Electrochemical interface modelling for electrocatalytic materials design

Abstract

The advancement of net-zero emissions technologies requires an in-depth understanding of electrochemical reactions at electrified interfaces. Essential processes such as green hydrogen production and CO2 reduction require sustainable electrocatalysts tailored for varied operational conditions. Computational techniques in electrocatalysis serve as crucial tools for providing microscopic insights and guiding towards higher-performing materials. Traditional modelling frameworks require approximations such as simplified surface models and an implicit description or neglect of electrolyte effects. A significant area for improvement is the treatment of the solid-liquid interface, where an explicit description of the electrolyte under realistic constant potential conditions remains the ultimate goal. This perspective examines recent advancements in charged interface modelling. We highlight cutting- edge simulation approaches, including the integration of machine learning techniques towards realistic atomic scale modelling for electrocatalytic materials design. As a case study, we focus on progress in understanding electrochemical nitrogen reduction for green ammonia production.