Abstract
Knowledge of the reaction rate constants can be vital in understanding electrochemical reaction mechanisms and their rate-determining processes. Although first-principles methods, such as density functional theory (DFT), provide valuable insight into reaction free energies and rate constants, they commonly use idealized assumptions. As a different approach, this study demonstrates the estimation of rate constants from electrochemical data. Specifically, this study estimates rate constants from electrochemical impedance spectroscopy (EIS) data of the oxygen evolution reaction (OER) with a hematite Fe(2)O(3) anode often used in photoelectrochemical cells. Unlike the common approach of equivalent circuit fitting with resistances and capacitances, the electrochemistry of the OER in this work is represented by a microkinetic model and physicochemical quantities. The estimated rate constants directly correspond to the OER reaction steps, and a single set of rate constants is obtained that is optimized for multiple potentials simultaneously. The estimation is conducted using maximum likelihood estimation. The effectiveness of the estimation method is shown using synthetic measurements first; intermediate species coverages are simulated as well. Then, the rate constants are estimated directly from experimental EIS measurements. Though accuracy is currently limited due to the model that does not account for all processes at the interface, such as, for example, diffusive transport, the estimated rate constants do represent the experimental interface and are perfectly suited for kinetic analysis and systematic parameter studies of the electrochemical system. Additionally, this approach enables analyses of differences between electrode materials, validation of models, and prediction of electrochemical data of different material systems, which is time-consuming and costly to obtain experimentally. This research demonstrates how combining potential- and frequency-dependent EIS experiments with microkinetic modeling enables the estimation of reaction rates and intermediate species coverages, aiding in identifying reaction mechanisms directly from experiments.