Use of Artificial Intelligence in Electrode Reaction Mechanism Studies: Predicting Voltammograms and Analyzing the Dissociative CE Reaction at a Hemispherical Electrode
Haotian Chen, Enno Kätelhön, Haonan Le, Richard G. Compton
Abstract
Artificial intelligence (AI) is used to learn the key voltammetric characteristics of the dissociative CE mechanism via training from multiple simulations using bespoke code. This allows first for the prediction of voltammograms without the need for further simulations, given knowledge of the relevant experimental parameters (rate and equilibrium constants, electrode geometry, and diffusion coefficients). Second, it is applied to analyze noisy experimental voltammetry to characterize the mechanistic type and to successfully extract the key kinetic and thermodynamic parameters.
Topics & Concepts
ChemistryElectrodeReaction rate constantDissociativeReaction mechanismKinetic energyStandard electrode potentialDiffusionMechanism (biology)VoltammetryAnalytical Chemistry (journal)ElectrochemistryThermodynamicsPhysical chemistryKineticsChromatographyCatalysisOrganic chemistryMedicinePharmacologyEpistemologyPhilosophyQuantum mechanicsPhysicsElectrochemical Analysis and ApplicationsElectrocatalysts for Energy ConversionMachine Learning in Materials Science