Nitrate Reduction Modeling under Acidic Conditions with Late Transition Metals

The electrochemical reduction of nitrate (NO₃R) to ammonia is a bold yet conceivable way of producing ammonia using renewable electricity. However, serious challenges remain in finding optimal electrocatalysts for the process. An atomistic understanding of the surface energetics behind the NO₃R is needed in order to design an efficient catalyst. Herein, we combine energetics from density functional theory and microkinetic modeling to demonstrate how surface descriptors can help simplify the search for efficient NO₃R electrocatalysts. We illustrate the strong correlations between transition-state energetics and O* binding energies for adsorbed nitrate and nitrite on transition metals. For intermediates from NO* and beyond, we compare the benefits of using either the N* or H* binding energies to predict reduction onset potentials. These insights enable us to develop a simple microkinetic model that elucidates the surface coverages of intermediates and the product selectivity of NO₃R across a range of potentials and transition metals. We show that the model adequately corroborates with quasi-steady-state rates observed experimentally.