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

Abstract

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 NO 2 -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. • The first elementary reduction of R-NO 2 limits the rate of nitrobenzene reduction • Strong O binding poisons catalysts otherwise active for nitrobenzene reduction • Intermediate O binding leads to an optimal nitrobenzene reduction electrocatalyst The reduction of nitroaromatics is important in both the production of fine chemicals and the treatment of wastewater. Electrocatalytic reduction could offer an energy-efficient and scalable approach for these applications. The development of active and selective electrocatalysts is facilitated by elementary mechanism determination. We applied density functional theory to determine the rate-limiting steps in electrocatalytic nitrobenzene reduction over late-transition metals. A “volcano” trade-off dictated by the metals’ affinity for binding O was developed and used to predict single-metal and bimetallic surfaces that would optimize nitrobenzene electroreduction activity. Rate-limiting steps in electrochemical nitrobenzene reduction on late-transition-metal surfaces are determined using density functional theory calculations. A rationale for electrocatalyst optimization is presented and used to suggest optimal nitroaromatic reduction electrocatalysts.