Neural modeling of laviron treatment for coating of electrodes with mediator

Abstract

In this paper, an original solution for modeling and simulation of the nonlinear electrochemical process associated to the Laviron treatment is proposed. The graphite electrodes were coated with mediator by adsorption. The Laviron treatment was firstly used to determine the efficiency of modified electrodes coatings. The experimental data were obtained using an electrochemical experiment. The mathematical model of the process is expressed using a neural network with complex structure, an aspect which represents a novel approach in this domain. The main advantages of the proposed model are: its accuracy in relation to the experimental data and the fact that its usage permits the numerical simulation of the process, with multiple future applications. Based on the proposed neural model, an original procedure to determine the parameters of the nonlinear Laviron equation is presented. Another interesting element is represented by proving the fact that the value of heterogeneous electron-transfer rate constant kS is a function depending in the potential scan rate. This aspect is possible due to the original proposed approach of the Laviron treatment as a nonlinear process, on the entire range of input signals, in contrast with the big majority of the studies from the literature which are based on the linearization of this process near particular steady state working points.