-3425.2018.5.20.17-25
Article
Essential Inorganic Ions in Milk-Based Drinks: Evaluation of Bioaccessibility Mirla Cidade1, Solange Cadore2 and Emanueli do Nascimento da Silva2* 1
Chemistry Department, Federal University of Roraima, Boa Vista, RR, Brazil 2 Institute of Chemistry, University of Campinas, Campinas, SP, Brazil
Graphical Abstract
The determination of the bioaccessible fractions of Co, Cu, Mo, Mn, Fe, Zn, Mg and Ca in milk-based drinks (dairy beverages) was carried out using in vitro digestion and quantification by ICP OES. Microwave assisted mineralization was used for sample preparation and the method allowed recoveries between 90 - 110% for all the elements, considering three different levels of analytes addition, with relative standard deviations (RSD) below 10%. The total concentration of Ca determined by the present method was in good agreement with the value declared by the manufacturer while Co was the only element that was below the limit of quantification (LOQ). The bioaccessible fractions for Ca and Mg were approximately 100% while for Cu, Zn, Mn and Fe the bioaccessibility values were 56, 48, 46, and 29%, respectively, and for Co and Mo the values were below the LOQ. Additionally, it was noticed that the bioaccessibility of these elements may vary according to the sample composition.
Keywords: bioaccessibility, milk-based drink, dairy beverages, in vitro digestion, ICP OES INTRODUCTION In Brazil, dairy beverages are defined as a “milky product resulting from the mixture of milk (in natura, pasteurized, sterilized, reconstituted, UHT, concentrated, powder, integral, semi-skimmed or skimmed) and whey (liquid, powder and concentrated), with addition or not of vegetal fat, fermented milk and other dairy products”. The amount of milk on the composition of these beverages should not be less than 51% and, often, fruits or chocolate are added, among other components. About 50% of this drink is consumed over th breakfast. Dairy beverages are in the 4 position of most consumed liquid foods, accounting for 12% of the total daily volume of non-alcoholic liquids. In the last years, this type of beverages has been chosen as a nutritional food to be consumed for children, seniors and also for people who choose a healthy life style [1]. Whey is a by-product from cheese manufacture, representing about 85 to 95% of the total volume of milk, depending on the type of cheese produced, hard, semi-hard or soft [2]. It retains about 55% of the nutrients present in milk [3,4] and was considered for a long time as a residue by dairy industries being often discarded. However, whey has been used as a raw material in the manufacture of various products due to its nutritional characteristics [2,5]. The use of whey to produce dairy beverages contributes to minimize environmental pollution problems, as well as facilitating their consumption. Some authors have reported that 50% of world whey production is treated and processed into different food products, with half of this total being used in the liquid form [6,7]. This usage is mainly in fermented milk beverage that represents 25% of the total market of yogurts in Brazil, which became a very promising market [8]. Considering the large consumption of this type of food and the population growth, better food control is needed, especially those destined for children. Monitoring of the amount of proteins, calories, vitamins and also of inorganic nutrients is necessary since deficiencies of nutrients can alter the activities of the enzymatic and metabolic functions increasing public health expenditures [9]. The food composition is a reasonable indication of its nutritional value; however, it is not enough for a complete characterization considering the *manu_bing@hotmail.com
https://orcid.org/0000-0002-7053-7132
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Essential Inorganic Ions in Milk-Based Drinks: Evaluation of Bioaccessibility
Article
nutritional aspect, because there are few nutrients that are totally available after ingestion. Hence, determining the bioaccessibility and the bioavailability of minerals in diets is important since these terms are associated with the establishment of the intake recommendations of these elements in accordance with the needs of individuals. Thus, this type of studies is used to obtain information on the behavior of the nutrients during the digestion/absorption process [10]. Considering nutritional aspects, bioavailability is the fraction of the nutrient that is available for using in physiological functions or to be stored. This means that bioavailability refers to the fraction that passes through the cell barrier and reaches the bloodstream. It is important to emphasize that bioavailability includes bioaccessibility, which is the fraction of nutrient that is soluble during the digestion and can be absorbed by the body [11-14]. The interest in bioaccessibility of nutrients has been growing in recent years, and many of them have been evaluated in different kinds of food like baby food [15,16], lettuce [17,18], beef [19], coffee [20], berries [21] and cheese [22], using different experimental models of in vitro digestion for obtaining data. Some important issues have been studied such as the influence of the food structures and the synergism or antagonism between food components, as well as the standardization of the methods to evaluate the soluble fractions of a food during the gastrointestinal digestion. Regarding the influence of the food structures of dairy foods, several authors described that the amount of nutrient released during the digestion depends on the food structure. Lamothe et al. studied different dairy matrices such as milk, yogurt, and cheese and observed that for cheeses, greater fatty acid release could not be related to faster matrix disintegration, suggesting that the lipid droplet size dispersion was more important than matrix breakdown for the modulation of lipid digestion kinetics [23]. Rinaldi et al. evaluated two liquid dairy matrices (pasteurized and sterilized milks) and one semi-liquid dairy matrix (stirred-yogurt), concluding that the severity of milk's heat treatment influences the kinetics of protein digestion, mainly during the gastric phase [24]. Mulet-Cabero et al. investigated a semi-solid meal comprised a mixture of cheese and yogurt and a liquid meal, an oil in water emulsion stabilized by milk proteins, and noted that the semi-solid sample generated higher nutrient released into the small intestine at an early stage of digestion whereas nutrient accessibility from liquid sample was delayed due to the formation of a cream layer in the gastric phase [25]. Considering the standardization aspect, a standard model was proposed by Minekus et al. based on three sequential extraction steps, i.e., salivary, gastric and intestinal digestion [26]. The main characteristics of the general in vitro methods are: digestion temperature, incubation time, agitation, concentration and composition of enzymes (enzymes from saliva, gastric juice, duodenal juice and bile salts). These characteristics depend on the person involved, the age, the mental health, the time of day that the food is consumed, the type and amount of food consumed and other components from the food consumed [11,27, 28]. In vitro methods have been proposed as an alternative to in vivo methods to estimate the bioavailability of elements in food [29]. Considering all these aspects the objective of this work was to determine the soluble fraction (bioaccessible content) of micro (Co, Cu, Mo, Mn, Fe and Zn) and macro-constituents (Mg and Ca) present in milk-based drinks using in vitro digestion with detection by ICP OES. MATERIALS AND METHODS Instruments, Reagents and Solutions For sample treatment the following equipment were used: closed vessel microwave oven, model ETHOS, from Milestone (Sorisole, Italy); water bath, Quimis, model Q226M1 (Diadema, Brazil); centrifuge, Quimis, model Q222T204 (Diadema, Brazil). The pH measurements were carried out with a pH-meter (Hanna Instruments, model pH200, São Paulo, Brazil) equipped with a combined glass electrode (silver/silver chloride). 18
Cidade, M.; Cadore, S.; do Nascimento da Silva, E.
Article Article
For the determination of the analytes an inductively coupled plasma optical emission spectrometer (ICP OES, Perkin Elmer, Optima 3000DV, Norwalk, CT, USA) equipped with a peristaltic pump, a cross flow nebulizer coupled to a Ryton double pass spray chamber (Scott type) and a ceramic central torch tube injector with an internal diameter of 2.0 mm was used. This instrument operates sequentially in either radial or axial torch configurations and has a solid state segmented array charge coupled device (SCD) detector. The argon gas (White Martins, São Paulo, Brazil) used for the analyses was 99.996% pure. The ICP OES parameters optimized for analysis included the following: a radio frequency power of 1300 W, a plasma argon flow rate of 15 L min-1, an auxiliary argon flow rate of 0.5 L min-1, a nebulization gas flow rate of 0.8 L -1 -1 min , sample flow rate of 1.0 mL min , radial observation height of 15 mm (for Ca, Co, Cu, Fe, Mg, Mo) and 30 seconds of reading time. The analytes studied included the following: Ca (317.933 nm), Co (228.616 nm), Cu (324.752 nm), Fe (238.204 nm), Mg (285.231 nm), Mn (257.610 nm axial view), Mo (202.031 nm) (213.857 nm axial view). All reagents used were of analytical grade and the deionized water used was produced by a Milli-Q system (Millipore, Bedford, MA, USA), showing conductivity of 18 MΩ cm. The materials, polyethylene bottles and glasses, were previously soaked in 10% (v/v) HNO3 (Merck, Darmstadt, Germany) for at least 12 h and rinsed with ultrapure water before use. -1 The standard solutions used for the analytical calibration curves were obtained from 1000 mg L stock solutions of Co, Cu, Fe, Mn, Mo, Zn and from 4000 mg L-1 stock solutions for Ca and Mg (all standards were Merck, Darmstadt, Germany), prepared in 1% (v/v) HNO3. Concentrated HNO3 (Merck), concentrated H2O2 (Merck), concentrated HCl (Merck), NaHCO3 (Merck), NaOH (Synth, Diadema, Brazil), pancreatin (Acros Organics, Morris Plains, USA), bile salt (Sigma Chemical Co., Saint Louis, USA), and pepsin (Acros Organics) were also used. Ten samples (designed as MD1, MD2,…, MD10) of milk-based drinks, from seven different manufacturers (A, B,…, G) were purchased in local supermarkets of Campinas, SP, Brazil. Microwave-assisted digestion For total analysis, the samples were submitted to microwave-assisted oxidative digestion based on a procedure recommended by the microwave oven manufacturer (to bovine milk). Approximately 1 g of each sample was weighed and transferred to closed microwave vials (Teflon®) and then 3 mL of concentrated HNO3, 1 mL of concentrated H2O2 and 5 mL of deionized water were added. The final mixture was weighed (acidity ~ 30%) in order to express the final results as w/w, and then submitted to the heating program described in Table I. Each procedure was carried out in triplicate. Table I. Heating program of microwave oven
Stage 1 2 3 4 5 6
(ram p) (hold) (ram p) (hold) (ram p) (hold)
Time (min) 3 2 4 5 7 25
Temperature (ºC) 80 80 120 120 200 200
The evaluation of method efficiency was carried out through addition and recovery of the analytes experiments, at three different concentration levels, as described in Table II.
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Essential Inorganic Ions in Milk-Based Drinks: Evaluation of Bioaccessibility
Article
-1
Table II. Concentration (mg L ) of the analytes added to MD1 sample
Elements Co, Mo, Mn, Cu Fe, Zn Ca Mg
Level 1
Level 2
Level 3
0.05 0.2 1.0 0.5
0.1 0.5 3.0 0.8
0.4 1.0 5.0 1.2
Bioaccessibility evaluation The procedure used for the determination of the bioaccessibility of the analytes was carried out in accordance with the methodology described by Glahn et al. [30]. Here, it was not employed the standardized method proposed by Minekus et al. [26] because Ca and Mg are present in large amounts in the reagents used to simulate the in vitro gastrointestinal digestion and then it becomes difficult to determine the small amount of these elements released from the sample to the soluble fraction (hydrolysate). For the gastric digestion simulation, the gastric juice was prepared by mixing 0.20 g of pepsin and 8 mL of 0.1 mol L-1 HCl, which was shaken for complete pepsin dissolution; for the intestinal digestion simulation, the intestinal juice -1 was prepared by mixing 0.05 g of pancreatin, 0.30 g of bile extract and 25 mL of 0.1 mol L NaHCO3 and then this mixture was shaken in order to obtain the complete dissolution. The bioaccessibility study was performed using 1.0 g of each milk beverage sample. For the in vitro gastric digestion procedure the pH of the sample was adjusted to approximately 2 by gradual addition of -1 5.0 mol L HCl solution, and then 0.50 mL of the pepsin solution (0.0125 g of pepsin/mL sample) were added. This mixture was submitted to a temperature of 37 ± 3 ºC for 60 minutes in a water bath, under constant stirring. Afterwards, the mixture resulted from the in vitro gastric digestion was submitted to the in -1 vitro intestinal digestion procedure, in which the pH was adjusted to 6 by gradual addition of 1.0 mol L NaHCO3 solution. To this mixture 2.50 mL of bile-pancreatin solution (0.005 g of pancreatin + 0.03 g of bile/mL of the sample) were added and the solution was again heated at 37 ± 3 ºC using a water bath for 2 h under stirring. After the intestinal digestion, the solution was then subjected to an ice bath for 10 minutes, in order to stop the enzymatic action. Moreover, the pH was adjusted to 7.2 by gradual addition of 0.5 mol -1 L NaOH solution and the mixture was centrifuged at 3500 rpm for 30 minutes. The supernatant (chyme) was separated from the precipitate and the soluble analytes in were quantified by ICP OES. RESULTS AND DISCUSSION Quantification of the analytes For the quantification of the total concentration the limits of quantification (LOQ) [31], calculated as 10 σ under the established experimental conditions were 0.01 mg kg-1 for Cu and Mn, 0.1 mg kg-1 for Mo, Co and Mg, 0.04 mg kg-1 for Zn and Fe, and 0.3 mg kg-1 for Ca. Therefore, these limits were adequate to determine the concentrations of the elements investigated. In order to evaluate the sample preparation using microwave-assisted digestion, the MD1 sample was spiked with three different concentration levels of the analytes. The recovery values are presented in Table III.
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Cidade, M.; Cadore, S.; do Nascimento da Silva, E.
