Elementary mechanism for the electrocatalytic reduction of nitrobenzene on late-transition-metal surfaces from density functional theory

Reduction of nitrobenzene to aniline is important in the production of industrial chemicals and treatment of wastewater. The electrocatalytic mechanism of nitrobenzene reduction across late-transition-metal electrocatalysts is not well established, making rational electrocatalyst design challenging. Density functional theory (DFT) methods are used to identify elementary steps for nitrobenzene reduction and determine trade-offs that dictate optimizing electrocatalysts. Overall reduction activity is optimized based on a trade-off between activity for the initial reduction of the NO₂-phenyl∗ and the reduction of surface-bound hydroxide (OH∗) species. The binding of O serves as a descriptor to predict the energetics of both steps, and the optimal electrocatalyst will have an intermediate O∗ binding strength. DFT results predict that, of close-packed late-transition-metal surfaces, the Cu (111), Ir (111), Pd (111), and Pt (111) metal surfaces will most effectively balance these trade-offs. Bimetallics that could offer high electrocatalytic activity for nitroaromatic reduction are suggested.