Abstract

We present a method for predicting the catalytic activity of the equilibrium surface of an alloy as a function of composition and temperature, allowing for the identification of the region of the alloy phase diagram that maximizes catalytic activity. This is accomplished by simultaneously treating the strain (due to the equilibrium lattice parameter of the bulk material) and ensemble (due to atomic order near the active site) effects with a lattice-parameter-dependent cluster expansion, where the energy of each cluster is expressed as a quadratic function of lattice parameter. We demonstrate our approach using the (111) surface of Pt–Ni catalysts for the oxygen reduction reaction (ORR), for which we present the catalytic activity of both ordered and disordered phases as a function of composition and temperature. We discuss how the optimal composition differs between the phases and suggest synthesis strategies for optimizing catalytic activity. We discuss other possible applications of our approach, including modeling strain effects that are driven by nanoparticle size effects or the creation of core-shell structures.

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