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Table III. Recovery and RSD values (%) obtained for the concentration levels added to MD1 sample
Elements
Level 1
Level 2
Level 3
Cu Mo Co Mn Zn Fe Ca Mg
101 (3) 100 (7) 95 (4) 92 (3) 82 (5) 105 (5) 113 (6) 106 (5)
105 (3) 100 (6) 97 (4) 95 (3) 91 (3) 96 (8) 90 (5) 96 (5)
113 (8) 100 (10) 98 (8) 100 (8) 90 (4) 108 (3) 93 (5) 96 (5)
As can be seen, recoveries between 90 and 110% and RSD lower than 10% were obtained for all analytes, showing that the proposed sample treatment is adequate for the analysis. In Table IV are presented the concentrations (mg kg-1) for each analyte in the samples and the respective standard deviations. The labels of the samples only contain the values for total concentration of Ca and the values found here agree with that declared by the manufacturers. -1 Calcium was the element found in highest concentration, varying over the range of 552 to 1380 mg kg , while Co was the only element that was below the LOQ in all samples analyzed. Table IV. Concentration (mg kg-1) of the elements determined in the samples and the RSD values (%)
Producer and samples Elements Cu Mo Co Mn Zn Fe Ca Mg
A
B
MD1
MD2
MD3
MD4
C MD5
0.60 ( 2)
0.23 (3)
< 0.001
0.47 ( 4)
< 0.001
0.05 (0.4)
0.05 (1)
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
0.84 ( 2)
1.43 (4)
< 0.001
0.67 ( 2)
< 0.001
3.67 ( 3)
4.18 (2)
3.23 (1)
2.40 (2)
3.01 (10 )
7.58 (0.3)
5.14 (1)
0.56 ( 5)
9.42 (0.1)
1.08 ( 5)
841 ( 5)
1337 (2)
1380 (8)
674 (8)
991 (2)
143 ( 5)
150 (3)
98.8 (2)
159 (4)
97.8 (10)
F MD9
G MD10
Producer and samples Elements Cu Mo Co Mn Zn Fe Ca Mg
D MD6
MD7
E MD8
< 0.001
< 0.001
< 0.001
0.45 (5)
< 0.001
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.001
< 0.001
0.11 (8)
0.58 (2)
< 0.001
2.43 (0.3)
2.50 (8)
1.68 (2)
1.73 (5)
2.79 (10)
1.00 ( 7)
0.44 (5)
0.83 (3 5)
6.58 (6)
1.92 (1)
995 (1)
1016 (9)
628 (5)
552 (2 )
998.83 ( 2)
90.3 (6)
91.5 (6)
70.7 (4)
148 (10)
105 (1)
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Essential Inorganic Ions in Milk-Based Drinks: Evaluation of Bioaccessibility
Article
Bioaccessibility of the analytes The bioaccessibility represents the soluble fraction which is the amount that can be absorbed and transformed into a biologically active form in the human body. Thus, the knowledge of this amount is more informative than knowing only the total concentration of the element in any food [32]. Table V shows the bioaccessible fraction (bioaccessibility) of the analytes in the samples, which is expressed as percentage, whose results were obtained on the basis of the total concentration shown in Table IV. Table V. Bioacessible fractions of gastro-intestinal digestion (as percentage of total concentration) and RSDs (%)
Elements Cu Mn Zn Fe Ca Mg Elements Cu Mn Zn Fe Ca Mg
Samples MD1
MD2
MD3
MD4
MD5
41.08 (0.04)
63.90 (0.04)
< 0.001
52.05 (0.04)
< 0.001
40.42 (0.04)
41.2 (0.3)
< 0.001
40.15 (0.05)
< 0.001
31.4 (0.6)
29.5 (0.9)
49.0 (0.1)
24.6 (0.3)
65.4 (0.3)
8 (2)
41 (2 )
43 (1 )
10 (7 )
56.8 (0.6)
108 (5 )
73 (4 )
94 (1 )
54 (8 )
100 (2 )
113 (5 )
99 (2)
99 (5)
85 (5 )
105 (10)
Samples MD6
MD7
MD8
MD9
MD10
< 0.001
< 0.001
< 0.001
65.15 (0.03)
< 0.001
< 0.001
< 0.001
< 0.001
60.99 (0.02)
< 0.001
57.1 (0.2)
51.7 (0.8)
69.9 (0.4)
44.3 (0.6)
60.5 (0.5)
22.7 ( 4)
28 (1)
44 (2)
22 (4)
10 (3)
87 (2)
85 (2)
99 (9)
97 (2)
92 (4)
97 (6)
91 (2)
105 (4)
102 (1)
97 (4)
Molybdenum and Co bioaccessible fractions were not calculated because the concentration for these -1 elements was below the LOQ. The total concentration of Mn in the MD1 sample was 0.84 mg kg , but only 0.34 mg kg-1 became soluble, i.e., 40.4% of the total amount of this nutrient is available for absorption by intestinal cells. Considering all the samples analyzed the bioaccessibility for manganese changes from 40 to 61%. There are no reports concerning the bioaccessibility of this element in dairy beverages. However, it is possible to compare this result with those obtained by do Nascimento da Silva et al. for Mn in milkbased instant cereals (19-42%) [16]. It is reasonable that for some milk-based drinks the bioaccessibility values are greater than for instant cereals because the presence of larger amount of proteins in dairy beverages leads to higher Mn solubility. In the present work it was also observed that the Mn bioaccessible fraction increases when its total concentration decreases, as already reported by Velasco-Reynold et al., who indicated that the higher the total Mn intake, the lower the absorption eďŹ&#x192;ciency of the element. In the present work, the same correlation was also observed for Cu [32]. Nascimento et al. observed that 83% of Cu and 78% of Fe present in cashew nuts were extracted during sample digestion [33]. Considering the milk-based drinks, the average availability of Cu and Fe was about 56 and 29%, respectively, which are much smaller values compared to the cashew nuts. Copper absorption inhibitors are sugars, proteins of animal origin, S-amino acids and histidine, therefore the Cu availability in dairy beverages is lower than in cashew nuts [13,34,35]. On the other hand, the values obtained here are in agreement with that obtained by do Nascimento da Silva et al. for Cu in milk-based instant cereals (~52%) and infant formulas (59-67%) [16]. Moreover, the presence of milk-derived caseino-phospho-peptides
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Cidade, M.; Cadore, S.; do Nascimento da Silva, E.
Article Article
(CPPs) in dairy samples may cause a great decrease of Fe bioaccessibility as can be seen for milk-based instant cereals (2.4-5%) and infant formulas (63-69%) [36]. However, a comparison of bioaccessible fraction obtained for dairy beverages with those obtained by other authors for diďŹ&#x20AC;erent samples is not simple, since the bioaccessibility of elements depends on the sample composition, the total amount of each analyte and also the in vitro digestion procedure used. Calcium and Mg were the elements which present the highest bioaccessibility values, around 100%, showing that milk-based drinks are a rich source of these elements, because this type of matrix has proteins that provide the increase on the solubility of these elements. Polyphenols and phytates, who could decrease the bioaccessibility of Ca an Mg are not present in high concentrations in milk-based drinks [34]. On the other hand, for some samples the values for Zn bioaccessibility (24-69%) are generally lower due to the presence of casein and casein phosphopeptides which make Zn insoluble. Although in the acid medium of the stomach, dietary Zn can be released from casein, a considerable proportion of this casein is not digested, making Zn less bioaccessible [35,36]. It was possible to observe here that many parameters should inďŹ&#x201A;uence the nutrient solubility during gastrointestinal digestion, such as the composition of the food, food structure and the in vitro digestion procedure used. Despite it was possible to obtain an approach of the solubility of some elements from milkbased drinks during the gastrointestinal digestion, it is worth highlighting that the actual percentage of each element to be absorbed by the digestive tract will mainly depend on the conditions of each individual. However, some important information concerning the bioaccessibility of inorganic nutrients in dairy beverages was obtained in the present work. CONCLUSION The microwave-assisted digestion using nitric acid and hydrogen peroxide showed to be suitable for the sample treatment, showing recovery values in the range of 90-110% and RSD less than 10% for all the elements studied. Calcium was the element with the highest concentration in all beverages evaluated in this study and the values obtained agreed with those declared by the manufacturers. The in vitro gastrointestinal digestion procedure provided an evaluation of the amount of the analytes that can potentially be absorbed by the body. It was veriďŹ ed that the bioaccessible fractions for Mn and Cu decrease with the increase of their total concentration, while Ca and Mg showed to be almost fully bioaccessible. The bioaccessibility of these elements may vary with the samples, according to their composition, showing the importance of determining accurately the amount of an essential element is actually available to the human body. Manuscript received March 27, 2018; revised manuscript received July 9, 2018; accepted July 11, 2018; published online October 3, 2018.
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Br. J. Anal. Chem., 2018, 5 (20), pp 26-34 DOI: 10.30744/brjac.2179-3425.2018.5.20.26-34
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Determination of As, Cd, Cu, Fe, Ni, Pb and Zn in Soybean Seeds and their Correlation with Relevant Biochemical Parameters to assess Food Quality Inés Viera1, Ignacio Machado2; Mariela Pistón2 *, María H. Torre1 1
Inorganic Chemistry, Facultad de Química, Universidad de la República (UdelaR). Av. Gral. Flores 2124 P.O. Box 1157, 11800 Montevideo, Uruguay 2 Analytical Chemistry, GATPREM, Facultad de Química, Universidad de la República (UdelaR) Av. Gral. Flores 2124, P.O. Box 1157, 11800 Montevideo, Uruguay
Soybean (Glycine max) represents one of the most important crops in Uruguay, mostly processed for animal feed, while a smaller percentage is processed for human consumption. Soy foodstuffs are also a source of trace elements (TEs). Cu, Fe, Ni, Zn, As, Cd and Pb were determined in soybean seeds batches and correlations within them and with biochemical parameters (superoxide anion content, superoxide dismutase enzyme and viability of the analyzed seeds) were studied. Analytical determinations of Cu, Fe and Zn were performed by flame atomic absorption atomic spectrometry (FAAS) while As, Cd, Ni and Pb were determined by electrothermal atomic absorption spectrometry (ETAAS). For sample preparation, a microwave assisted digestion was carried out using diluted acid (3.5 mol L-1 HNO3). The concentrations of the essential elements where in the following ranges: 12 – 24 mg kg-1 for Cu, 60 - 125 mg kg-1 for Fe, 5.4 – 17.9 mg kg-1 for Ni and 33 – 50 mg kg-1 for Zn. Cd and As content was < 0.2 and 0.3 mg kg-1 respectively, -1 whereas Pb exceeded slightly the admitted limit in five samples (above 0.2 mg kg ). Positive correlations were found for Fe:Cd:Pb (p<0.005), Cu:Fe, As:Cd:Pb and Zn:Ni (p<0.05). A novel highly significant positive correlation (p < 0.005) between Cd content and seed quality parameters related to seed germination was found. This suggests that the concentration of Cd do not produce negative effects in the development of the seedlings, despite this Cd and Pb levels must be monitored to guarantee food safety. Keywords: Soybean seeds, essential trace elements in food, food safety INTRODUCTION Some trace elements (TEs) are essential micronutrients for human beings. The requirement is no more than a few milligrams per day, but deficiencies, excesses, or imbalances in their supply from dietary sources can have an importantly deleterious influence. Some of the most relevant are copper (Cu), iron (Fe) and zinc (Zn). The essentiality of Fe and Cu resides in their capacity to participate in one-electron exchange reactions. Systemic Cu deficiency can generate anemia, ataxia, diminished growth, alterations in bone mineralization, diminished immune response and Menkes disease, among others. Moreover, it is well known that Fe deficiency can mainly produce anemia [1]. The primary influence of Zn in biological systems resides in its presence in ca. 300 enzymes. Zn has particularly relevant roles in growth, reproduction, immune and neuronal functions [2]. These elements must be incorporated through the diet but nowadays, due to frequently dietary disorders, TEs deficiencies have become a matter of concern. In the case of Nickel (Ni), it is essential for plants and bacteria [3-5] but there is no evidence of the effect of Ni deficiency in humans. On the other hand, TEs such as arsenic (As), lead (Pb), and cadmium (Cd) are potentially harmful to human and animal health [6]. Humans exposed to As may develop skin lesions, neuropathy, gastrointestinal diseases, cardiovascular diseases, cancer, and other ailments. Exposure to Pb due to contaminated food may cause changes in the neurologic system, leading to loss of neurological function. Acute Cd exposure can cause stomach irritation, *mpiston@fq.edu.uy https://orcid.org/0000-0002-6762-5852 26
Determination of As, Cd, Cu, Fe, Ni, Pb and Zn in Soybean Seeds and their Correlation with Relevant Biochemical Parameters to assess Food Quality
Article Article
while the long-term intake of low levels of Cd can cause kidney disease and bone fragility [7,8]. Therefore, regional regulations established maximum limits for As, Cd and Pb in several foodstuff for safety reasons. Then, it is important to monitor these TEs to ensure food safety. Crops such as rice, wheat and soybeans are the basis of human diet in many countries and are widely used in food and feed. Soybean is one of the most important crops in terms of cultivated area in Uruguay covering more than 60% of the total agricultural area [9]. Besides, studies on the transfer of heavy metals from soil to crops have shown that soybean may accumulate more potentially toxic elements than other crops [10]. Salazar et al. evaluated the content of Cd, Pb and Zn in agricultural soils, the transfer of these elements to the plant and its relation to crop quality. They found that concentration values for Pb and Cd in both soils and soybeans, at several sites in Argentina, were above the maximum permissible levels. This information alerted about the possible presence of these elements in seeds that are imported from Argentina to Uruguay as raw material for food as well as for planting purposes [10]. In this work, in addition to determine the contents of TEs (four essentials and three potentially toxic) in soybean seeds, correlations between these contents and biochemical parameters related to oxidative stress such as superoxide dismutase activity, basal superoxide anion level and non-enzymatic activity, and seed quality (vigor and germination) were carried out [11,12]. The results are presented for the first time to asses' food safety and commercial and economic aspects of these crops. MATERIALS AND METHODS Reagents -1
Commercial standard solutions 1000 mg L of As(V), Cd, Cu, Fe, Ni, Pb and Zn provided by Merck (Germany) were used. Calibration solutions were prepared by dilution of the stock solution of each element, using 0.1% v/v nitric acid (HNO3) prepared from concentrated HNO3 (67% v/v) provided by Merck (Germany). Ultrapure water, ASTM Type I (18.2 MΩ cm resistivity) was obtained from a Millipore® (Brazil) Direct-Q 5 purifier. All glassware remained submerged overnight in 10% v/v HNO3 and after that it was rinsed exhaustively with ultrapure water before use. Chemical matrix modifier for Cd and Pb determination were prepared from stock solutions of Pd(NO3)2 -1 and Mg(NO3)2 provided by Merck (Germany) containing 10000 and 20000 mg L respectively. For As determination a permanent modifier was prepared from a stock solution of Nb(NO3)5 1000 mg L-1 provided by Sigma- Aldrich (Switzerland). All other reagents were of analytical reagent grade or better. Reagents and solvents for the determination of biochemical parameters were commercially available research-grade chemicals and were used without further purification [13]. Analytical determinations Trace elements Analytical determinations of Cu, Fe and Zn were performed by flame atomic absorption atomic spectrometry (FAAS) using a spectrometer Perkin Elmer AAnalyst 200 (USA) operated at the analytical lines of Cu (324.7 nm), Fe (248.3 nm) and Zn (213.9 nm). Photron (Australia) hollow cathode lamps were -1 used as recommended by the manufacturer. Flame composition was acetylene (2.5 L min ) and air (10.0 L min-1). As, Cd, Ni and Pb were determined by electrothermal atomic absorption spectrometry (ETAAS) using a spectrometer Thermo Scientific iCE 3500 (United Kingdom) equipped with auto-sampler module (GFS33) and employing Zeeman-based correction. A transversely heated graphite tube furnace module (GFS35Z), from Thermo Fisher Scientific, was used. Photron (Australia) hollow cathode lamps, operated at the
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Viera, I.; Machado, I.; Pistón, M.; Torre, M. H.
Article Article
193.7 nm (As), 228.8 nm (Cd), 232.0 nm (Ni) and 283.3 nm (Pb), were used. The spectrometer was controlled with the commercial software SOLAAR from Thermo Scientific (United Kingdom). Integrated peak-area was used as signal for evaluation and quantification. All the determinations were performed using pyrolytically coated graphite tubes from Thermo Scientific. Argon 99.998% provided by Linde (Uruguay) was used as the purge and protective gas. The heating programs employed for the analytical determinations are showed in Table I. These conditions were optimized and reported in a previous work [14]. Table I. ETAAS optimized temperature programs for the determination of As, Cd, Ni and Pb
Temperature (ºC)
Ramp rate (ºC s -1)
Hold time (s)
Drying 1
100
10a,c,d/5b
30
Drying 2b
140
15
20
Pyrolysis
1200a/350b/1000c,d
15a/10b/150c,d
15a/0b/20c,d
2200a/1500b/2500c /1800d
0
3
2600
0
3
Stage
Atomization Cleaning a
As, bCd, cNi, dPb
For Cd and Pb determinations the chemical matrix modifier used was: 10 μL of solution containing 5 μg of Pd(NO3)2 and 3 μg of Mg(NO3)2. For Cd two drying steps were required using conditions presented in Table I [15]. Sample injection volume was 20 µL for both elements. For Ni determination, no chemical modifier was required, and sample injection volume was 30 µL. Since As determinations required a special procedure using a permanent modifier, graphite tubes were treated with niobium, according to Machado et al. by pipetting 50 µL of a 1000 mg L-1 Nb(NO3)5 solution and then submitting the tube to the following temperature program: [temperature/ramp time/ hold time]: drying (100 °C / 10 s / 60 s), atomization (2700 °C / 0 s / 5 s). The entire procedure was repeated six times (to obtain an amount of 300 µg of permanent modifier on the tube). Then the temperature program was as -1 shown in Table I. The injection volume was 30 µL. In all cases argon flow rate was 0.2 L min [14]. Biochemical parameters Biochemical parameters related to oxidative stress of the batches were performed as previously reported by our research group as follows: a) antioxidant enzymatic systems were evaluated in a buffer extract determining the superoxide dismutase (SOD) activity using the method based on the inhibitory effect of SOD over the reduction of nitrobluetetrazolium by the superoxide generated by the xanthine/ xanthine oxidase system; b) basal superoxide anion level was determined by a spectrophotometric method in the same extract as in a); c) non-enzymatic antioxidant activity was determined as 2,2-diphenyl-1picrylhydrazyl (DPPH) radical scavenging capacity of an ethanolic extract following the Brand-Williams method. A Thermo Scientific Evolution 60 spectrometer was used for spectrophotometric measures [13]. Soybean quality analysis consists mainly in three in vitro tests: germination, vigor and viability by tetrazolium test. Results of these tests were provided by a Uruguayan laboratory that performs tests according to the International Seed Testing Association (ISTA) rules [16]. Seeds are classified as “normal” according to ISTA rules when germination is > 80%, considering several standard parameters of growth, these seeds can be sold to farmers for planting. Vigor test is performed to detect significant differences related to physiological quality of batches of seeds, thus complementing the information of germination tests. Sometimes it happens that certain batches of seeds with high percentages of germination have different behavior when they grow in field.
