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Abstract:

In this work, we present the combined effect of artificial neural networks (ANN) and experimental design as a suitable analytical tool for improving the performance of thermospray flame furnace atomic absorption spectrometry (TS-FFAAS) using Mg as leading case. To this end, mixtures of different amounts of methanol, ethanol, and i-propanol inwaterwere assayed as carriers at different flow rates and different flame stoichiometries (air/acetylene ratios). Different levels of these variables determined the experimental domain, consisting in a cube whichwas divided into eight identical cubical regions that allowed increase in the number of available experimental points. A Box-Behnken design (BBD) was employed in each one of the regions. The nameMultiple Box-Behnken design (MBBD)was given to this newapproach. Then, the features of ANN were exploited to find the optimum conditions for conducting Mg determination by TS-FFAAS. The prediction capability of ANN was examined and compared to the least-squares (LS) fitting when applied to the response surface method (RSM). The suitability of the new approach and the implications on TS-FFAAS analytical performance are discussed. © 2015 Elsevier B.V.

Registro:

Documento: Artículo
Título:A novel combination of experimental design and artificial neural networks as an analytical tool for improving performance in thermospray flame furnace atomic absorption spectrometry
Autor:Morzan, E.; Stripeikis, J.; Goicoechea, H.; Tudino, M.
Filiación:Laboratorio de Análisis de Trazas. INQUIMAE, Departamento de Química Inorgánica, Analítica y Química Física, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires, 1428, Argentina
Departamento de Ingeniería Química, Instituto Tecnológico de Buenos Aires, Av Eduardo Madero 399, Buenos Aires, C1106, Argentina
Laboratorio de Desarrollo Analítico y Quimiometría (LADAQ), Cátedra de Química Analítica I, Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral-CONICET, C.C. 242, S3000ZAA, Santa Fe, Argentina
Palabras clave:ANN; Experimental design; Thermospray flame furnace atomic absorption spectrometry; acetylene; alcohol; magnesium; methanol; propanol; water; analytic method; Article; artificial neural network; atomic absorption spectrometry; experimental design; flow rate; intermethod comparison; predictive value; priority journal; regression analysis; response surface method; stoichiometry; thermospray flame furnace atomic absorption spectrometry
Año:2016
Volumen:151
Página de inicio:44
Página de fin:50
DOI: http://dx.doi.org/10.1016/j.chemolab.2015.11.011
Título revista:Chemometrics and Intelligent Laboratory Systems
Título revista abreviado:Chemometr. Intelligent Lab. Syst.
ISSN:01697439
CODEN:CILSE
CAS:acetylene, 74-86-2; alcohol, 64-17-5; magnesium, 7439-95-4; methanol, 67-56-1; propanol, 62309-51-7, 71-23-8; water, 7732-18-5
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01697439_v151_n_p44_Morzan

Referencias:

