Solvent effect on the electrocatalytic nitrogen reduction reaction: a deep potential molecular dynamics simulation with enhanced sampling for the case of the ruthenium single atom catalyst

Abstract

The electrocatalytic nitrogen reduction reaction (NRR) is a promising approach for the production of ammonia at ambient temperature and pressure. However, the intricate structure of the solvent–catalyst interface has often led to a significant discrepancy between current computational and experimental studies. To elucidate the explicit hydration structure and complex proton transfer mechanism during electrocatalytic NRR, we employed enhanced sampling molecular dynamics simulations with a neural network potential to incorporate the solvation effect on a nitrogen-doped graphene Ru single-atom catalyst. The present study provides direct observation of how solvent water molecules participate in the NRR process and profoundly impact the NRR dynamics. In particular, a significantly lower free energy barrier (0.59 eV) and a small free energy change (0.15 eV) were obtained for the rate-determining step, i.e., the first hydrogenation step of NRR, compared to the prediction (free energy change of 1.19 eV) without considering the solvent effect. The present prediction is in good agreement with the existing experimental result.