Modified genetic algorithms to model atomic cluster structures: CuSi clusters

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This paper presents the results obtained using a genetic algorithm (GA) to search for stable structures of Cu-silicon clusters. In this work the GA uses a semiempirical energy function to find the best cluster structures, which are further optimized using density functional theory. For small cluster...

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Detalles Bibliográficos
Autores principales: Oña, O., Bazterra, V.E., Caputo, M.C., Ferraro, M.B., Fuentealba, P., Facelli, J.C.
Formato: JOUR
Materias:
Atomic cluster structure
Genetic algorithms
copper
silicon
article
atomic particle
cluster analysis
density functional theory
energy
genetic algorithm
structure analysis
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01661280_v681_n1-3_p149_Ona
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
Descripción
Sumario:This paper presents the results obtained using a genetic algorithm (GA) to search for stable structures of Cu-silicon clusters. In this work the GA uses a semiempirical energy function to find the best cluster structures, which are further optimized using density functional theory. For small clusters our results agree well with previously reported structures, but for larger ones new structures appear in addition to those previously found using limited local searches on common structural motifs. This demonstrates the need for global optimization schemes when searching for stable structures of medium size Cu-silicon clusters. © 2004 Elsevier B.V. All rights reserved.

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