Wavelet based spectral approach for solving surface coverage model in an electrochemical arsenic sensor - An operational matrix approach

Abstract

Surface coverage parameter of an electrochemical sensor plays a vital role in enhancing the figure of merits of the sensor. Developing a theoretical model for the surface coverage will help to standardize the fabrication of working electrodes used in electrochemical sensors. In this background, a wavelet based spectral algorithm has been developed to model the surface coverage of an arsenic sensor. For the model, Michaelis-Menten constant of fluorine doped cadmium oxide (F-doped CdO) working electrode based arsenic sensor was used as the seed fount. Theoretical analysis for the estimation of surface coverage based on Michaelis-Menten constant with nonlinear reaction-diffusion equation is considered. In order to estimate the Michaelis-Menten constant and maximum current response, the measured current values are linearized with the help of Hanes-woolf plot. Using the Legendre wavelet spectral approach, the nonlinear reaction-diffusion equation is converted into a system of algebraic equations through operational matrix of derivatives. The surface coverage was determined using Legendre wavelets and this method can be determined the desired surface coverage for detecting arsenic in water of specific range.