title: Quasi-combinatorial energy landscapes for nanoalloy structure optimisation.
abstract: We formulate nanoalloy structure prediction as a mixed-variable optimisation problem, where the homotops can be associated with an effective, quasi-combinatorial energy landscape in permutation space. We survey this effective landscape for a representative set of binary systems modelled by the Gupta potential. In segregating systems with small lattice mismatch, we find that homotops have a relatively straightforward landscape with few local optima - a scenario well-suited for local (combinatorial) optimisation techniques that scale quadratically with system size. Combining these techniques with multiple local-neighbourhood structures yields a search for multiminima, and we demonstrate that generalised basin-hopping with a metropolis acceptance criterion in the space of multiminima can then be effective for global optimisation of binary and ternary nanoalloys.
authors.affiliation: University Chemical Laboratories, Lensfield Road, Cambridge CB2 1EW, UK. Dmitri.Schebarchov@gmail.com dw34@cam.ac.uk.
authors.forename: D
authors.initials: D
authors.lastname: Schebarchov
authors.forename: D J
authors.initials: DJ
authors.lastname: Wales