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Abdollah Salimi

Abdollah Salimi

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId: 57198900488
Faculty: Faculty of Science
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Research

Title
Genetic Algorithm Strategy for Potential Selection in Simultaneous Voltammetric Determination of Nitro-aromatic Compounds Using Partial Least Squares Regression and Artificial Neural Networks on Modified Glassy Carbon Electrode with Carbon Nanotube
Type
Presentation
Keywords
Genetic Algorithm -Nitro-aromatic Compounds -Carbon Nanotube
Year
2007
Researchers Amir najafi ، Abdollah Salimi ، Raouf Ghavami

Abstract

A voltammetric method for the quantitative determination of nitrobenzene and mononitro-phenol isomers, such as, o-, m- and p-nitro-phenol in mixtures has been developed by recording differential puls voltamograms between -100 and -850 mV with a bare and glassy carbon electrode modified with multilwall carbon nanotube (GCE & MWCNT-GCE) in Britton-Robinson buffer of pH = 2.25. The chemical and instrumental variables affecting the analytical performance of the methodology were studied. It was found by applying the differential pulse voltammetric that nitrobenzene and three nitro-phenol compounds had well formed reduction voltammetric waves with the peak potentials at -0.499, -0.468, -0.507, -0.591 on GCE and -0.345, -0.309, -0.321, -0.393V on MWCNT-GCE, respectively. For each compounds a linear calibration was obtained in the concentration range of 0.61-31.8 μg ml-1 for nitrobenzene, 0.14-20 for o-nitrophenol, 0.14-20.7 μg ml-1 for m-nitrophenol and 0.14-25.7 μg ml-1 for p-nitrophenol on bare and modified CNT-electrode. However, the voltamograms of these compounds are deeply overlapped and show nonlinear character which does not allow their direct determination without previous separation. The proposed method applies partial least squares regression (PLS) and artificial neural networks multivariate calibration to the resolution of this mixture using a set of potentials previously selected by genetic algorithms [1,2]. The linear calibration graphs used to construct the calibration matrix were selected in the ranges from 0.61 to 23.54 μg ml-1 for nitrobenzene, from 0.46 to 19.21 ng ml-1 for o-nitrophenol, from 0.46 to 13.77 μg ml-1 for m-nitrophenol, and from 0.46 to 15.14 μg ml-1 for p-nitrophenol. A cross-validation procedure was used to select the number of factors. The prediction ability of the proposed method was tested with the use of a data set constructed from synthetic solutions of the four compounds, and in general, satisfactory results were obtained.