Journal
TALANTA
Volume 64, Issue 3, Pages 590-596Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2004.03.034
Keywords
multicomponent analysis; Ag+, Cu2+ and Hg2+; potentiometric titration; carbon paste electrode; artificial neural network
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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. (C) 2004 Elsevier B.V. All rights reserved.
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