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Determination of As, Cd, Cu, Fe, Ni, Pb and Zn in Soybean Seeds and their Correlation with Relevant Biochemical Parameters to assess Food Quality
Article
This is explained by the fact that seeds lose vigor before losing their ability to germinate. Viability tests counts percentage of viable embryos through different standard techniques [13]. Samples Sixteen batches of soybean seeds (Glycine max (L.) Merrill) were obtained from a local distributor (Agropecuaria Valdense S.R.L., Colonia, Uruguay). All batches consisted of transgenic yellow soybean seeds and ranged from 0.618 to 0.864 cm of diameter. Samples were dried in an oven with forced air circulation (70 °C) and stored at 20 °C. Before sample preparation for the different assays, seeds were milled to obtain the flour. A certified reference material (CRM) NIST-1587a of wheat flour was also analyzed, this CRM was considered adequate for trueness evaluation. This CRM did not inform Ni content and for As and Pb a concentration value is informed in the certificate but without uncertainty, thus spiked samples were also analyzed to complement trueness evaluation of the analytical methods. Sample preparation For trace element determinations, a microwave assisted digestion was carried out employing a microwave oven (CEM, Mars 6) provided with 12 EasyPrep Plus® vessels. Each sample was prepared in triplicate as follows: 0.5 g of sample (flour) was accurately weighted, and 10.00 mL of 3.5 mol L-1 HNO3 were added into each EasyPrep Plus® vessel. The program was: power 4001800 W, 15 minutes ramp time until 200 ºC, 10 minutes hold at 200 ºC, 500 psi pressure. Reagent blanks were also run. After digestion, TEs in samples were directly measured or when necessary a suitable dilution with ultrapure water was performed. Assays to obtain biochemical parameters were performed with soybean seeds flour without further treatment as previously described [13]. Correlations Associations between variables were determined via Pearson´s correlation analysis. Multiple linear correlation and linear regression analysis were carried out using MS Excel®. RESULTS AND DISCUSION Trace elements determinations 2 For all the studied analytes, the determination coefficients (R ) for linear regression of the calibration curves were greater than 0.99 using either FAAS or ETAAS technique. Linearity (mg L-1) was up to: 4.0 for Cu, 2.0 for Fe, 0.10 for Ni, 1.0 for Zn, 0.020 for As, 0.004 for Cd and 0.050 for Pb. Detection limits were estimated for each element, according to Eurachem Guide, expressed as the element content corresponding to three times the standard deviation of a blank (3s; n=10) and expressed in the sample (dry basis). Quantification limits were estimated in the same way considering in this case 10 times the standard deviation (10s; n=10) [17]. A summary of the TEs content in each sample is presented in Table II, detection and quantification limits for each element are also shown.
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Viera, I.; Machado, I.; Pistón, M.; Torre, M. H.
Article
Table II. Trace elements content (mg kg-1) in soybean seeds Samples
Cu
Zn
Fe
Ni
Cd
Pb
As
S01
14.9 ± 0.4
42 ± 2
99 ± 1
9.5 ± 0.5
0.027 ± 0.002
0.292 ± 0.002
0.125 ± 0.001
S02
13.9 ± 0.3
50 ± 1
105 ± 2
12.8 ± 0.4
0.015 ± 0.001
0.218 ± 0.002
0.147 ± 0.001
S03*
13.0 ± 0.2
35 ± 1
115 ± 1
9.4 ± 0.1
0.056 ± 0.001
0.539 ± 0.017
0.158 ± 0.006
S04
13.2 ± 0.8
44 ± 1
82 ± 4
14.3 ± 0.3
0.014 ± 0.001
0.165 ± 0.011
0.104 ± 0.001
S05
24 ± 3
44 ± 2
125 ± 8
13.6 ± 0.3
0.032 ± 0.001
0.416 ± 0.016
0.097 ± 0.001
S06*
12.2 ± 0.5
42 ± 3
83 ± 1
7.4 ± 0.3
0.035 ± 0.001
0.324 ± 0.009
0.164 ± 0.002
S07
14.5 ± 0.2
44 ± 2
77 ± 4
7.4 ± 0.2
0.011 ± 0.001
0.194 ± 0.003
0.108 ± 0.001
S08
15.0 ± 0.3
35 ± 1
70 ± 12
9.4 ± 0.1
0.013 ± 0.002
0.112 ± 0.008
0.151 ± 0.001
S09
12.5 ± 0.2
39 ± 1
67 ± 4
9.2 ± 0.2
0.014 ± 0.002
0.137 ± 0.010
0.060 ± 0.004
S10
14.2 ± 0.1
41 ± 2
83 ± 6
10.9 ± 0.2
0.013 ± 0.002
0.173 ± 0.011
0.144 ± 0.001
S11
14.8 ± 0.7
48 ± 3
81 ± 3
10.7 ± 0.1
0.015 ± 0.001
0.123 ± 0.009
0.092 ± 0.003
S12
14.0 ± 0.1
43 ± 1
61 ± 1
17.9 ± 0.1
0.013 ± 0.001
0.136 ± 0.004
0.111 ± 0.003
S13
17 ± 2
41 ± 1
52 ± 7
7.7 ± 0.2
0.011 ± 0.001
0.178 ± 0.009
0.106 ± 0.002
S14
14.5 ± 0.3
44 ± 2
70 ± 2
8.1 ± 0.1
<LOD
0.080 ± 0.005
0.107 ± 0.002
S15
13.2 ± 0.2
33 ± 1
60 ± 2
5.4 ± 0.3
˂LOD
0.081 ± 0.001
0.092 ± 0.003
S16
12.5 ± 0.2
41 ± 1
66 ± 2
8.3 ± 0.2
˂LOD
0.085 ± 0.009
0.104 ± 0.004
LOD
0.16
0.08
0.10
0.02
0.002
0.012
0.008
LOQ
0.54
0.26
0.30
0.05
0.006
0.038
0.024
˂
L
O
D
Results are expressed on dry basis as mean ± standard deviation (n=3). Cu, Fe and Zn were determined by FAAS. As, Cd, Ni and Pb were determined by ETAAS. LOD: Limit of detection (3s; n=10). LOQ: Limit of quantification (10s; n=10). * Samples with germination <80%.
The maximum limits allowed by regional regulation to consider soybean seeds a safety food are 0.2 mg -1 -1 kg for Cd and Pb and 0.3 mg kg for As [18], therefore detection limits for As, Cd and Pb were adequate for monitoring food safety in soybean seeds since they are much lower than the legal limits allowed for this food. Precision expressed as relative standard deviation (RSD) was in all cases lower than 10% (n=3 for each element in each sample replicate and n=6 for the CRM). Trueness was evaluated by the analysis of the CRM under the same conditions and by performing a spike-recovery assay over the 16 batches of soybean seeds. Recoveries for the CRM were in the range 90-110% for Cu, Fe and Zn using FAAS and in the range 90-120% for As, Cd, Ni and Pb using ETAAS. Results obtained using a CRM such us wheat flour, a very similar matrix, guarantee that the analytes are quantitative extracted from the matrix even using diluted acid (3.5 mol L-1 HNO3). When the flour obtained from soybean seeds is spiked with a known amount of analyte, it can be ensured there are no losses during the analysis. Both studies guarantee the trueness of the method. The use of diluted acid for microwave assisted digestions was reported as an efficient procedure for total digestion in several complex matrices including soybean seeds [14,19]. In this work, the use of 3.5 mol L-1 HNO3 was successful. Clear solutions were obtained after the digestion process with good recoveries and complying with the principles of Green Chemistry. The essential TEs content in soybean seeds obtained are in accordance with those reported by several authors in the literature [11,19-21]. The concentration of the essential elements in the analyzed samples 30
Determination of As, Cd, Cu, Fe, Ni, Pb and Zn in Soybean Seeds and their Correlation with Relevant Biochemical Parameters to assess Food Quality
Article
-1
-1
-1
where in the range: (12.2 – 24.0) mg kg for Cu, (60 - 125) mg kg Fe, (5.4 – 17.9) mg kg for Ni and -1 (33 - 50) mg kg for Zn. All ranges are in good agreement with values reported for Argentinian and Brazilian crops. Other authors have found statistically significant differences in the metallic content between transgenic and non-transgenic soybean seeds, being concentrations of Cu and Fe higher in transgenic seeds by 40 and 20% respectively [22-23]. Soybean seeds composition is dependent on numerous factors, including soil characteristics and water source composition. Once these factors are controlled during the growth, it can be expected that differences in concentrations should be related only to genetic modification. In this case, all samples were from transgenic origin, so it was not possible to perform such a comparison. Regarding non-essential elements, all samples comply with the regional regulation established for Cd -1 and As (<0.2 and 0.3 mg kg respectively). Therefore, soybean seeds analyzed can be considered as safe for human consumption. However, five samples showed levels of Pb that exceeded the maximum limit -1 admitted of 0.2 mg kg . These are only few batches to take conclusions about food safety, but they provide evidence that there must be rigorous controls of toxic elements in food. Coincidentally with the fact that Pb is toxic to living organisms, two of the samples with high levels of Pb presented poor germination (<80%), particularly sample S03 whose germination was <10%. Germination data of these same batches was previously reported by our research group [13]. Correlations within trace elements contents The set of data presented in Table II was used to perform the correlations within TEs, where particularly novel information was presented regarding potentially toxic elements such as As, Cd and Pb. Plants have developed mechanisms to prevent their own toxicity by regulating the transportation of the toxic elements with chelation or sequestration. Different strategies are performed to deal with high concentration levels of TEs in the environment [24-25]. The uptake and efflux of metals ions at cellular level must be strictly coordinated with the requirements of the whole plant to maintain homeostasis [26]. Table III shows Pearson´s correlation coefficients between TEs content. Significantly high positive correlations were found for Fe:Cd:Pb (p<0.005), while for Cu:Fe, As:Cd, As:Pb and Zn:Ni the correlations were also positive but slightly lower (p<0.05). Table III. Pearson´s correlation coefficients between TEs content in soybean seeds samples
Cu Zn Fe Ni Cd Pb
Zn
Fe
Ni
Cd
Pb
As
0.2415
0.4328* 0.2582
0.2609 0.4419* 0.2762
0.1331 -0.1752 0.7356** 0.0592
0.3238 -0.0537 0.8164** 0.1064 0.7543**
-0.1680 -0.0487 0.3685 -0.0033 0.4960* 0.4544*
* p<0.05 and **p<0.005
It seems that there are important agonist interactions between potentially toxic elements, as they are positively related. In the case of Cd and Pb, it could be explained by the fact they are assimilated from the soil by the same family of ATPases, divalent cation transporter class enzymes [26]. According to Cd and Fe interactions, many studies on plants showed that Cd may displace Fe from EDTA complexing agents, leading to diminished Cd bioavailability and increasing the resistance of the plant. The inhibition of the uptake of essential elements may contribute to Cd toxicity. But also, the Cd efflux as a resistance strategy could lead to the efflux of other metal ions as well. Recent studies found no inhibition of
31
Viera, I.; Machado, I.; Pistón, M.; Torre, M. H.
Article
Fe uptake by Cd toxicity, in fact, in this work both elements resulted to be positively related, probably due to the presence of specific transporters for each one. Several authors reported metal efflux proteins P-type ATPases for Cd and metal uptake proteins Yellow Stripe1-Like (YSL) for Fe [26-27]. Correlations between trace elements contents and biochemical parameters Biochemical parameters, previously reported by the authors [13], are shown in Table IV. Pearson´s correlation coefficients between TEs and biochemical parameters in soybean seeds samples are presented in Table V. Regarding TEs content and biochemical parameters a moderate negative correlation between Cu and superoxide anion was found. This is in accordance with the fact that Cu integrates numerous enzymatic detoxifying systems responsible for controlling the oxidative stress. Table IV. Biochemical parameters
Samples
Superoxide* (Absorbance560)
SOD activity * (U mg-1 protein)
DPPH assay* (mg antioxidant per g dry seed)
Germination (%)
Vigor (%)
Viability (%)
0.011 0.020 0.018 0.011 0.010 0.028 0.012 0.020 0.024 0.012 0.011 0.018 0.017 0.010 0.018 0.017
49.7 30.7 20.3 47.1 44.5 36.4 80.4 25.4 67.7 39.2 48.0 33.5 57.3 35.2 33.5 34.5
4.6 5.9 5.1 5.4 7.0 5.1 6.5 5.2 5.5 6.4 5.0 5.8 5.9 6.0 5.8 5.4
93 80 20 86 80 70 97 70 80 87 97 87 75 74 87 71
64 50 33 31 44 60 74 45 53 59 60 44 54 34 44 36
99 88 96 89 89 98 99 80 98 93 98 99 88 94 99 90
S01 S02 S03 S04 S05 S06 S07 S08 S09 S10 S11 S12 S13 S14 S15 S16
*Results expressed as mean value (n=3) as previously reported by Cardoso et al. [13]. In vitro tests: germination, vigor and viability were performed using the tetrazolium test according to ISTA rules [16]. Table V. Pearson´s correlation coefficients between TEs and biochemical parameters in soybean seeds samples
Parameter
Cu
Zn
Fe
Ni
Cd
Pb
As
Superoxide
-0.4508*
-0.3532
-0.1666
-0.3310
0.2061
0.0825
0.2779
SOD activity
0.1140
0.2501
-0.2750
-0.0305
-0.3220
-0.1995
-0.5981***
DPPH assay
0.5593**
0.2130
0.0385
0.2684
-0.2595
-0.0355
-0.2260
Germination
0.1470
0.4607
-0.2944
0.0935
0.7549***
-0.5849
-0.4684
Vigor
0.0177
0.2633
-0.1281
-0.036
0.6162*
-0.0515
0.0141
Viability
-0.3209
-0.0207
-0.0155
-0.2652
0.6109*
0.1177
-0.2514
* p<0.05, **p<0.025, ***p<0.01
32
Determination of As, Cd, Cu, Fe, Ni, Pb and Zn in Soybean Seeds and their Correlation with Relevant Biochemical Parameters to assess Food Quality
Article
The highly significant positive correlation (p < 0.01) between Cd content and quality parameter germination (vigor and viability to a lesser extent) would indicate that Cd content does not produce negative effects in the development of the seeds. This is in accordance with findings reported by some authors, who suggest that a slightly increased level of oxidative stress stimulates germination [28,29]. This theory is also supported by Bailly et al. who describes the need of a period of oxidative stress for germination process [30]. Small amounts of Cd could lead to this oxidative stress and stimulate germination. It is interesting to highlight that the positive correlation between Cd and the germination parameters is significantly higher than for Cu, being Cu an essential TE. On the other hand, theories about the pattern of Zn and Cd uptake, reinforces the hypothesis that plants are adapting to Cd, in certain amount, this element do not cause harm to the seed. In the case of Pb, no significant correlations were observed with any of the studied biochemical parameters. The Pb uptake by plants might be due to unknown mechanisms. However, evidence has proved that Pb taken by the plant and translocated to the upper parts is under the form of Pb-chelate complexes like EDTA-Pb and HEDTA-Pb. Once the complex is inside the plant, it stays intact to relieve potential toxic effects and allow the plant to continue growing [31]. An interesting observation was the negative correlation between Pb and germination showing a toxic effect. No significant correlations were observed for Ni or Zn with the studied biochemical parameters. On the other hand, there is a significant negative correlation (p < 0.01) between As content and SOD activity. This fact could indicate a negative effect of As over a protective mechanism against free radicals, interfering with the scavenging capacity of the SOD. It has been demonstrated that high-affinity as well as constitutive low-affinity uptake systems for As are present in plants. As(V) competes with phosphate for its uptake, and after it, reduction of intracellular As(V) to As(III) takes place by an As reductase and then it is detoxified through complex formation with thiol-rich peptides [32]. CONCLUSIONS For the first time, correlations within TEs content in soybean seeds and with biochemical parameters related to oxidative stress and seed quality was performed. These results allowed us to increase knowledge about TEs effect in biological systems in soybean seeds. Particularly, a significantly positive correlation for Cd and parameters like vigor and germination of seeds was found suggesting that small amounts of Cd can promote seed growth. Some of the analyzed batches had poor germination in field; these batches showed higher levels of Pb, but Pearson´s correlations did not show a negative effect on germination or vigor for the rest of the batches. Besides, high positive correlations for Fe:Cd:Pb (p<0.005) were found, which can be explained by natural physiological mechanisms of the plant. Moreover, we would like to highlight from our study that Cd and Pb do not seem to have a negative influence on the proper growth of soybean seeds, but their levels should be controlled since food safety must be guarantee to consumers and the nutritional value can be altered. Manuscript received May 6, 2018; revised manuscript received June 29, 2018; accepted July 25, 2018; published online October 3, 2018.
