Authors: O.B. Oña, M.B. Ferraro, J.C. Facelli
Affilation: University of Utah, United States
Pages: 324 - 327
Keywords: DFT, genetic algorithms, Si-Cu clusters
The characterization and prediction of the structures of metal silicon clusters is important for nanotechnology research because these clusters can be used as building blocks for nano devices. Several authors have postulated that there is a transition between exo to endo absorption of Cu in SinCu clusters. Here we use our Parallel Genetic Algorithms as implemented in our MGAC software directly coupled with DFT energy calculations to show that the global search of SinCu cluster structures does not find endohedral clusters for n < 8 and finds them for n > 8. These results are in qualitative agreement with the existent experimental evidence. This research demonstrates that our parallel genetic algorithms approach is a reliable method to study the exo/endo transition in Si-transition metals clusters and that modeling techniques such as those used in this paper can be used successfully to predict the structures of critical building blocks for nano devices.
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