Open AccessElectrochemiluminescence Mechanisms Investigated with Smartphone‐Based Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis
Author(s) -
Rivera Elmer Ccopa,
Summerscales Rodney L.,
Tadi Uppala Padma P.,
Kwon Hyun J.
Publication year - 2020
Publication title -
chemistryopen
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.644
H-Index - 29
ISSN - 2191-1363
DOI - 10.1002/open.202000165
Subject(s) - sensitivity (control systems) , electrochemiluminescence , computer science , estimation theory , convergence (economics) , calibration , biological system , data mining , algorithm , chemistry , electronic engineering , mathematics , statistics , engineering , electrode , biology , economic growth , economics
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) 3 2+ /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.