Over the past few decades, the field of electrochemistry has witnessed rapid advances in computational methods. This review highlights recent methodological progress in computational electrocatalysis, with a specific focus on the accurate prediction of electrochemical reaction kinetics. Particular emphasis is placed on our group's contributions using single-atom catalysts as model systems to quantitatively simulate the kinetics of energy-relevant small-molecule electrocatalytic reactions. By simultaneously capturing atomic-scale interfacial phenomena in the electric double layer, such as cation effects, explicit solvation structures, proton transfer dynamics, and potential distribution, our approach bridges the gap between idealized models and realistic electrochemical environments and predicts experimental observables, such as current density-potential curves and coverages. The current framework has also revealed previously inaccessible kinetic insights, including hydrogen-bond-mediated intermediate reorganization and its impact on transition states, and potential-driven solvent reorganization that dictates proton transfer kinetics. These advances provide both fundamental kinetic insights into electrocatalytic mechanisms and practical design principles for energy conversion catalysts.
Qian et al. (Fri,) studied this question.