Article ID Journal Published Year Pages File Type
189027 Electrochimica Acta 2012 7 Pages PDF
Abstract

A programmed switching system combined with an array of potentiometric sensors consisting of seven potentiometric sensors (i.e., ion-selective or cross-selective electrodes) was connected directly to a pH/potentiometer and a computer (PC) to sequentially acquire the potential corresponding to water sample mixtures. The acquired potentials were recorded and saved on the PC and were used as input variables for an artificial neural network to simultaneously yield the concentrations of Cd2+, Cu2+, and Ag+ in simple and complex mixtures. A feed-forward, back propagation network with a Levenburg–Maquart algorithm was employed to optimize the network parameters. Certain characteristics of each of the seven ion-selective electrodes, including selectivity coefficients, calibration curves, and response times, were also studied. A five-second delay time was used when recording the potentials of the electrodes using the switching system. The array system was also optimized for the selection of the ion-selective electrodes. A four-electrode array system was found to be the best choice for the prediction of Cd2+, Ag+ and Cu2+ ion concentration, but application of all seven ion-selective electrodes was necessary for prediction of these primary ions in samples containing a combination of zinc and nickel ions as interfering ions.

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Physical Sciences and Engineering Chemical Engineering Chemical Engineering (General)
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