Surface Energy as a Descriptor of Catalytic Activity

Computational searches for catalysts of the hydrogen evolution reaction commonly use the hydrogen binding energy (HBE) as a predictor of catalytic activity. Accurate evaluation of the HBE, however, can involve large periodic supercell slab models that render high-throughput screening relatively expensive. In contrast, calculations of other relevant surface properties, such as the surface energy, work function, and potential of zero charge (PZC), require only small surface unit cells and are hence less expensive to compute. Correlations between catalytic activity and these surface properties warrant exploration because of this reduced computational cost. Here, we use density functional theory in conjunction with three different exchange-correlation functionals the local density approximation (LDA), the Perdew Burke Ernzerhof (PBE) generalized gradient approximation, and the PBEsol functional (a reparameterization of the PBE functional) to calculate the lattice constants, surface energy, cohesive energy, and work function of six common catalysts: three metals (Au, Pd, and Pt) and three transition metal carbides (TMCs; WC, W2C, and Mo2C). The three exchange-correlation functionals produce identical trends, and PBEsol yields results between those calculated using LDA and PBE and most often closer to experiment. We therefore use PBEsol to obtain the surface energy, work function, and PZC of nine novel hybrid catalysts, each containing a metal monolayer on a TMC substrate. Importantly, a volcano-shaped correlation between the experimental exchange current density and the theoretical surface energies emerges. We also investigate solvation effects on the surface energy and work function using a polarizable continuum model within the framework of joint density functional theory. For these particular materials, the surface energies in vacuum are nearly unchanged upon exposure to an aqueous solution, prior to any reaction with water. The volcano-shaped correlation observed between the exchange current densities and the surface energies is not observed for the work function or PZC. Our work thus reveals opportunities for more rapid computational screening of reduced Pt-loading catalysts using the surface energy as a computationally efficient catalytic descriptor.