Structure prediction for multicomponent materials using biminima

Abstract

The potential energy surface of a heteroparticle system will contain points that are local minima in both coordinate space and permutation space for the di erent species. We introduce the term biminima to describe these special points, and we formulate a deterministic scheme for nding them. Our search algorithm generates a converging sequence of particle-identity swaps, each accompanied by a number of local geometry relaxations. For selected binary atomic clusters of size N = NA + NB 98, convergence to a biminimum on average takes 3NANB relaxations, and the number of biminima grows with the preference for mixing. The new framework uni es continuous and combinatorial optimization, providing a powerful tool for structure prediction and rational design of multicomponent materials.