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Article
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Br. J. Anal. Chem., 2018, 5 (20), pp 35-47 DOI: 10.30744/brjac.2179-3425.2018.5.20.35-47
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Chemical characteristics of Amazonian Dark Earth in Santarem, Brazil 1
1
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Douglas Sousa da Silva , Julio Cesar Amaral Cardoso , Brainy César Castro Lima , Arthur Abinader 1 2 3 4 Vasconcelos , Lilian Rebellato , Denise Pahl Schaan , Denise Maria Cavalcante Gomes , Rafael da Rosa Couto5, Gustavo Brunetto6, Paulo Sérgio Taube1* 1 Institute of Biodiversity and Forests, Federal University of Western Pará, Santarém, PA, CEP 68035-110, Brazil 2 Institute of Social Science, Federal University of Western Pará, Santarém, PA, CEP 68040-070, Brazil 3 Institute of Philosophy and Human Sciences, Federal University of Pará, Belém, PA, CEP 66075-110, Brazil 4 Department of Anthropology, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, CEP 20940-040, Brazil 5 Nucleus of Education, Research and Extension in Agroecology, Federal University of Santa Catarina, Florianópolis, SC, CEP 88034-000, Brazil 6 Department of Soil Science, Federal University of Santa Maria, Santa Maria, RS, CEP 97105-900, Brazil Graphical Abstract
Possible sources of incorporation of P, Ca, Mg and K into the Amazonian Dark Earth The Indian-style arrows represent the incorporation in the pre-colonial period. The main sources of P and Ca (carbonate and phosphate) are bones of fish and other animals, and carapaces of chelonians. 2+
2+
+
This research aimed at to compare some chemical characteristics (pH in water, and KCl, Ca , Mg , K , 3+ Al , organic phosphorus 'Porg' and available phosphorus 'Pava') of anthropogenic and non-anthropogenic soils. Soil samples were collected at five depths: 0-20, 20-40, 40-60, 60-80 and 80-100 cm in two archaeological sites and one non-anthropogenic area. The analysis revealed that the anthropogenic soils presented higher amount of Pava than the non-anthropogenic ones, and that these amounts presented a 2+ positive correlation with the Ca contents, which reflects the incorporation of animal bones, mainly fish to these soils. However, the non-homogeneous distribution of these species and the low K+ contents found in most samples may be limiting for some cultures. Finally, it was possible to differentiate samples of the anthropogenic soils from non-anthropogenic ones by using the values of pH in water and KCl, as well as the Porg and Pava contents. Key words: phosphorus availability, phosphorus fractionation, macronutrients, soil pH.
*arthurnadervas@yahoo.com.br https://orcid.org/0000-0003-4496-6475 35
Chemical characteristics of Amazonian Dark Earth in Santarem, Brazil
Article
INTRODUCTION Most soils of the Amazonic region in Brazil, Bolivia, Colombia, Peru and Ecuador are acid, presenting low natural fertility [1-2]. In this same region, it is possible to find anthropogenic soils with plaggen epipedon horizon, normally associated with high fertility, thus characterizing the so called Amazonian Dark Earths (ADE) [3-4]. ADEs present higher amounts of calcium, manganese and phosphorus in relation to the nonanthropogenic Oxisols and Ultisols [4-6]. They also present high amounts of stable organic matter, being rich in pyrogenic carbon (black carbon) [4,7] thus the presence of ceramics and/or lithic material is a striking feature [8-9]. Their high fertility is due to the incorporation of inorganic (bones and ashes) and organic (plants and animals) residues into the soil [4,10], which results in soils with moderate acidity and low levels of exchangeable aluminum [11]. ADEs are generally found near riverbanks and have A horizons deeper in comparison with the nonanthropogenic adjacent soils [12]. They also are characterized by good drainage, high water availability, and low density, ideal conditions for aeration, porosity and hydraulic conductivity, which favor water penetration and gas exchange [13]. Unlike most non-anthropogenic soils, ADEs generally present high levels of available phosphorus (Pava), which is one of the most important characteristics for their agricultural use in the amazonic region [14]. The high amount of phosphorus reflects the incorporation of large quantities of fish bones, turtle shells, and other animals [9,15]. In spite of the high levels of P, Ca and Mg, several studies of chemical characterization of ADE soils have shown that K is normally found in low concentrations in these soils, which may cause deficiency of this nutrient for certain crops [14,16-17]. Moreover, ADEs are relevant in the search for alternatives to sustainable agricultural practices in the Amazon [11,18]. In the region of Santarem, Brazil, there are several archeological sites, some with a large extension; however, most of the studies already undertaken in these areas emphasize mainly archeological questions. Thus, in order to generate information about the fertility of ADEs in urban areas and to understand the heterogeneity of these soils, the following hypothesis can be established: ADE soils present high levels of organic and available phosphorus, however, the non-homogeneity in the distribution of these species and the possible potassium deficiency may limit their use for some cultures. In this context, this study aimed to evaluate chemical attributes in soils from two archaeological sites containing ADEs and an adjacent non-anthropogenic soil. MATERIAL AND METHODS Location of study area The study areas were located in Santarem, a city in the western region of the state of Pará, Brazil (Figure 1). Soil samples were collected at two archaeological sites: 1) ADE 1 (2º25'06"S and 54º44'19''W), which has a predominant vegetative cover of grasses (Paspalum sp.) and other species, such as: Spondias mombin, Psidium sp., Acrocomia aculeata, Euterpe edulis mart, Byrsonima basiloba, Astrocarium tucuma, Pouteria macrophylla [19] and large fruit trees, such as e.g. cashew and hose tree [20]; 2) ADE 2 (2º25'17''S and 54º44'03''W), which has a predominant vegetative cover of grasses (Paspalum sp.), species Mangifera indica, Syzygium malaccense, Anacardium occidentale and Cyperus sp and; 3) an adjacent area (nonanthropogenic), with a predominant vegetative cover of grasses (Echinochloa pyramidalis and Paspalum sp.), Mangifera indica, Spondias mombin and Anacardium occidentale trees (2º25'39"S and 54º44'19"W). The climate of the region according to the Köppen classification is Ami (tropical humid), average annual temperature of 25.5 °C; relative air humidity around 90% and annual average rainfall of 2318 mm, with pronounced variations during the year [21]. Usually, higher volumes of precipitation are observed during the January and May period.
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da Silva, D. S.; Cardoso, J. C. A.; Lima, B. C. C.; Vasconcelos, A. A.; Rebellato, L.; Schaan, D. P.; Gomes, D. M. C.; Couto, R. R.; Brunetto, G.; Taube, P. S.
Article
Figure 1. Geographical location of the areas evaluated
Santarem is located in the central portion of the Sedimentary Basin of Amazonas, with most of its territory formed in the upper section of the Cretaceous / Tertiary period (Alter do Chão Formation). It is characterized by ruffled and reddish sediments with predominance of fine and thick sandstones with frequent cross-stratification [22]. The area presents Lithographs of the Cretaceous/Tertiary and Quaternary Periods, being the first one represented by lithologies of the Alter do Chão formation, formed by fine and medium sandstones, siltstones and kaolinitic, yellow, red and white argillites. This formation presents tabular surfaces, thus a flat relief. The predominant soils in the region are: typical dystrophic yellow latosol, typical dystrophic argisol and gleysol [22]. Soil collection and analysis In each studied area, a 30 x 30 m plot was demarcated. In each soil, samples were collected in five points at five depths: 0-20, 20-40, 40-60, 60-80 and 80-100 cm. All soil samples were dried in air, macerated and sifted (2 mm mesh) to obtain the fine earth fraction (FEF). The soil was then packed in polyethylene bags and reserved for further analysis. -1
Soil particle size analysis was carried out by using 20 g of soil and 10 mL of a 0.1 mol L NaOH solution [23]. The soil:extractor suspension was subjected to mechanical stirring at 240 rpm during 15 min. Thereafter, the clay and sand fractions (coarse and fine) were separated by sedimentation and sieving, respectively, and the silt fraction was calculated by difference between the total amount and sum of clay plus sand contribution. pH values in water and 1.0 mol L-1 KCl was potentiometrically measured, using a 1.0:2.5 soil:solution ratio [23]. The ΔpH was calculated as the difference between the pH in KCl and pH in water. 2+ 2+ -1 The exchangeable cations (Ca and Mg ) were extracted with a 1.0 mol L KCl aqueous solution, and the in soil:solution proportion was 1:20 (w/v) [24]. These cations were determined in a model 3110 atomic + absorption spectrometer (Perkin Elmer, Texas, USA) equipped with a flame atomization. K was extracted -1 -1 with aqueous solution Mehlich-1 (0.05 mol L HCl plus H2SO4 0.0125 mol L ) [24] and, quantified in a model DM61 Digimed flame photometer DM61 (Sao Paulo, SP, Brazil) equipped with an interference filter for determining K, Na, Li and Ca. Al3+ in the KCl extract was determined by titration with a 0.025 mol L-1 NaOH solution [18]. Available phosphorus (Pava) was extracted with aqueous solution Mehlich-1 in a 1:10 (soil:solution, w/v) proportion -1 [24]. The organic phosphorus (Porg) was extracted with 0.5 mol L H2SO4 solution according to Olsen and Sommers [25]. Both phosphorus fractions were quantified according Murphy and Riley [26]. 37
Chemical characteristics of Amazonian Dark Earth in Santarem, Brazil
Article
Statistical analysis The analytical results were submitted to principal component analysis using the software MINITAB 14© (Minitab, State College, PA, USA). The analysis of the effects between the areas was performed by considering the variability resulting from the values obtained in the samples evaluated in triplicate and expressed from the standard deviation of the mean. RESULTS AND DISCUSSION The analysis of soil texture showed the predominance of the sand fraction in all depths of the analyzed soils, with higher amounts in the ADE 1 (Table I). These results were similar those found by Lima et al. (2002), when analyzing soils with ADE horizon in the western Amazonia [15]. Table I. Particle size distribution of the analyzed soils Soil
ADE 1
ADE 2
Non-anthropogenic soil
Depth
Granulometry (g kg-1) Sand
Silt
Clay
0-20
835
87
78
20-40
820
88
92
40-60
857
65
78
60-80
868
63
69
80-100
867
43
90
0-20
662
188
150
20-40
656
139
205
40-60
657
136
207
60-80
678
119
203
80-100
670
131
199
0-20
770
88
142
20-40
778
77
145
40-60
766
85
149
60-80
772
72
157
80-100
783
77
140
The pH values in water and KCl were not homogeneous intra and extra anthropogenic soils, i.e, pH oscillated with depth in the same ADE and varied from ADE to ADE (Tables II and III). The pH values in water ranged from 5.04 to 8.22 (Table II) and 4.56 to 6.12 (Table III), whereas those in KCl ranged from 4.62 and 6.70 (Table II) and 3.53 and 5.38 (Table III), in ADE 1 and ADE 2, respectively. On the other hand, in the non-anthropogenic soil, the pH values in water and KCl, in the same depths, were lower than those observed for the ADE soils, except for some points of ADE 1, ranging from 4.26 to 6.18 and from 4.01 and 5.88 (Table IV), respectively. The higher pH values in water and KCl for ADE soils are due to the larger amount of plant and animal residues introduced during its formation [27]. The addiction of these residues results in the incorporation of high levels of exchangeable Ca2+ and Mg2+, typically higher than 100 and 30 mmol kg-1, respectively [27-28]. In general, ADE 1 presented higher pH values in comparison with ADE 2 (Tables II and III), at the same depths. This was probably due to the higher incorporation of residues containing calcium carbonate in soil (e.g. fish bones and carapaces of turtles), and may be related to the population at that site have been larger than the ADE 2 [29-30]. The ΔpH values in the soil layers at both sites and in the adjacent area presented negative values (Tables II-IV). The increase in soil negative charges in these layers enhances the adsorption 2+ 2+ + of cationic elements such as Ca , Mg and K which is normally desirable [31].
38
da Silva, D. S.; Cardoso, J. C. A.; Lima, B. C. C.; Vasconcelos, A. A.; Rebellato, L.; Schaan, D. P.; Gomes, D. M. C.; Couto, R. R.; Brunetto, G.; Taube, P. S.
Article
The content of the exchangeable cations (Ca2+ and Mg2+) were higher in anthropogenic soil than in non2+ anthropogenic soil (Tables II-IV). The high Ca concentrations in anthropogenic soils are mainly associated with the human and animal bones input [9,32-33]. Furthermore, Ca2+ can form highly stable organometallic 2+ complexes, mainly associated with pyrogenic carbon [27,32-33]. At higher depths in ADE 1 and ADE 2, Ca 2+ and Mg levels were the lowest (Tables II and III), which reflects the absence of leaves and vegetable waste, as well as ceramic fragments, remnants visible bones or charcoal. According to Kern et al., palm leaves 2+ used to cover housing, are renewed regularly, and may be an important source of Mg . In addition, higher Mg2+ levels in the soil surface may be directly related to the recent incorporation of plant remains (e.g. leaves) [34]. +
-1
The K amounts associated with anthropogenic soils, in general, were low (<1.1 mmol kg ), and this may indicate that the discarded waste had low concentration of this nutrient and/or the high rainfall + precipitation in the Amazon region which increased the K losses by leaching [35]. Nevertheless, high + -1 amounts of K (>2.3 mmol kg ) were observed in ADE 2 (Table III), where the maximum amounts at point -1 + 4 were 6.1 (0-20 cm) and 5.9 mmol kg (20-40 cm). In ADE 1, the highest K concentration was 1.6 mmol -1 kg (point 1 at 0-20 cm) (Table II), interpreted as average (from 1.1 to 2.3 mmol kg-1) [36]. Some studies on chemical characterization of ADE soils have shown that K+ levels are lower than the P, 2+ 2+ -1 Ca and Mg . Falcão and Borges reported values of 1.9 and 1.2 mmol kg in ADE fertilized and nonfertilized, respectively, from Iranduba, AM, Brazil [14]. These results show that ADE exhibits an average content of exchangeable K+ very close to the lower limit of the range considered appropriate for most crops. In this way, supplementary potassium fertilization is necessary in order to obtain satisfactory production. The K+ amounts are generally low in ADE, although still higher than those observed in non-anthropogenic areas. Moreover, the higher K+ levels observed in adjacent soil surfaces may be related to the recent incorporation of plant residues. This may be associated with higher incorporation of residues containing potassium (leaves and vegetable residues) in ADE, or even cycling K+ in plants, which can be absorbed by the roots or even incorporated in their tissues [37]. The exchangeable aluminum values (Al3+) were low (<2.0 mmol kg-1) in all depths of ADEs and nonanthropogenic soils, with higher levels observed in the latter (Tables II-IV). This occurred probably because of the considerable amounts of exchangeable bases, notably in ADE sites, corroborating the observation of Brasil and Cravo [36]. These results show that ADEs offer no problems with toxicity of Al3+ to plants [5].
