Application of artificial neural network to simultaneous potentiometric determination of silver(I), mercury(II) and copper(II) ions by an unmodified carbon paste electrode |
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Authors: | Shamsipur Mojtaba Tashkhourian Javad Hemmateenejad Bahram Sharghi Hashem |
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Institution: | a Department of Chemistry, Razi University, Kermanshah, Iran b Department of Chemistry, Shiraz University, Shiraz, Iran c Medicinal & Natural Product Chemistry Research Center, Shiraz University of Medical Science, Shiraz, Iran |
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Abstract: | The response characteristics and selectivity coefficients of an unmodified carbon paste electrode (CPEs) towards Ag+, Cu2+ and Hg2+ were evaluated. The electrode was used as an indicator electrode for the simultaneous determination of the three metal ions in their mixtures via potentiometric titration with a standard thiocyanate solution. A three-layered feed-forward artificial neural network (ANN) trained by back-propagation learning algorithm was used to model the complex non-linear relationship between the concentration of silver, copper and mercury in their different mixtures and the potential of solution at different volumes of the added titrant. The network architecture and parameters were optimized to give low prediction errors. The optimized networks were able to precisely predict the concentrations of the three cations in synthetic mixtures. |
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Keywords: | Multicomponent analysis Ag+ Cu2+ and Hg2+ Potentiometric titration Carbon paste electrode Artificial neural network |
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