  • Gáspár, A., Berndt, H., Thermospray flame furnace atomic absorption spectrometry (TS-FF-AAS)-a simple method for trace element determination with microsamples in the μg/l concentration range (2000) Spectrochim. Acta B, 55, pp. 587-597
  • Brancalion, M.L., Sabadini, E., Arruda, M.A.Z., Description of the thermospray formed at low flow rate in thermospray flame furnace atomic absorption spectrometry based on high-speed images (2007) Anal. Chem., 79, pp. 6527-6533
  • Arruda, M.A.Z., Figueredo, E.C., Atomic spectrometry based on metallic tube atomizers heated by flame: innovative strategies from fundamentals to analysis (2009) Spectrochim. Acta B, 64, pp. 477-481
  • Miranda, K., Pereira-Filho, E.R., Potentialities of thermospray flame furnace atomic absorption spectrometry (TS-FF-AAS) in the fast sequential determination of Cd, Cu, Pb and Zn (2009) Anal. Methods, 1, pp. 215-219
  • Morzan, E., Piano, O., Stripeikis, J., Tudino, M., Evaluation of quartz tubes as atomization cells for gold determination by thermospray flame furnace atomic absorption spectrometry (2012) Spectrochim. Acta B, 77, pp. 58-62
  • Morzan, E., Stripeikis, J., Tudino, M., Towards broadening thermospray flame furnace atomic absorption spectrometry: influence of organic solvents on the analytical signal of magnesium (2015) Anal. Chem. Res., 4, pp. 1-7
  • Vera-Candioti, L., Cámara, M., Dezan, M., Goicoechea, H., Experimental design and multiple response optimization. Using the desirability function in analytical methods development (2014) Talanta, 124, pp. 123-138
  • Myers, R.H., (2009) D. C. Montgomery in Response Surface Methodology, Process and Product Optimization using Designed Experiments, , Ed. Wiley & Sons, New York, 3nd ed
  • Dingstad, G., Egelandsdal, B., Naes, T., Modeling methods for crossed mixture experiments-a case study from sausage production (2003) Chemom. Intell. Lab., 66, pp. 175-190
  • Lee, K.M., Gilmore, D.F., Formulation and process modeling of biopolymer (polyhydroxyalkanoates: PHAs) production from industrial wastes by novel crossed experimental design (2005) Process Biochem., 40, pp. 229-246
  • Adinarayana, K., Ellaiah, P., Srinivasulu, B., Bhavani Devi, R., Adinarayana, G., Response surface methodological approach to optimize the nutritional parameters for neomycin production by Streptomyces marinensis under solid-state fermentation (2003) Process Biochem., 38, pp. 1565-1572
  • Prapulla, S.G., Jacob, Z., Chand, N., Rajalakshmi, D., Karanth, N.G., Maximization of lipid production by rhodotorula gracilis CFR-1 using response surface methodology (1992) Biotechnol. Bioeng., 40, pp. 965-970
  • Roberto, I.C., Sato, S., de Mancilha, I.M., Taqueda, M.E.S., Influence of media composition on xylitol fermentation by Candida guiliiermondii using response surface methodology (1995) Biotechnol. Lett., 17, pp. 1223-1228
  • Liu, Y.T., Long, C.N., Xuan, S.X., Lin, B.K., Long, M.N., Hu, Z., Evaluation of culture conditions for cellulase production by two Penicillium decumbens under liquid fermentation conditions (2008) J. Biotechnol., 1365, p. S328
  • Dingstad, G., Westad, F., Naes, T., Three case studies illustrating the properties of ordinary and partial least squares regression in different mixture models (2004) Chemom. Intell. Lab., 71, pp. 33-45
  • Piepel, G.F., Modeling methods for mixture-of-mixtures experiments applied to a tablet formulation problem (1999) Pharm. Dev. Technol., 4, pp. 593-606
  • Brandvik, P.J., Statistical simulation as an effective tool to evaluate and illustrate the advantage of experimental designs and response surface methods (1998) Chemom. Intell. Lab., 42, pp. 51-61
  • Ortega, N., Albillos, S.M., Busto, M.D., Application of factorial design and response surface methodology to the analysis of bovine caseins by capillary zone electrophoresis (2003) Food Control, 14, pp. 307-315
  • Severini, C., Baiano, A., De Pilli, T., Romaniello, R., Derossi, A., Lebensm, A., Prevention of enzymatic browning in sliced potatoes by blanching in boiling saline solutions (2003) Wiss. Technol., 36, pp. 657-665
  • Nardi, J.V., Acchar, W., Hotza, D., Enhancing the properties of ceramic products through mixture design and response surface analysis (2004) J. Eur. Ceram. Soc., (24), pp. 375-379
  • Abnisa, F., Wan Daud, W.M.A., Sahu, J.N., Optimization and characterization studies on bio-oil production from palm shell by pyrolysis using response surface methodology (2011) Biomass Bioenergy, 35, pp. 3604-3616
  • Giordano, P.C., Martínez, H.D., Iglesias, A.A., Beccaria, A.J., Goicoechea, H.C., Application of response surface methodology and artificial neural networks for optimization of recombinant Oriza sativa non-symbiotic hemoglobin 1 production by Escherichia coli in medium containing byproduct glycerol (2010) Bioresour. Technol., 101, pp. 7537-7544
  • Betiku, E., Okubsikawi, S.S., Ajala, S.O., Odelele, O.S., Performance evaluation of artificial neural network coupled with generic algorithm and response surface methodology in modeling and optimization of biodiesel production process parameters from shea tree (Vitellaria paradoxa) nut butter (2015) Renew. Energy, 78, pp. 408-417
  • Prakash Maran, J., Priya, B., Comparison of response surface methodology and artificial neural network approach towards efficient ultrasound-assisted biodiesel production from muskmelon oil (2015) Ultrason. Sonochem., 23, pp. 192-200
  • Sabonian, M., Behnajady, M.A., Artificial neural network modeling of Cr(VI) photocatalytic reduction with TiO2-P25 nanoparticles using the results obtained from response surface methodology optimization (2015) Desalin. Water Treat., , (article in press)
  • Silva, S.F., Anjos, C.A.R., Cavalcanti, R.N., Celeghini, R.M.D.S., Evaluation of extra virgin olive oil stability by artificial neural network (2015) Food Chem., 179, pp. 35-44
  • Desai, K.M., Survase, S.A., Saudagar, P.S., Lele, S.S., Singhal, R.S., Comparison of artificial neural network (ANN) and response surface methodology (RSM) in fermentation media optimization: case study of fermentative production of scleroglucan (2008) Biochem. Eng. J., 41, pp. 266-273

Citas:

---------- APA ----------
Morzan, E., Stripeikis, J., Goicoechea, H. & Tudino, M. (2016) . A novel combination of experimental design and artificial neural networks as an analytical tool for improving performance in thermospray flame furnace atomic absorption spectrometry. Chemometrics and Intelligent Laboratory Systems, 151, 44-50.
http://dx.doi.org/10.1016/j.chemolab.2015.11.011
---------- CHICAGO ----------
Morzan, E., Stripeikis, J., Goicoechea, H., Tudino, M. "A novel combination of experimental design and artificial neural networks as an analytical tool for improving performance in thermospray flame furnace atomic absorption spectrometry" . Chemometrics and Intelligent Laboratory Systems 151 (2016) : 44-50.
http://dx.doi.org/10.1016/j.chemolab.2015.11.011
---------- MLA ----------
Morzan, E., Stripeikis, J., Goicoechea, H., Tudino, M. "A novel combination of experimental design and artificial neural networks as an analytical tool for improving performance in thermospray flame furnace atomic absorption spectrometry" . Chemometrics and Intelligent Laboratory Systems, vol. 151, 2016, pp. 44-50.
http://dx.doi.org/10.1016/j.chemolab.2015.11.011
---------- VANCOUVER ----------
Morzan, E., Stripeikis, J., Goicoechea, H., Tudino, M. A novel combination of experimental design and artificial neural networks as an analytical tool for improving performance in thermospray flame furnace atomic absorption spectrometry. Chemometr. Intelligent Lab. Syst. 2016;151:44-50.
http://dx.doi.org/10.1016/j.chemolab.2015.11.011