39
Chemical characteristics of Amazonian Dark Earth in Santarem, Brazil
Article
Table II. Chemical characteristics of the ADE 1 pH (H2O)
pH (KCl)
ΔpH
Porg (mg kg-1)
Pava (mg kg-1)
Ca2+ (mmol kg-1)
Mg2+ (mmol kg-1)
K+ (mmol kg-1)
Al3+ (mmol kg-1)
(1) 0-20
6.05±0.03
5.26±0.02
-0.79
159±10
233±11
2242±34
69.1±1.9
1.6±0.16
Nd
(2) 20-40
5.48±0.02
4.85±0.02
-0.63
58±8
842±12
1812±30
38.3±0.9
0.4±0.05
0.1±0.05
(3) 40-60
5.86±0.03
5.04±0.02
-0.82
86±8
738±13
1770±27
32.6±0.7
0.3±0.05
Nd
(4) 60-80
5.83±0.03
5.13±0.02
-0.70
90±6
332±14
1199±20
33.7±0.8
0.1±0.05
Nd
(5) 80-100
5.94±0.03
5.19±0.02
-0.75
128±9
565±15
843±20
32.6±0.8
0.8±0.10
Nd
(6) 0-20
7.72±0.04
6.61±0.03
-1,11
1412±61
672±12
1550±37
Nd
0.2±0.05
Nd
(7) 20-40
7.29±0.03
6.00±0.03
-1.29
722±13
691±10
1859±38
Nd
0.1±0.05
Nd
(8) 40-60
5.82±0.03
4.94±0.02
-0.88
246±8
228±8
1424±27
Nd
0.1±0.05
0.1±0.05
(9) 60-80
5.73±0.03
4.84±0.02
-0.89
55±7
608±10
769±18
Nd
0.1±0.05
0.1±0.05
(10) 80-100
8.22±0.07
6.70±0.03
-1.52
281±13
676±11
465±6
Nd
0.8±0.11
Nd
(11) 0-20
5.04±0.02
4.87±0.02
-0.17
459±11
1327±19
3352±44
12.0±0.5
0.5±0.10
0.1±0.05
(12) 20-40
5.08±0.02
4.89±0.03
-0.19
651±11
2744±60
2242±38
Nd
0.2±0.05
0.1±0.05
(13) 40-60
5.45±0.03
5.02±0.03
-0.43
41±7
2544±49
1775±32
Nd
0.2±0.05
Nd
(14) 60-80
5.96±0.03
5.09±0.02
-0.87
530±12
1172±35
1576±33
Nd
0.1±0.04
Nd
(15) 80-100
6.09±0.03
5.17±0.02
-0.92
135±10
204±10
1021±14
Nd
1.6±0.12
Nd
(16) 0-20
5.44±0.03
4.71±0.04
-0.73
356±10
1138±44
1445±17
24.6±0.6
0.3±0.04
0.2±0.05
(17) 20-40
5.78±0.03
4.93±0.03
-0.85
56±6
598±16
2105±35
36.0±0.8
0.2±0.05
Nd
(18) 40-60
5.95±0.02
5.08±0.02
-0.87
235±10
250±9
1162±19
32.7±0.8
0.1±0.04
Nd
(19) 60-80
5.99±0.04
5.18±0.03
-0.81
19±2
230±8
911±11
Nd
0.1±0.04
Nd
(20) 80-100
5.58±0.02
5.83±0.02
-0.25
153±7
449±12
670±5
Nd
0.8±0.06
Nd
(21) 0-20
7.28±0.05
6.63±0.04
-0.65
277±8
785±4
2242±49
10.9±0.4
0.2±0.05
Nd
(22) 20-40
7.21±0.04
6.11±0.04
-1.10
483±9
904±8
1398±28
Nd
0.3±0.05
Nd
(23) 40-60
7.26±0.04
6.41±0.03
-0.85
323±9
316±6
1660±28
Nd
0.2±0.05
Nd
(24) 60-80
7.62±0.04
6.44±0.02
-1.85
417±5
367±12
685±14
Nd
Nd
Nd
(25) 80-100
5.43±0.02
4.62±0.03
-0.81
116±7
828±14
1000±18
Nd
0.4±0.04
0.3±0.06
Depth (cm) Collect point 1
Collect point 2
Collect point 3
Collect point 4
Collect point 5
40
da Silva, D. S.; Cardoso, J. C. A.; Lima, B. C. C.; Vasconcelos, A. A.; Rebellato, L.; Schaan, D. P.; Gomes, D. M. C.; Couto, R. R.; Brunetto, G.; Taube, P. S.
Article
Table III. Chemical characteristics of the ADE 2 pH (H2O)
pH (KCl)
ΔpH
Porg (mg kg-1)
Pava (mg kg-1)
Ca2+ (mmol kg -1)
Mg2+ (mmol kg -1)
K+ (mmolc kg-1)
Al3+ (mmol kg -1)
(26) 0-20
5.85±0.01
5.38±0.03
-0.47
197±12
967±14
1220±28
41.7±1.0
0.8±0.05
Nd
(27) 20-40
5.82±0.03
5.03±0.04
-0.79
107±8
26±9
911±11
42.8±1.1
0.7±0.06
0.1±0.04
(28) 40-60
5.53±0.04
4.60±0.03
-0.93
31±4
951±13
586±7
46.3±1.1
0.2±0.04
0.3±0.05
(29) 60-80
5.47±0.03
4.49±0.02
-0.98
38±4
812±7
397±4
49.7±1.6
0.4±0.05
0.4±0.05
(30) 80-100
5.42±0.02
4.28±0.03
-1.14
60±5
538±8
172±3
47.4±1.5
0.3±0.06
0.1±0.05
(31) 0-20
5.45±0.04
4.49±0.03
-0.96
67±5
234±10
1508±36
46.0±1.8
2.0±0.23
0.2±0.05
(32) 20-40
5.01±0.02
3.76±0.05
-1.25
77±8
255±5
465±10
47.4±1.7
4.8±0.34
1.2±0.12
(33) 40-60
4.68±0.03
3.70±0.06
-0.98
68±6
250±7
130±3
36.0±1.5
1.9±0.19
1.1±0.10
(34) 60-80
4.97±0.03
3.92±0.06
-1.05
220±9
978±10
8.9±0.3
41.7±1.3
3.4±0.26
0.7±0.04
(35) 80-100
5.22±0.02
4.13±0.02
-1.09
43±6
946±10
560±10
45.1±1.6
4.5±0.28
0.3±0.05
(36) 0-20
5.48±0.02
4.66±0.03
-0.82
233±7
1238±16
2194±43
53.1±2.3
2.4±0.15
0.4±0.05
(37) 20-40
5.45±0.02
4.47±0.02
-0.98
132±6
980±8
1086±23
47.4±1.5
1.8±0.09
0.2±0.04
(38) 40-60
5.45±0.03
4.53±0.02
-0.92
158±8
418±8
1891±38
46.3±1.4
1.1±0.07
0.2±0.05
(39) 60-80
5.79±0.02
4.92±0.03
-0.87
258±5
720±7
1848±37
42.8±1.4
0.6±0.05
Nd
(40) 80-100
5.89±0.03
5.13±0.03
-0.76
58±6
441±13
1277±30
39.4±1.3
0.6±0.03
Nd
(41) 0-20
6.12±0.03
5.38±0.03
-0.74
294±7
309±7
2373±59
130.8±3.0
6.1±0.35
0.1±0.06
(42) 20-40
4.82±0.03
3.73±0.04
-1.09
90±9
213±5
712±20
53.1±1.3
5.9±0.30
1.1±0.10
(43) 40-60
4.57±0.02
3.53±0.06
-1.04
94±7
210±6
224±4
36.0±0.9
1.6±0.14
1.6±0.11
(44) 60-80
4.56±0.04
3.60±0.05
-0.96
37±3
863±11
88±2
33.7±0.8
1.2±0.09
1.4±0.08
(45) 80-100
4.68±0.02
3.72±0.06
-0.96
47±3
528±8
83±2
33.7±0.9
1.1±0.12
1.1±0.12
(46) 0-20
5.58±0.03
4.73±0.03
-0.85
1352±22
399±5
3876±93
80.5±1.9
3.6±0.26
0.1±0.05
(47) 20-40
5.42±0.03
4.66±0.03
-0.76
159±6
243±5
1953±42
42.8±1.2
1.0±0.08
0.1±0.04
(48) 40-60
5.30±0.03
4.45±0.04
-0.85
154±6
871±8
1162±22
41.7±1.1
0.5±0.05
0.3±0.05
(49) 60-80
5.01±0.02
4.09±0.03
-0.92
62±4
242±7
743±21
38.3±1.0
0.3±0.06
0.6±0.06
(50) 80-100
5.09±0.03
4.04±0.04
-1.05
34±3
1250±21
467±10
38.3±1.1
0.5±0.07
0.5±0.05
Depth (cm) Collect point 1
Collect point 2
Collect point 3
Collect point 4
Collect point 5
Nd: Below Limit of Detection
41
Chemical characteristics of Amazonian Dark Earth in Santarem, Brazil
Article Table IV. Chemical characteristics of the non-anthropogenic soil pH (H2O)
pH (KCl)
ΔpH
Porg (mg kg-1)
Pava (mg kg-1)
Ca2+ (mmol kg-1)
Mg2+ (mmol kg-1)
K+ (mmol kg-1)
Al3+ (mmol kg-1)
(51) 0-20
4.45±0.04
4.17±0.04
-0.28
222±9
21±3
628±12
4.0±0.1
0.6±0.06
1.8±0.20
(52) 20-40
4.58±0.03
4.14±0.05
-0.44
55±4
10±1
376±8
Nd
0.6±0.05
1.0±0.11
(53) 40-60
4.65±0.04
4.15±0.05
-0.50
61±5
8±1
256±5
Nd
0.5±0.06
0.9±0.06
(54) 60-80
4.57±0.02
4.15±0.06
-0.42
50±6
9±1
261±6
Nd
0.4±0.05
1.0±0.01
(55) 80-100
4.96±0.02
4.15±0.05
-0.81
62±6
15±1
151±4
Nd
0.4±0.05
1.1±0.12
(56) 0-20
4.99±0.03
4.07±0.06
-0.92
52±3
9±1
156±3
Nd
0.2±0.04
0.9±0.12
(57) 20-40
4.60±0.04
4.01±0.06
-0.59
61±4
9±1
4±1
Nd
0.1±0.05
1.0±0.08
(58) 40-60
4.90±0.04
4.07±0.05
-0.83
54±4
8±1
Nd
Nd
0.1±0.06
1.0±0.5
(59) 60-80
4.26±0.03
4.11±0.05
-0.15
28±3
6±1
99±2
Nd
0.2±0.05
1.0±0.6
(60) 80-100
4.33±0.04
4.13±0.05
-0.20
28±2
7±1
4±1
Nd
0.1±0.03
1.0±0.5
(61) 0-20
5.38±0.03
4.74±0.04
-0.64
112±4
23±2
1765±46
46.3±1.4
3.0±0.18
Nd
(62) 20-40
5.52±0.03
5.08±0.03
0.44
92±3
18±1
979±25
14.3±0.3
3.1±0.23
Nd
(63) 40-60
5.32±0.03
4.98±0.04
-0.34
101±6
14±1
387±10
Nd
0.2±0.05
0.2±0.05
(64) 60-80
5.81±0.02
4.73±0.04
-1.08
54±4
12±1
313±11
Nd
0.2±0.04
0.2±0.05
(65) 80-100
4.75±0.04
4.38±0.03
-0.37
85±5
12±1
439±12
Nd
0.3±0.05
0.4±0.06
(66) 0-20
6.18±0.02
5.88±0.04
-0.30
108±6
16±2
1807±43
24.6±0.7
0.4±0.05
Nd
(67) 20-40
5.70±0.03
5.58±0.03
-0.12
44±4
20±1
26±1
8.6±0.2
0.3±0.04
Nd
(68) 40-60
5.19±0.03
4.82±0.03
-0.37
92±5
6±1
355±10
Nd
0.6±0.08
0.3±0.06
(69) 60-80
5.51±0.02
4.52±0.04
-0.99
52±5
3±0.4
Nd
Nd
0.1±0.06
0.5±0.05
(70) 80-100
5.01±0.03
4.20±0.04
-0.81
41±4
2±0.4
Nd
Nd
0.1±0.04
0.2±0.04
(71) 0-20
4.88±0.03
4.10±0.04
-0.78
128±7
19±1
347±8
8.1±0.3
0.2±0.06
Nd
(72) 20-40
4.56±0.03
4.15±0.06
-0.41
38±3
10±1
283±8
2.3±0.1
0.1±0.05
Nd
(73) 40-60
4.76±0.03
4.05±0.04
-0.71
27±0.4
6±1
192±4
Nd
0.2±0.05
0.3±0.05
(74) 60-80
4.82±0.02
4.07±0.05
-0.75
20.±1
4±1
167±3
Nd
0.1±0.05
0.2±0.05
(75) 80-100
4.78±0.03
4.11±0.04
-0,67
8±1
2±1
146±4
Nd
0.1±0.04
0.2±0.04
Depth (cm) Collect point 1
Collect point 2
Collect point 3
Collect point 4
Collect point 5
Nd: Below Limit of Detection
42
da Silva, D. S.; Cardoso, J. C. A.; Lima, B. C. C.; Vasconcelos, A. A.; Rebellato, L.; Schaan, D. P.; Gomes, D. M. C.; Couto, R. R.; Brunetto, G.; Taube, P. S.
Article
High levels of Pava were observed in all depths of both ADEs, with the highest levels observed for ADE 1 (Tables II and III). The minimum and maximum amounts of Pava ranged from 204 mg kg-1 (20-40 cm) to 2740 -1 mg kg (80-100 cm) in point 3 (Table II), whereas ADE 2, the minimum and maximum Pava values were 213 mg kg-1 (point 4, depth 20-40 cm) and 1250 mg kg-1 (point 5, depth 80-100 cm), respectively (Table III). On the other hand, in non-anthropogenic soil the maximum amount was 22.6 mg kg-1 (point 3, depth 0-20 cm), which was around 121 and 55 times lower than the maximum amount found, respectively, in ADE 1 and ADE 2 (Table IV). These higher levels of available phosphorus in the anthropogenic layers are due to the high incorporation of residues, mainly animal remains [38]. -1 -1 The maximum amounts of Porg were 1410 mg kg (point 1, depth 0-20 cm) (Table II) and 1350 mg kg (point 5, depth 0-20 cm) (Table III), respectively, in ADE 1 and ADE 2, while the value in the nonanthropogenic soil was 222 mg kg-1 (point 1, depth 0-20 cm) (Table IV). Fraser and Clement evaluated ADE in the Amazonic region and attributed these high Porg and Pava values to the addition of animal bones by preColumbian people [38]. Regarding variance analysis, the ďŹ rst component explained 45.1% and 47.7%, and the second component explained 20% and 22.8% of the variance among the investigated parameters in soil samples, respectively, from the ADE 1 and non-anthropogenic soil; and between ADE 2 and non-anthropogenic soil (Figures 2a and b). The points referring to the non-anthropogenic area were not weighted in one of the parameters that compose each principal component, according to the simultaneous analysis involving scores and loadings. This shows that these parameters did not show high variability in these points, nor enough correlation to be accountable for a group formation (Figure 2). Porg, Pava, pH values in water and KCl had potential to discriminate ADE 1 from adjacent soil, once some non-anthropogenic soils were observed in this group. The remaining ADE 1 samples formed a distinct 2+ + 3+ 2+ group from Mg , K and Al . The higher weight to the formation of this group was assigned to the Mg amount (Figure 2A and 2B). 2+ 2+ The Pava and Ca had the highest correlations at the ADE 1 and ADE 2, and pH in water and KCl, Ca , Porg and Pava had a positive correlation (Figure 2F). This high correlation is associated with the incorporation of human and animal bone remains [32-33]. Furthermore, Al3+, K+ and Mg2+ were negatively correlated + (Figure 2). In both anthropogenic soils, the K amount had the least correlation with other attributes. This may have been favored by the low concentrations of this cation, in addition to the fact that the sandy soil texture and water regime favored its leaching in the soil proďŹ le [39], since the only valence load is poorly adsorbed on soil colloids [40]. The strongest correlations between ADE 1 and ADE 2 were observed in relation to pH values in water and in KCl (Figure 2F).
