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Grand and Semigrand Canonical Basin-Hopping.

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Calvo, F 
Schebarchov, D 
Wales, DJ 


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.



Algorithms, Alloys, Models, Molecular, Nanostructures, Temperature, Thermodynamics

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J Chem Theory Comput

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American Chemical Society (ACS)
Engineering and Physical Sciences Research Council (EP/J010847/1)
Engineering and Physical Sciences Research Council (EP/N035003/1)
FC acknowledges generous computational resources granted by the regional Pôle Scientifique de Modélisation Numérique in Lyon. DJW and DS acknowledge financial support from the EPSRC and the ERC.