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Global geometry optimization of clusters using a growth strategy optimized by a genetic algorithm

✍ Scribed by Bernd Hartke

Publisher: Elsevier Science
Year: 1995
Tongue: English
Weight: 595 KB
Volume: 240
Category: Article
ISSN: 0009-2614
DOI: 10.1016/0009-2614(95)00587-t

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✦ Synopsis

A new strategy for global geometry optimization of clusters is presented. Important features are a restriction of search space to favorable nearest-neighbor distance ranges, a suitable cluster growth representation with diminished correlations, and easy transferability of the results to larger clusters. The strengths and possible limitations of the method are demonstrated for Si,, using an empirical potential.

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