title: Grand and Semigrand Canonical Basin-Hopping.
abstract: We introduce grand and semigrand canonical global optimization approaches using basin-hopping with an acceptance criterion based on the local contribution of each potential energy minimum to the (semi)grand potential. The method is tested using local harmonic vibrational densities of states for atomic clusters as a function of temperature and chemical potential. The predicted global minima switch from dissociated states to clusters for larger values of the chemical potential and lower temperatures, in agreement with the predictions of a model fitted to heat capacity data for selected clusters. Semigrand canonical optimization allows us to identify particularly stable compositions in multicomponent nanoalloys as a function of increasing temperature, whereas the grand canonical potential can produce a useful survey of favorable structures as a byproduct of the global optimization search.
authors.affiliation: Université Grenoble Alpes , LIPHY, F-38000 Grenoble, France.|CNRS , LIPHY, F-38000 Grenoble, France.
authors.forename: F
authors.initials: F
authors.lastname: Calvo
authors.affiliation: University Chemical Laboratories , Lensfield Road, Cambridge CB2 1EW, United Kingdom.
authors.forename: D
authors.initials: D
authors.lastname: Schebarchov
authors.affiliation: University Chemical Laboratories , Lensfield Road, Cambridge CB2 1EW, United Kingdom.
authors.forename: D J
authors.initials: DJ
authors.lastname: Wales
mesh_terms: D000465:Algorithms; D000497:Alloys / Q000737:chemistry; D008958:Models, Molecular; D049329:Nanostructures / Q000737:chemistry; D013696:Temperature; D013816:Thermodynamics
chemical_list: D000497:Alloys