Modified genetic algorithms to model atomic cluster structures: CuSi clusters

Abstract

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.