Authors: Xinwei Zhu | Jun Huang | Michael Eikerling
Source: ChemRxiv (preprint, 2024-04-22)
Field: Materials Science — Materials Chemistry

How to Decipher Electrocatalytic Reactions withTheory and Computation Electrocatalytic reactions, such as oxygen reduction/evolution reaction and CO2 reduction reaction that are pivotal for the energy transition, are multi-step processes occurring in a nanoscale electric double layer (EDL) at solid-liquid interfaces. Conventional analyses based on the Sabatier principle, using binding energies or effective electronic structure properties of the d-band center as descriptors, are able to grasp overall trends in catalytic activity in groups of catalysts. However, thermodynamic approaches fail to account for a plethora of electrolyte effects that arise in the EDL, including pH effects, cation effects, and anion effects. These effects have been observed to strongly influence electrocatalytic reactions. There is a growing consensus that the local reaction environment (LRE) prevailing in the EDL is the key to deciphering these complex and hitherto perplexing electrolyte effects. Equal attention is thus paid to designing appropriate electrolytes, positioning the LRE at center stage. Achieving this is essential for designing electrocatalysts with specifically tailored properties, which could enable much needed breakthroughs in electrochemical energy science. Theory and modeling are becoming increasingly important and powerful in addressing this multifaceted problem that involves physical phenomena at different scales interacting in a multidimensional parametric space. Theoretical models developed for this purpose should treat intrinsic multistep kinetics of electrocatalytic reactions, EDL effects from sub-nm scale to the scale of 10 nm, and mass transport phenomena bridging scales from < 0.1 to 100 μm. Given the diverse physical phenomena and scales involved, it is evident that the challenge at hand surpasses the capabilities of any single theoretical or computational approach. In this Account, we present a hierarchical theoretical framework to address the above challenge. It seamlessly integrates several modules: (i) a comprehensive microkinetic model accounting for various reaction pathways; (ii) an LRE model that describes the interfacial region extending from the nanometric EDL continuously to the solution bulk; (iii) first-principles calculations that provide parameters, e.g., adsorption energies, activation barriers and EDL parameters. The microkinetic model considers all elementary steps without designating an a priori rate-determining step. The kinetics of these elementary steps are expressed in terms of local concentrations, potential and electric field that are co-determined by EDL charging and mass transport in the LRE model. New insights on electrode kinetic phenomena, i.e., potential-dependent Tafel slopes, cation effects, and pH effects, obtained from this hierarchical framework are then reviewed. Finally, an outlook on further improvement of the model framework is presented, in view of recent developments in first-principles based simulation of electrocatalysis, observations of dynamic reconstruction of catalysts, and machine-learning assisted computational simulations DECIPHER ; Computation ; Computer science ; Computational biology ; Bioinformatics ; Biology ; Algorithm Machine Learning in Materials Science