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. 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.
Journal: TechConnect Briefs
Volume: 3, Nanotechnology 2009: Biofuels, Renewable Energy, Coatings, Fluidics and Compact Modeling
Published: May 3, 2009
Pages: 324 - 327
Industry sector: Advanced Materials & Manufacturing
Topics: Informatics, Modeling & Simulation