Artificial Intelligence as a Tool for Fitting Voltammograms and Extracting Kinetic Parameters in Square-Wave Voltammetry

Mathcad-simulated libraries in Excel of simulated theoretical voltammograms, together with excel files of experimental voltammograms, can serve as a basis to recognize the most likely mechanism (CE, EC, EC′, ECE, etc.) and to fit the key parameters (e.g., ks, α, Kchem, Keq, D) with rather good precision by using following algorithm in Artificial Intelligence. One should provide Excel data from simulated voltammograms of particular mechanism and should give all parameters used for given set of simulation parameters. Afterwards, by using identical conditions as in the simulations (in respect to SW amplitude, frequency, time sampling window, potential step, starting potential, final potential, temperature etc.) one should put the excel file in the AI algorithm. Very good precision might be obtained in respect of evaluating kinetic and thermodynamic data, if the data are consistently obtained and explained. Entire approach is detailed step-by-step in this work.