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Chemical characteristics of Amazonian Dark Earth in Santarem, Brazil
Article
Figure 2. Principal component analysis of the averages of chemical attributes between ADE 1 (■) and non-anthropogenic soil (▲) (A and B); ADE 2 (●) and non-anthropogenic soil (▲) (C e D); and ADE 1 (■) and ADE 2 (●) (E e F). (A, C and E) Scores. (B, D and F) Loadings. Numbers refer to the Tables I, II and III.
44
da Silva, D. S.; Cardoso, J. C. A.; Lima, B. C. C.; Vasconcelos, A. A.; Rebellato, L.; Schaan, D. P.; Gomes, D. M. C.; Couto, R. R.; Brunetto, G.; Taube, P. S.
Article
CONCLUSION The amount of Porg, Pava, Ca2+ and Mg2+ as well as pH values in water and in KCl were higher in ADE in + relation to non-anthropogenic soils, and his aspects gives rise to the soil increased fertility. The low K amounts in both ADEs may be limiting for some crops if they not receive additional fertilization with this 2+ nutrient. The high amounts of Porg and Pava and the correlation with Ca amount in anthropogenic soils is directly related to bone incorporation, possibly of fish. The pH values in water and KCl have the potential to differentiate anthropogenic from non-anthropogenic soils. ACKNOWLEDGEMENTS This work was supported by the Brazilian Federal entities CNPq (National Council for Scientific and Technological Development) and CAPES (Coordination of Improvement of Higher Education Personnel). Conflict of Interest Statement The authors declare no conflict of interest. Manuscript received: 10/02/18; revised manuscript received: 11/03/18; revised manuscript for the 2nd time received: 11/14/18; manuscript accepted: 11/14/18; published online November 28, 2018.
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30. Lehmann, J.; Kern, D. C.; Glaser, B.; Woods W. I. Amazonian Dark Earths: origin, properties, management. Kluwer Academic Publisher. Dordrecht, 2003, p 523. 31. Liang, B.; Lehmann, J.; Solomon, D.; Kinyangi, J.; Grossman, J.; O'Neill, B.; Skjemstad, J. O.; Thies, J.; Luizão, F. J.; Petersen, J.; Neves, E. G. Soil Sci. Soc. Am. J., 2006, 70, pp 1719-1730 (DOI: 10.2136/sssaj2005.0383). 32. Steiner, C.; Teixeira, W. G.; Lehmann, J.; Zech, W. Microbial response to charcoal amendments of highly weathered soils and Amazonian dark earth in Central Amazonia: preliminary results. In: Glaser, B.; Woods, W. I. (Ed). Amazonian dark earths: explorations in space and time. Springer, New York, 2004, pp 195-212. 33. Novotny, E. H.; Azeredo, E. R.; Bonagamba, T. J.; Cunha, T. J. F.; Madari, B. E.; Benites, V. M.; Hayes, M. H. Environ. Sci. Technol., 2007, 41, pp 400-405 (DOI: 10.1021/es060941x). 34. Kern, D. C.; Costa, M. L.; Frazao, F. J. L. Geoquímica de sítio arqueológico com Terra Preta de Índio no centro da cidade de Quatipuru-PA. In: VI Simpósio de Geologia da Amazônia, Manaus, SBG, 1999, p 408. 35. Grimaldi, C.; Grimaldi, M.; Millet, A.; Bariac, T.; Boulegue, J. Hydrol. Process., 2004, 18, pp 93-106 (DOI: 10.1002/hyp.1314). 36. Brasil, E. C.; Cravo, M. S. Interpretação dos resultados de análises de solo. In: Cravo, M. S. et al. (Ed). Recomendações de adubação e calagem para o Estado do Pará. Belém, PA, Embrapa Amazônia Oriental, 2007, pp 43-48. 37. Viana, E. M.; Kiehl, J. C. Bragantia, 2010, 69, pp 975-982 (DOI: 10.1590/S0044-59672006000400001). 38. Fraser, J. A.; Clement, C. R. Bol. Mus. Para. Emílio Goeldi. Cienc. Hum., 2008, 3, pp 175-194 (DOI: 10.1590/S1981-81222008000200004). 39. Neves, L. S.; Ernani, P. R.; Simonete, M. A. Rev. Bras. Cienc. Solo, 2009, 33, pp 25-32 (DOI: 10.1590/S0100-06832009000100003). 40. Ernani, P. R.; Bayer, C.; Almeida, J. A.; Cassol, P. C. Rev. Bras. Cienc. Solo, 2007, 31, pp 393-402 (DOI: 10.1590/S0100-06832007000200022).
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Br. J. Anal. Chem., 2018, 5 (20), pp 48-59 DOI: 10.30744/brjac.2179-3425.2018.5.20.48-59
Technical Note
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Quantification of Hydroxyl Groups from Alumina in Aluminosilicate Materials by Adsorption Isotherms Allyson Leandro Rodrigues dos Santos, Rosana Maria Nascimento de Assunção and Anizio Marcio de Faria* Instituto de Ciências Exatas e Naturais do Pontal, Universidade Federal de Uberlândia Rua Vinte, 1600, 38304-402, Ituiutaba, MG, Brazil. Graphical Abstract
A simple and accessible method without the use of expensive and specific reagents is presented in this work for the quantification of hydroxyl groups from alumina in aluminized silica. The method is based on the differential interaction of a dye on bare silica and on aluminized silica surfaces due to the electrostatic repulsion of dye molecules by Al–OH groups in aluminized silica, and subsequent spectrophotometric quantification. The adsorbate molecule used for this Determination of Al-OH content in aluminized silica by the removal of malachite green from aqueous solution study was malachite green. The difference between under controlled pH condition. amount of malachite green retained on bare silica and aluminized silica remained constant when the ratio of active sites on the support to malachite green molecules was not very different. The results indicated that the method presents sensitivity and selectivity for the determination of hydroxyl groups in aluminosilicate materials with high repeatability, making possible the quantification of Al-OH in aluminosilicates without the use of sophisticated scientific instruments. Keywords: Aluminized silica, malachite green, molecular absorption spectroscopy, Al–OH sites. INTRODUCTION For many years silica has been the main material used as chromatographic support for reversed-phase liquid chromatography (RP-LC). This wide use is associated with its pore structure; fully compatible with the mechanisms of chromatographic separation, producing stationary phases of greater efficiency in the resolution of several chemical species [1,2]. However, the limitation of silica-based stationary phases to a restricted pH range between 2 and 8 promoted a growing search for more stable inorganic oxides, mainly in alkaline medium, as supports for RP-LC [2-4]. Coating the silica with metal oxide layer was shown to be one of the most successful strategies in the preparation of chromatographic supports and led to the expansion of application field of RP-LC without loss in separation efficiencies [5-9]. More recently, silica coated with alumina has been presented as a chromatographic support that, in addition to greater chemical stability, results in a lower residual activity in separations by HPLC compared to coating with other metallic oxides [10-13]. Thus, polar solutes are not retained on the phases of aluminized silica as strongly as they are on silica coated with other metal oxides, such as zirconia [14,15] and titania [14,16].
*anizio@ufu.br https://orcid.org/0000 -0001 -6915 -8963
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Quantification of Hydroxyl Groups from Alumina in Aluminosilicate Materials by Adsorption Isotherms
Technical Note
The alumina surface activity is related to concentration of hydroxyl groups attached to aluminum atoms on the aluminized silica surface and available to interact with the solutes in a chromatographic separation process. A high concentration of Al–OH groups may lead to a reduction in the degree of surface coating due to the lower reactivity of these groups compared to silanols (Si–OH) in the preparation of reversed stationary phases, and also to an increase in residual activity, an undesirable interaction of acidic or basic compounds with these groups due to the amphoteric character of alumina [3,4,17]. Therefore, Al–OH group content on the surface of chromatographic supports is an important factor in obtaining both a stable and efficient support material for chromatographic purposes. The determination of alumina activity on aluminized silica requires selective procedures to discriminate the hydroxyl groups from alumina from those of other oxides [18-21]. Most of the time this determination is performed directly by instrumental techniques, such as solid state nuclear magnetic resonance [19,21], infrared absorption spectroscopy [20,22], thermogravimetric analysis [22], etc. In all cases, it is necessary to use specific and high-purity reagents or high-cost instrumentation techniques that are difficult to access for most research laboratories. Therefore, the development of simpler and more easily accessible methods, without the need for specific reagents for the determination of the concentration of active surface groups of alumina, can lead to obtaining the desired information in a less expensive, faster and equally reliable manner. In this work, a simple method, possible to be performed in most chemistry laboratories, without the need for specific scientific instrumentation and/or expensive and expensive reagents, is proposed for the determination of active alumina groups in solid aluminized silica materials. The method is based on measuring the absorbance of a colored substance in solution before and after contact with an aluminacontaining adsorbent. The quantification of these active groups of alumina is carried out from the consequent discoloration of the solution and subsequent analysis by molecular absorption spectroscopy in the visible region. MATERIALS AND METHODS Materials The chromatographic support used in the study was 5 μm spherical Microsorb silica (Varian, Palo Alto, CA, USA). For the preparation of aluminized silica, isooctane analytical grade from Synth (Diadema, SP, Brazil), aluminum isopropoxide (99%) and sodium bis(2-ethylhexyl)sulfosuccinate (>97%) from SigmaAldrich (São Paulo, SP, Brazil), and nitric acid (65%) from Carlo Erba (Milan, Italy), were used. Sodium chloride PA and Malachite Green chloride (MG) of analytical grade purchased from Synth, and ultrapure water (resistivity > 18 MΩ cm) obtained from a Megapurity purification system (Billerica, MA, USA) were used in the study of adsorption isotherms. All solvents were individually filtered prior to use in a mobilephase filtration system employing nylon membranes with 0.22 μm pore diameter from Millipore (São Paulo, SP, Brazil). Synthesis of aluminized silica particles by intra-micellar sol-gel process Alumina particles were produced by a sol-gel process within the sodium bis(2-ethylhexyl) sulfosuccinate micelles, Na(AOT), according to the method of Silveira et al. [11]. Briefly, Na(AOT) reversed micelles were produced in isooctane by adding 2.440 g of the surfactant to 36 mL of solvent under gentle and continuous stirring in a refluxing system at 100 °C. Then 1.0 mL of ultrapure water and 0.250 g of aluminum isopropoxide were added to the Na(AOT) microemulsion, ensuring a ratio of surfactant/aluminum isopropoxide/water equal to 90.0:5.4:4.6 w/w/w. The reaction mixture was stirred for 2 h at 100 °C. Subsequently, 900 μL of HNO3 solution at 0.01 mol L-1 was added to the reaction medium. After peptization, the blend was aged for 24 h under constant stirring at 100 °C. After this period the mixture was centrifuged at 2500 rpm for 5 min and the alumina gel phase separated.
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dos Santos, A. L. R.; de Assunção, R. M. N; de Faria, A. M.
Technical Note
The alumina gel phase contained within the Na(AOT) reversed micelles was incorporated onto the surface of spherical silica particles using the layer-by-layer self-assembly technique. The alumina gel covered by a Na(AOT) layer was added to 20 mL of isooctane under stirring at 100 °C. After 2 h, 1.500 g of silica previously activated at 140 °C for 12 h was added to the reaction medium under reflux and kept under constant stirring for 24 h. The surfactant layer on alumina gel acted as a 'glue' on the silica microspheres. After the reaction, the mixture was filtered on 0.22 μm pore diameter nylon membranes and the solid material was calcined at 500 °C for 30 min. The calcined material was washed sequentially with isooctane, toluene, isopropanol, methanol and ultrapure water. The silica particles were coated with a layer of alumina nanoparticles, and referred to as aluminized silica. Adsorption of malachite green on chromatographic supports Adsorption kinetics of malachite green To evaluate the adsorption kinetics of malachite green (MG) on silica and aluminized silica, 10 mg of solid material was added to Eppendorf tubes containing 1 mL of an aqueous solution of MG at 100 mg L-1. Twelve aqueous solutions of MG in 0.010 mol L-1 NaCl were prepared, adjusting pH to 5.00 before the study. The tubes were gently stirred at time intervals from 0 to 120 min, maintaining a constant temperature of 27 °C. The absorbances of aliquots of the solutions, without solid material particles, were measured at 610 nm in a PerkinElmer UV-vis spectrophotometer, model Lambda 25 (Waltham, MA, USA) to determine the concentration of unretained MG on silica and aluminized silica. All experiments were performed in triplicate. Adsorption isotherms of malachite green The MG adsorption experiments on silica and aluminized silica were performed by adding 10 mg of the -1 solid materials to Eppendorf tubes containing 1.00 mL of MG solution in 0.01 mol L NaCl at pH 5 over a -1 range of concentrations of 0.1 to 300.0 mg L . The tubes were stirred gently for 5 min and then centrifuged at 3000 rpm for 2 min. Aliquots of supernatant were analyzed by molecular absorption spectroscopy in the visible region. All experiments were conducted at 27 °C and performed in triplicate. The experimental data obtained were used for the construction of adsorption isotherm curves of MG on bare silica and aluminized silica. Characterization of aluminized silica supports Specific surface area and porosity The specific surface areas of silica and aluminized silica were determined by adsorption of nitrogen in the dry state, following the conventional BET (Brunauer, Emmet and Teller) method with an ASAP 2010 instrument from Micromeritics (Norcross, GA, USA). Scanning electron microscopy and energy-dispersive X-ray spectroscopy The alumina content on aluminized silica supports was determined by an X-ray energy dispersion spectrometer coupled to a TESCAN scanning electron microscope, model Vega3 (Brno, Czech Republic) at an acceleration voltage of 20 kV. The samples were prepared by fixing the silica and aluminized silica particles to conductive double-sided carbon tape, and coating with a gold film layer to increase the conductivity. RESULTS AND DISCUSSION Characterization of aluminized silica support Scanning electron microscopy and energy-dispersive X-ray spectroscopy The aluminum content in the aluminized silica support was determined by dispersive energy spectroscopy (EDS). Twelve distinct regions in three typical scanning electron micrographs of aluminized 50
Quantification of Hydroxyl Groups from Alumina in Aluminosilicate Materials by Adsorption Isotherms
Technical Note
silica particles were analyzed by EDS and the obtained spectra were used for quantification of elements. Figure 1 shows a typical spectrum of one of the spectrally analyzed regions in aluminized silica micrographs. 1000
Si
800 O
). u. a( st nu o C
600
400
200
Al
Au
Au
0 0
2
4 6 E n e rg y (k e V )
8
10
Figure 1. EDS spectrum of the aluminized silica sample
The EDS spectrum in Figure 1 indicates the presence of aluminum in aluminized silica support. The average aluminum content, as a mass percentage, obtained from twelve distinct regions in micrographs of aluminized silica particles was 1.61 ± 0.14% w/w. By converting this amount to the alumina content, the aluminized silica contained 3.05 ± 0.27% w/w alumina on average. The small dispersion around the average alumina content indicates a regular distribution of metal oxide onto the silica surface. The relatively low content of alumina in the aluminized silica support is sufficient to increase its stability under alkaline mobile phase conditions without causing significant loss of separation efficiency. The activity of hydroxyl groups bound to the aluminum atoms was obtained by adsorption studies. Micrographs of bare and aluminized silica are presented in Figure 2. It can be seen from the SEM images in Figure 2 that, in contrast to the bare silica particles, the aluminized silica has a layer of smaller alumina particles into the silica microsphere surface. (a)
(b)
Figure 2. SEM images of (a) bare silica and (b) aluminized silica samples
Specific surface area and porosity The specific surface area, pore volume and pore diameter of aluminized silica particles were determined by the physisorption technique. The morphological information of both silica and aluminized silica particles used in this study is presented in Table I.
