Robust Active Site Design of Single Atom Catalysts for Electrochemical Ammonia Synthesis
Abstract
In this work, we provide a computational methodological framework using the single-atom systems as an example material class for ammonia synthesis that is robust towards parameter selection. Applying this to Pt1/g-C3N4, Ru1/g-C3N4, and Fe1/g-C3N4, we generate ensembles of limiting potentials, using the ensemble of functionals collected via Bayesian Error Estimation Functionals (BEEF), to robustly predict catalytic activity. We then extend this to study the scaling between NRR reaction intermediates and use it to identify that NNH* as the best descriptor for these relations. In addition, a procedure to investigate selectivity is outlined, and a more robust way to analyze the selectivity-activity trade-off is presented. For this single-atom material class, we find choosing catalysts that lie on the strong binding leg of the activity volcano are worth further exploration. Given the ease of integration of the proposed method with minimal additional computational cost, we believe this should become a routine part of analysis workflow for multi-electron electrochemical reactions.