Modelling Complex Chemical Processes in Homogeneous Solutions: Automatic Numerical Simulation

Two algorithms for the determination of the necessary limit of local error for the numerical solution of ordinary differential equation (ODE) systems describing homogeneous chemical and biochemical processes, and for the evaluation of their stiffness are developed. The approach for finding the necessary limit of local error of a numerical ODE solver is justified by the proof of the corresponding theorems. The application of the new algorithms implemented in version 2.1 of KinFitSim software to the simulation of real chemical systems is considered on the example of Belousov-Zhabotinsky reaction

Electrochemiluminescence Mechanisms Investigated with Smartphone-Based Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis

The present study introduces a unified framework combining a mechanistic model with a genetic algorithm (GA) for the parameter estimation of electrochemiluminescence (ECL) kinetics of the Ru(bpy)32+/TPrA system occurring in a smartphone‐based sensor. The framework allows a straightforward solution for simultaneous estimation of multiple parameters which can be, otherwise, time‐consuming and lead to non‐convergence. Model parameters are estimated by achieving a high correlation between the model prediction and the measured ECL intensity from the ECL sensor. The developed model is used to perform a sensitivity analysis (SA), which provides quantitative effects of the model parameters on the concentrations of chemical species involved in the system. The results demonstrate that the GA‐based parameter estimation and the SA approaches are effective in analyzing the kinetics of the ECL mechanism. Therefore, these approaches can be incorporated as analysis tools in the ECL kinetics study with practical application in the calibration of mechanistic models for any required sensing condition