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dos Santos, A. L. R.; de Assunção, R. M. N; de Faria, A. M.
Technical Note
Table I. Morphological information of silica and aluminized silica particles
Specific surface area (m 2 g-1)
Pore volume (cm 3 g-1)
Pore diameter (nm)
Alumina content (%)
Bare silica
219 ± 3
0.67 ± 0.02
12.2 ± 0.5
< 0.01
Aluminized silica
212 ± 7
0.54 ± 0.04
10.5 ± 0.6
3.05 ± 0.27
Material
Despite the incorporation of about 3% alumina onto the silica microparticles, the specific surface area of aluminized silica was not significantly reduced when compared to the bare silica. The deposition of alumina occurred onto the surface and into the pores of the silica particles, as there was a reduction of pore diameter and pore volume of the silica after incorporation of alumina. The active groups of silica, silanols (Si–OH), are distributed on the silica surface, but are mostly found inside the pores of mesoporous materials. Considering that the alumina is deposited on the silica by interaction/reaction with Si–OH groups, a small reduction in the pore parameters of the aluminized silica was to be expected. This morphological information is important in determining the content of active Al–OH groups on the aluminized silica surface because the molecule used in the adsorption study must be able to access all the pores of the chromatographic support. Studies of adsorption of malachite green onto aluminized silica particles The determination of Al–OH content in the aluminized silica support was carried out by the study of interaction of malachite green (MG) onto the silica and aluminized silica supports, with subsequent analysis of the adsorbate solutions by absorption spectroscopy in the visible region. In this study, the pH of the solutions was adjusted to 5, since the isoelectric point of alumina is at pH 8,23 while that of silica is at about pH 2 [24]. In slightly acidic medium (pH 5), the alumina and the MG will be positively charged [25], while the silica is negatively charged. Thus, the aluminized silica will electrostatically repel the MG, keeping the solution greenish in color. On the other hand, the negatively charged silica sites will attract the MG onto its surface, decolorizing the solution. The higher the content of Al–OH sites on the aluminized silica support the lower the amount of MG retained on its surface, the less decolorization of the solution. It is important to emphasize that although we believe that the mechanism of ion exchange established between the adsorbate and the adsorbents is predominant, other interaction processes can also occur mainly under different dye concentrations in solution, in this way, we will use the term adsorption in this text to generalize the adsorbent-adsorbate interaction process. Figure 3 shows the distribution of MG species according to the pH of the aqueous solution.
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Quantification of Hydroxyl Groups from Alumina in Aluminosilicate Materials by Adsorption Isotherms
Technical Note
Figure 3. (a) Chemical equilibrium of malachite green in aqueous solution. (b) Graph of distribution of malachite green (MG) species in aqueous solution as a function of pH [26].
The concentration of MG in solution that was not retained on silica or on aluminized silica was determined by constructing an analytical curve for the malachite green. The linear equation, obtained by linear regression -1 of absorbance data for MG solutions in 0.01 mol L NaCl in the concentration range of 0.005 to 5.000 mg L-1, was: A = 0.1503 CMG – 0.0052, with coefficient of determination R2 = 0.9997. Adsorption kinetics of malachite green on aluminized silica Adsorption is a multi-stage process that involves transporting MG molecules from aqueous phase to the surface of aluminized silica particles, followed by the diffusion of molecules dissolved within the pores of the support. The adsorption kinetics represent the change in ratio with time of the amount of free MG to that adsorbed on the aluminized silica. The effect of time on the adsorption of MG on aluminized silica support is shown in Figure 4.
Figure 4. (a) Curve for adsorption kinetics of malachite green on aluminized silica support. (b) Pseudo-second-order kinetic model for the adsorption of malachite green on aluminized silica 53
dos Santos, A. L. R.; de Assunção, R. M. N; de Faria, A. M.
Technical Note
From Figure 4 the adsorption of MG on aluminized silica was initially very fast, reaching equilibrium in around 5 min, from when it remained practically constant. The mechanism involved in the kinetics for the removal of MG from the solution by the aluminized silica support was investigated by applying the experimental data in the equation for the pseudo-first-order (Equation 1), pseudo-second-order (Equation 2) and intraparticle diffusion kinetic models [27] (Equation 3). log(qe – qt) = log(qe) – k1t/2.303 (1) qe (meq g-1) and qt (meq g-1) are the amounts of MG adsorbed per unit mass of aluminized silica at -1 equilibrium and at any time t, respectively; (min ) is the constant of pseudo-first-order adsorption rate. t/qt = 1/(k2qe2) + t/qe (2) -1
-1
qe (meq g ) and qt (meq g ) are the amounts of MG adsorbed per unit mass of aluminized silica at equilibrium and at any time t, respectively; (g meq-1 min-1) is the constant of pseudo-second-order adsorption rate, which is obtained by the angular coefficient of the curve in Figure 3(b). qt = kit1/2 + C (3) -1
qt (meq g ) is the amount of MG adsorbed per unit mass of aluminized silica at any time t; (meq g min-0.5) is the constant of intraparticle diffusion rate and C is the coefficient of linear regression.
-1
A better fit with the data occurs with the pseudo-second-order kinetic model for the MG adsorption on 2 aluminized silica, confirmed by the coefficient of determination, R = 0.999, presenting it as the appropriate kinetic model and indicating the existence of chemisorption in the studied process. The chemisorption process can be explained by an ion exchange process between the positively charged MG and the deprotonated silanol groups in aluminized silica, under the pH condition studied. The rate constant for MG 3 -1 -1 adsorption was 3.12 × 10 g meq min , which means a rapid adsorption rate on aluminized silica. The value of qe calculated from the model was 1.14 × 10-3 meq g-1, while the experimental qe was 1.15 × 10-3 -1 meq g . Thus, the best fit to the pseudo-second-order mechanism can be confirmed by the proximity of the qe value determined experimentally and that calculated from the model equation. Table II summarizes the calculated parameters for the kinetic models. Table II. Kinetic parameters for the interaction of malachite green with aluminized silica particles
Pseudo-first-order k1 (min-1)
qe calc (meq g-1)
qe exp (meq g-1)
r
5.14 × 10-3
5.749 × 10 -3
1.14 × 10-3
0.399
qe calc (meq g-1)
qe exp (meq g-1)
r
h (meq g-1 min-1)
1.14 × 10-3
1.15 × 10-3
0.999
4.04 × 10-3
Pseudo-second-order k2 (g meq-1 min-1) 3.12 × 103 Intraparticle diffusion kdif (meq g-1 min-0,5) 6.62 ×
54
10-5
C
r
0.299
0.613
Quantification of Hydroxyl Groups from Alumina in Aluminosilicate Materials by Adsorption Isotherms
Technical Note
Isotherm models for the adsorption of malachite green on bare and aluminized silica The adsorption isotherms describe the equilibrium between adsorbent and adsorbate (solute) considering the ratio between the amount of solute adsorbed and that remaining in solution at a fixed temperature. Since the adsorption phenomenon depends on the interactions between the surface of the adsorbent and the adsorbed species, it is possible to use information about the adsorption process to identify the surface modification of an adsorbent [28]. To investigate the surface modification of silica after incorporation of nanoparticles of alumina, the adsorption isotherms of MG on bare silica and on aluminized silica were evaluated using the isotherm models of Langmuir, Freundlich and Sips, Equations 4-6, respectively. qe = Qmax KL Ce /1 + KL Ce qe = KF Ce1/nF e = Qmax Ks CenS /1 + Ks CenS q
(4) (5) (6)
where: qe = amount of adsorbate per unit mass of adsorbent at equilibrium (meq g ); Ce = concentration of adsorbate at equilibrium (meq L-1); Qmax = maximum adsorption capacity (meq g-1); KL = Langmuir constant -1 related to the free energy of adsorption (L meq ); nF = Heterogeneity factor, which indicates adsorption intensity; KF = Freundlich constant, which indicate adsorption capacity; ns = Dimensionless heterogeneity factor; Ks = Sips equilibrium constant related to the free energy of adsorption (L meq-1) -1
The Langmuir and Freundlich isotherm models are the most used in the evaluation of adsorption processes. In the first case, the adsorption of a monolayer of the adsorbate occurs on the surface of the adsorbent due to the presence of homogeneous sites of the same energy. This process is characterized by Equation 4, developed from the equilibrium condition of the adsorption process. Freundlich's isotherm (Equation 5), on the other hand, admits a multilayer adsorption process and predicts the heterogeneity of adsorption sites on the adsorbent surface. The application of these two models to the MG adsorption data on bare silica and aluminized silica can be observed in Figure 5 and Table III. 0.012
0.012
(b)
(a) 0.009
0.009
Langmuir Freundlich
-1 qqee (meq g- )
)
Sips
1
)
0.006
e
qeq(meq g-1)1-
Isotherms Models
(
0.003
Isotherms Models
0.006 m
e
q
g
0.003
Langmuir Freundlich Sips
0.000 0.00015
0.00030 Ce L-1) Ce (meq (
m
e
q
0.00045 -1 L
)
0.000 0.00060
0.00015
0.00030
0.00045
0.00060
-1 CeCe (meq -1L ) (
m
e
q
L
)
Figure 5. Adsorption isotherm models of malachite green on (a) bare silica and (b) isotherm models of malachite green on aluminized silica in 0.01 mol L-1 NaCl solution at pH 5.00
The profile of experimental data shown in Figure 5 (a) is similar to the pattern of the predicted graph in the Langmuir model. In this model, the graph is characterized by the presence of a plateau at which saturation is observed, i.e. a molecule occupies the site and no additional adsorption occurs [29]. However,
55
dos Santos, A. L. R.; de Assunção, R. M. N; de Faria, A. M.
Technical Note
the non-linear regression of the experimental data in relation to the Langmuir and Freundlich models was not adequate, since the adjusted determination coefficient deviates from 1, indicating a poor fit of experimental data in relation to the predicted curves in each model. The application of the Freundlich model in the study of MG adsorption on aluminized silica, Figure 5(b), shows that the adsorption process is unfavorable, in this condition, since the convex profile of the curve -1 indicates low dye removal capacity within the range of MG concentrations studied, 0.05 to 0.15 mg L , for the quantification of Al-OH groups. The value of the ratio 1/n is equal to 3.475, which indicates heterogeneity of the superficial sites and weaker interaction between the adsorbent and adsorbate compared to the adsorbate–adsorbate interaction (Table III). It is important to note that the adjusted determination coefficient shows a value of 0.995, indicating good fit with the data on adsorption of MG on aluminized silica using the Freundlich model. In the same experimental conditions, the bare silica and the aluminized silica showed marked differences in the mechanism of adsorption of MG. The Langmuir and Freundlich models are based on the hypothesis of physical adsorption and therefore present a poor description of the system under study, which should be based models that may consider greater complexity as chemical reactions involved in adsorption processes. To better evaluate the adsorption differences between the two adsorbents, a model with three parameters was applied: Sips model. The results show a good fit with experimental data and are presented in Table III. Table III. Comparison of the parameters of isotherm models of adsorption of malachite green on bare silica and aluminized silica Langmuir Parameters
Bare Silica
Aluminized Silica
g-1)
73.644
106.520
0.275
0.094
0.800
0.617
Qmax (meq KL (L
meq-1)
R2adjusted
Freundlich Parameters
Bare Silica
Aluminized Silica
324.653
1.154
1/nF
1.351
3.475
R2adjusted
0.862
0.995
KF
(meq1-(1/n)
(g-1)
L1/n)
Sips Parameters
Bare Silica
Aluminized Silica
g-1)
0.012
0.469
3.711
3.519
Qmax (meq ns Ks (L
meq-1)-n
R2adjusted
1.488 ×
1013
0.987
3.465 0.994
The Sips isotherm is an empirical equation that presents a combination of Langmuir and Freundlich isotherms. The equation was developed by considering the equilibrium involved in the adsorption process. High Ks values indicate a very favorable adsorption process, in contrast to low Ks values. The best results observed for fit of experimental curves for bare silica and aluminized silica were obtained using the Sips model (Table III). The Ks value for bare silica, 1.488 × 1013, indicates that the MG adsorption process on bare silica was extremely favorable, in contrast to the value 3.465 found for aluminized silica. For the aluminized silica, when applying the Sips model, which is a combination of Langmuir and Freundlich isotherms, an extremely high value is observed for the maximum adsorption capacity. This value is a result 56
Quantification of Hydroxyl Groups from Alumina in Aluminosilicate Materials by Adsorption Isotherms
Technical Note
of the tendency of Sips model to follow the Freundlich model, so this value indicates the theoretical condition of infinite adsorption and should not be compared to the real value of maximum adsorption capacity on the silica. The results show significant differences in the adsorption process due to the incorporation of alumina nanoparticles on silica surface. To quantify the experimental modification, the adsorption of MG was evaluated at low concentrations, in which the adsorption of MG is linear, using the initial concentration of the solutions to evaluate the amount adsorbed. Quantification of Al–OH sites on aluminized silica To understand the adsorption behavior of MG on the aluminized silica surface, an adsorption isotherm was constructed. To verify the effect of MG adsorption on aluminized silica, the MG adsorption on bare silica, which does not possess Al–OH sites on its surface, was compared with it. The adsorption isotherms of malachite green on both chromatographic supports are shown in Figure 5. It can be observed that the adsorption of MG presented a distinct behavior on bare silica compared to that on aluminized silica support. The adsorption of MG on bare silica resulted in a graph with concave curvature, Figure 5(a). This condition implies a favorable adsorption of relatively high amounts of MG, even at low concentration levels. This isotherm is considered L-type because it has an initial curvature facing down due to the decrease in the availability of active sites on the adsorbent [30]. For the adsorption of MG on aluminized silica the graph resulted in a convex curvature, Figure 5(b), which implies unfavorable MG adsorption on aluminized silica, due to its low capacity for removal of MG from solution at low concentrations. Convex adsorption curves are considered S-type isotherms, in which adsorbate–adsorbent interactions are weaker than adsorbate–adsorbate or adsorbent–solvent interactions [30]. This difference between the behavior of MG adsorption on bare silica and on aluminized silica can be therefore associated with the presence of Al–OH sites on the latter adsorbent. It was observed that for the adsorption study using intermediate MG concentrations, conditions in which the number of active sites of the supports is not much higher than that of MG molecules, and that the number of MG molecules is not significantly higher than that of sites, there is a linear behavior between the amount of MG adsorbed on the supports and the initial MG concentration in solution. Figure 6 shows the adsorption curves obtained for MG on bare silica and aluminized silica at these MG concentrations. 0 .0 1 0 0
1 -1 qeqe (meq- g )
0 .0 0 7 5 )
0 .0 0 5 0
0 .0 0 2 5
0 .0 0 0 0
B a re silica A lu m in ize d silica 0 .0 0 2 5
0 .0 0 5 0 0 VM
CC VM (meq L ) 0
(
m
e
-1
q
0 .0 0 7 5
0 .0 1 0 0
-1 L
)
Figure 6. Adsorption curves of MG on bare silica and aluminized silica in a narrow range of MG concentration in solution. In detail, the difference in amount of MG adsorbed on the two supports under the same experimental conditions.
According to Figure 6, the amounts of MG adsorbed on bare silica and on aluminized silica at intermediate MG concentrations in solution exhibit linear behavior. Furthermore, the difference between the amount of MG adsorbed on bare silica and the amount adsorbed on aluminized silica remains constant 57
dos Santos, A. L. R.; de Assunção, R. M. N; de Faria, A. M.
