Interplay between shape and composition in bimetallic nanoparticles revealed by an efficient optimal-exchange optimization algorithm

Despite the large relevance of bimetallic metal nanoparticles for heterogeneous catalysis, the relation between their shape and elemental composition remains elusive. Here, we investigate this relationship by implementing and applying global optimization methods enhanced with a novel optimal-exchange algorithm. In particular, we determine the lowest energy chemical orderings for PtAu nanoparticles, revealing that the most stable shape changes from highly symmetric structures for pure particles to distorted and less symmetric shapes for intermediate compositions. The presented method leverages the local atomic contributions to an empirical surrogate energy expression to identify optimal atom exchanges. This also allows us to pinpoint the origin of the stability of distorted shapes, revealing a favorable energy trade-off when over-coordinating Pt and under-coordinating Au upon distorting the particle shape.