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http://dx.doi.org/10.4191/kcers.2011.48.6.493

Prediction of Atomic Configuration in Binary Nanoparticles by Genetic Algorithm  

Oh, Jung-Soo (Computational Science Research Center, Korea Institute of Science and Technology)
Ryou, Won-Ryong (Seoul Science High School)
Lee, Seung-Cheol (Computational Science Research Center, Korea Institute of Science and Technology)
Choi, Jung-Hae (Computational Science Research Center, Korea Institute of Science and Technology)
Publication Information
Journal of the Korean Ceramic Society / v.48, no.6, 2011 , pp. 493-498 More about this Journal
Abstract
Optimal atomic configurations in a nanoparticle were predicted by genetic algorithm. A truncated octahedron with a fixed composition of 1 : 1 was investigated as a model system. A Python code for genetic algorithm linked with a molecular dynamics method was developed. Various operators were implemented to accelerate the optimization of atomic configuration for a given composition and a given morphology of a nanoparticle. The combination of random mix as a crossover operator and total_inversion as a mutation operator showed the most stable structure within the shortest calculation time. Pt-Ag core-shell structure was predicted as the most stable structure for a nanoparticle of approximately 4 nm in diameter. The calculation results in this study led to successful prediction of the atomic configuration of nanoparticle, the size of which is comparable to that of practical nanoparticls for the application to the nanocatalyst.
Keywords
Atomic configuration; Binary nanoparticle; Computer simulation; Genetic algorithm; Molecular dynamics;
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Times Cited By KSCI : 4  (Citation Analysis)
Times Cited By SCOPUS : 0
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