Technical Note
within the range of concentrations evaluated. This difference may be related, by approximation, to inactivation of silica adsorption sites occupied by Al–OH groups. The lower amount of MG adsorbed on aluminized silica may be related to the electrostatic repulsion suffered by the (positively charged) MG molecules by the (positively charged) Al–OH groups. Therefore, the difference of adsorbed MG on these two materials can be correlated to the number of active Al–OH groups on the aluminized silica surface. According to the data extracted from the curves in Figure 6, the mean difference between the amount of -1 MG adsorbed on bare silica and on aluminized silica was 0.122 ± 0.003 mg g for the different initial concentrations of MG in solution. Considering a molar mass of MG of 329.458 g mol-1, the mean number -1 of moles of MG that adsorbed further on bare silica was 0.371 ± 0.003 μmol g . Considering also that the ratio between MG and Al–OH is 1.25:1 (considering that at pH 5 25% of MG species are doubly charged cations) in the electrostatic repulsion between the adsorbate and adsorbent, and that the specific surface 2 -1 area of aluminized silica is 204 m g , the concentration of Al–OH on the aluminized silica surface was 2.28 ± 0.02 nmol m-2. The obtained value is significantly low, which implies that aluminized silica has a low activity of Al–OH sites on its surface and pores, with alumina being predominantly incorporated in the form of Al2O3 particles. These values refer to nine experiments carried out independently, which are, therefore, authentic replicates with a low dispersion of values around the mean. The low dispersion can be attributed to the repeatability of the method to quantify the content of active alumina sites on an aluminized silica surface, which makes the method an interesting alternative to the more sophisticated instrumental techniques to perform this type of measurement. It is also important to emphasize that knowledge of the content of Al–OH sites on the surface of a chromatographic support is an important factor for the preparation of stationary phases for high performance liquid chromatography. The presence of very high numbers of Al–OH sites may lead to greater difficulty in modification of the support with organic groups to produce reversed stationary phases and/or the presence of amphoteric residual sites, which may interact undesirably with basic and acidic solutes. CONCLUSIONS A new method was successfully employed to determine the content of Al–OH groups in a solid aluminosilicate material from the differential adsorption of malachite green, and analysis of the adsorbate solution by molecular absorption spectroscopy. The method, besides being simple and easy to perform, does not require sophisticated instrumentation or expensive and specific reagents to perform a selective determination of hydroxyl groups in aluminized silica materials. The method presented excellent repeatability, showing itself as an alternative to the conventional, expensive and difficult-to-access methods. The proposed method is suitable for aluminosilicate-based materials and the experimental conditions must be strictly controlled so that the adsorbate adsorbs differentially with the groups to be determined. The aluminized silica support studied had an Al–OH active group content suitable for chromatographic purposes, according to the method. The low number of Al–OH groups obtained does not significantly affect the subsequent modification with organic clusters to produce reversed phases and does not imply the presence of residual groups after this modification, which could hinder the chromatographic separation of acidic or basic compounds. Manuscript received March 19, 2018; revised manuscript received May 26, 2018; accepted June 25, 2018; published online October 3, 2018.
58
Quantification of Hydroxyl Groups from Alumina in Aluminosilicate Materials by Adsorption Isotherms
Technical Note
REFERENCES 1. Stella, C.; Rudaz, S.; Veuthey, J. L.; Tchapla, A. Chromatographia, 2001, 53, pp S113-S131. 2. Qiu, H.; Liang, X.; Sun, M., Jiang, S. Anal. Bioanal. Chem., 2011, 399, pp 3307-3322. 3. Nawrocki, J.; Dunlap, C.; Li, J.; Zhao, J.; McNeff, C. V.; McCormick, A.; Carr, P. W. J. Chromatogr. A, 2004, 1028, pp 31-62. 4. Claessens, H. A.; van Straten, M. A. J. Chromatogr. A, 2004, 1060, pp 23-41. 5. Silva, C. R.; Airoldi, C.; Collins, K. E.; Collins, C. H. J. Chromatogr. A, 2008, 1191, pp 90-98. 6. Collins, C. H.; Silva, C. R.; Faria, A. M.; Collins, K. E.; Jardim, I. C. S. F. J. Braz. Chem. Soc., 2009, 20, pp 604-612. 7. Silva, C. G. A.; Collins, C. H.; Lesellier, E.; West, C. J. Chromatogr. A, 2013, 1315, pp 176-187. 8. Ge, J.; Zhao, L.; Chen, L. R.; Shi, Y. P. J. Chromatogr. Sci., 2010, 48, pp 29-34. 9. Amparo, M. R.; Marques, F. A.; Faria, A. M. J. Braz. Chem. Soc., 2013, 24, pp 1512-1519. 10. Goraieb, K.; Bueno, M. I. M. S.; Collins, C. H.; Collins, K. E. Quím. Nova, 2013, 36, pp 1131-1138. 11. Silveira, J. L.; Dib, S. R.; Faria, A. M. Anal. Sci., 2014, 30, pp 285-291. 12. Song, Z.; Wu, D.; Ding, K.; Guan, Y. J. Chromatogr. A, 2016, 1433, pp 85-89. 13. Faramawy, S.; El-Naggar, A. Y.; El-Fadly, A. M.; El-Sabagh, S. M.; Ibrahim, A. A. Arab. J. Chem., 2016, 9, pp S765-S775. 14. Borges, E. M.; Collins, C. H. J. Chromatogr. A, 2011, 1218, pp 4378-4388. 15. Silva, C. G. A.; Collins, C. H. J. Chromatogr. A, 2012, 1232, pp 248-256. 16. Faria, A. M.; Collins, K. E.; Collins, C. H. Chromatographia, 2008, 67, pp 357-363. 17. Nawrocki, J.; Dunlap, C.; McCormick, A.; Carr, P. W. J. Chromatogr. A, 2004, 1028, pp 1-30. 18. Zhao, Q.; Chen, W. H.; Huang, S. J.; Wu, Y. C.; Lee, H. K.; Liu, S. B. J. Phys. Chem. B, 2008, 106, pp 4462-4469. 19. Fry, R. A.; Tsomaia, N.; Pantano, C. G.; Mueller, K. T. J. Am. Chem. Soc., 2003, 125, pp 2378-2379. 20. Hensen, E. J. M.; Poduval, D. G.; Ligthart, D. A. J. M.; van Veen, J. A. R.; Rigutto, M. S. J. Phys. Chem. C, 2010, 114, pp 8363-8374. 21. Malfait W. J.; Xue, X. Geochim. Cosmochim. Acta, 2010, 74, pp 719-737. 22. Gallas, J. P.; Goupil, J. M.; Vimont, A.; Lavalley, J. C.; Gil, B.; Gilson, J. P.; Miserque, O. Langmuir, 2009, 25, pp 5825-5834. 23. Gulicovski, J. J.; Cerovic, L. S.; Milonjic, S. K. Mat. Manuf. Process., 2008, 23, pp 615-619. 24. Kokunesoski, M.; Gulicovski, J.; Matovic, B.; Logar, M.; Milonjic, S. K.; Babic, B. Mat. Chem. Phys., 2010, 124, pp 1248-1252. 25. Hameed, B. H.; El-Khaiary, M. I. J. Hazard. Mat., 2008, 153, pp 701-708. 26. https://chemicalize.com/ [Accessed 12 December 2017] 27. Ho, Y. S.; McKay, G. Process. Biochem., 1999, 34, pp 451-465. 28. Belhachemi, M.; Addoun, F. Appl. Water Sci., 2011, 1, pp 111-117. 29. Foo, K. Y.; Hameed, B. H. Chem. Eng. J., 2010, 156, pp 2-10.
30. Dias Filho, N. L.; Carmo, D. R. Adsorption at Silica, Alumina and Related Surfaces. In: Hubbard, A.
T. (Ed.). Encyclopedia of Surface and Colloid Science . Marcel Dekker, New York, N. J., 2004, pp 120. 59
Br. J. Anal. Chem., 2018, 5 (20), pp 60-67
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Comprehensive Analysis of Nanoparticles using Single and Triple Quadrupole ICP-MS and a Dedicated Data Evaluation Tool Daniel Kutscher1, Shona McSheehy Ducos1, Julian D. Wills1, Bruno Menezes Siqueira 2 1
2
Thermo Fisher Scientific, Bremen, Germany Nova Analítica Importação e Exportação, São Paulo, SP, Brazil
The goal of this work is to demonstrate the possibility of directly determining the size distribution and particle number concentration of different nanoparticles using ICP-MS operated in the so-called single particle mode. Different nanoparticles (e.g. made from gold or titanium dioxide) were analyzed using either single quadrupole ICP-MS or triple quadrupole ICP-MS. All parameters relevant for the measurement were determined automatically using a dedicated software module, the npQuant plug-in for the Thermo
ScientificTM QtegraTM Intelligent Scientific Data Solution software. To show the validity of the results, a dataset acquired using the npQuant plug-in was exported and evaluated in an independent, publically available software solution. Excellent agreement with certified values was achieved. A comparison of the results obtained by the npQuant plug-in to a widely accepted spreadsheet solution also showed identical results. For TiO2 particles, low detection limits (in terms of lowest detectable particle size) were achieved using triple quadrupole based ICP-MS. Keywords: Nanoparticles, ICP-MS, Triple Quadrupole. INTRODUCTION Due to their unique properties, nanomaterials have found their way into many everyday consumer products. In some cases, the use of nanomaterials is openly declared for marketing purposes. In other cases, however, the use of nanomaterials is not obvious from the product labeling. Despite their growing prevalence, the potential adverse effects of nanomaterials on human health and the environment is still not fully understood. Common approaches used to characterize nanomaterials include microscopy based techniques e.g. transmission electron microscopy (TEM), and optical properties methods e.g. dynamic light scattering (DLS). Fractionation or separation of different particle sizes within one sample prior to detection can be accomplished using asymmetric flow field flow fractionation (AF4) for example, or alternative chromatographic techniques such as hydrodynamic chromatography (HDC). Whereas techniques based on microscopy only allow the sampling of a small amount of particles, optical techniques may be limited in detection sensitivity with samples derived from environmental sources. Furthermore, not all techniques are able to directly deliver a number based size distribution, which is mandatory to meet the current definition of a nanomaterial. Single particle ICP-MS (spICP-MS) has found its niche in the portfolio of techniques available to characterize nanoparticles, both in terms of their size distribution, as well as the number of particles with a given size present in a sample. Indeed, a low number of particles is a prerequisite for spICP-MS. The direct sizing and counting of nanoparticles using single particle ICP-MS (spICP-MS) is an alternative to established techniques for particle characterization. However, for some materials such as silica or TiO2, spectral interferences are still a limiting factor. In addition, the differences in data evaluation may slow the implementation of spICP-MS as a tool in routine analysis. In order to enable comprehensive analysis of nanoparticles this report will show a completely integrated workflow solution based on the Qtegra Intelligent Scientific Data Solution software. The software plug-in allows also unexperienced users to set up methods through automatic determination of key input parameters and statistical evaluation of the data in order to recognize artifacts. 60
Br. J. Anal. Chem., 2018, 5 (20), pp 68-70
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Investigate batteries with a SEM for better performance Insights on what can be revealed on batteries structure and composition with a Scanning Electron Microscope The battery production cycle is a long process that involves several stages. Intermediate checks are necessary to verify the quality of the production system, starting from the inspection of raw materials, to the production of intermediate components, as well as checks on the final product, requiring the system used for the investigations to be highly versatile. The secret to improving the specifications of new generation batteries is miniaturization. SEM is an unrivaled technique for inspecting and analyzing nanoscale materials, improving production processes or detecting the reasons for failure. The insulating materials in batteries are, by definition, non-conductive. When imaging with a SEM, this causes an accumulation of electrons on the surface of such samples, compromising the quality of the final picture and often hiding important details. In order to flawlessly Figure structures of interest, different solutions are available. Reducing the vacuum level in the imaging chamber can help to discharge the sample, immediately improving Figure quality. The value of the current that is applied can also be altered to reduce the interactions and, when dealing with very delicate samples, prevent surface damage. If both of the previously-mentioned techniques fail, a thin layer of gold can be applied on the surface, making it conductive and ready for high resolution imaging. The advantages of electron microscopy: • Access to nanoscale magnification; • Integrated, non-destructive EDS analysis to measure chemical composition of the sample locally; • Automated routines to gather data on pores, particles and fibers - quickly and without wasting the operator's time; • 3D reconstruction of the surface to measure morphology. With an electron microscope, you can observe: • Size and granulometry of powders used as raw materials; • Size and orientation of pores and fibers in insulating membranes; • Three-dimensional structure of electrodes after production processes; • Response of materials to electrical or thermal solicitations; • Presence of contaminants in the battery sublayers.
Figure 1.SEM images of battery insulating membranes. Highly non-conductive samples require special treatment for imaging. Operating at a different vacuum level can reduce charging effects. Coating the sample with a thin gold layer will dramatically reduce the issue. 68
Br. J. Anal. Chem., 2018, 5 (20), pp 71-73
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Detection and quantification of multi-elements in nanoparticles with the icpTOF Olga Borovinskaya1, Martin Tanner1, Steffi Boehme2 1
TOFWERK, Switzerland; 2RIKILT, The Netherlands
An increasing number of multi-element nanoparticles (alloy, core-shell structures) are being manufactured nowadays. Multielement particle detection is necessary to trace manufactured nanoparticles in the high background of natural particles. Single particle inductively coupled plasma mass spectrometry (sp-ICPMS) has established itself as a robust and sensitive method for the measurement of nanoparticle size and number concentration at environmentally relevant levels. A single particle transmitted into an ICP-mass spectrometer generates a ~1 ms pulse of ion signal. Most ICP- mass spectrometers use sequential mass analyzers that can measure only one or two isotopes during this rapid single-particle detection event. This is insufficient for the detection of complex multi-element particles, which represent a substantial portion of manufactured nanomaterials used as additives in consumer products or which are formed by chemical modifications of pristine single-element particles after they have entered the natural environment. The icpTOF provides simultaneous detection of all isotopes and records a unique mass spectrum every 30 μs, making it an ideal tool for multielement detection and quantitation of nanoparticles in unknown or poorly characterized samples. Moreover, it uniquely combines high mass resolution with collision- and reaction-cell technology (Q-cell), enabling more efficient resolution of analytes from interferences (e.g. 56Fe). In this report, the ability of the icpTOF to record all elements in single particles is demonstrated, and multi-element icpTOF data are compared to what can be recorded with modern sequential mass analyzers. The elemental composition of single steel nanoparticles in a polydisperse population is quantified based on a simple multi-element solution calibration. Experimental Nanosteel nanoparticles composed of Fe, Cr, Ni, Mo were diluted with milliQ water and measured with the icpTOF using H2 in the Q-cell at 3 ml/min to remove ArO interference on 56Fe. The TOFWERK icpTOF, which simultaneously measures all isotopes, enabling determination of the complete chemical composition of single nanoparticles, was used. Figure 1 shows the transient signal of a single steel particle detected with 90 μs temporal resolution. Three single TOF extractions were averaged. The total counts detected per particle are given. Transient signal of the same particle recorded with sequentially measuring quadrupole or sector-field were simulated from the TOF signal using 90 μs dwelling time on each isotope, with no analyzer settling time. Sensitivity is decreased by up to 33-fold due to sequential detection of the four isotopes. Element mass ratios deviate from ratios determined with TOF by 76 - 270%.
71
Br. J. Anal. Chem., 2018, 5 (20), pp 84-84
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Some recent contributions from SelecScience® to the scientific community lndustry News: Scientists Achieve Single Molecule Control for a Millionth of a Billionth of a Second New technology, termed scanning tunneling microscope, pushes the limits of nanoscience. Physicists at the University of Bath have discovered how to manipulate and contrai individual molecules for a millionth of a billionth of a second, after being intrigued by some seemingly odd results. Their new technique is the most sensitive way of controlling a chemical reaction on some of the smallest scales scientists can work - at the single molecule levei. lt will open up research possibilities across the fields of nanoscience and nanophysics. Read the full text: www.selectscience.net/industry-news/
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The future is closer than you think For two decades, SelectScience has been publishing news and content from the front line of scientific advancement, improving communication between leading scientists and the biggest and best manufacturers across the globe, as we work towards one common goal - making the future healthier. ln 2040 - where will we be - a disease-free humanity, producing super-foods, or even super-humans? We welcome you to explore what the future of science could like, meet the people making that happen, and discover how they intend to do it. Access "The Future of Science - How science could change your life by 2040" future.selectscience.net
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