Genetic Algorithm Application to the Structural Properties of Si-Ge Mixed Clusters

Dugan, Nazim
Erkoç, Şakir
Optimum geometries of silicon-germanium (Si-Ge) clusters are found using a single parent genetic algorithm. 100 atom and 150 atom clusters are studied with some variety of compositions and initial geometries. Total interaction energies, distances of Si and Ge atoms to the cluster centers, and average bond lengths are calculated. Si-core Ge-shell geometry is found to be favorable compared to other geometries.


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Evolutionary computation techniques (in particular, genetic algorithms) have been applied to optimize the structure of microclusters. Various empirical potential energy functions have been used to describe the interactions among the atoms in the clusters. A comparative study of silicon microclusters has been performed.
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Citation Formats
N. Dugan and Ş. Erkoç, “Genetic Algorithm Application to the Structural Properties of Si-Ge Mixed Clusters,” MATERIALS AND MANUFACTURING PROCESSES, pp. 250–254, 2009, Accessed: 00, 2020. [Online]. Available: