Oh, J.S. Ryou, W. Lee, S.-C. Choi, J.-H. 2024-01-20T16:02:59Z 2024-01-20T16:02:59Z 2021-09-02 2011-11 1229-7801 https://pubs.kist.re.kr/handle/201004/129865 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. Korean Korean Ceramic Society Atoms Binary alloys Computer simulation Genetic algorithms Molecular dynamics Nanocatalysts Platinum alloys Silver alloys Atomic configuration Binary nanoparticles Calculation results Core shell structure Crossover operator Molecular dynamics methods Mutation operators Stable structures Nanoparticles Prediction of atomic configuration in binary nanoparticles by genetic algorithm Article 10.4191/kcers.2011.48.6.493 1 Journal of the Korean Ceramic Society, v.48, no.6, pp.493 - 498 Journal of the Korean Ceramic Society 48 6 493 498 scopus kci ART001606152 2-s2.0-84255170545 Article Atoms Binary alloys Computer simulation Genetic algorithms Molecular dynamics Nanocatalysts Platinum alloys Silver alloys Atomic configuration Binary nanoparticles Calculation results Core shell structure Crossover operator Molecular dynamics methods Mutation operators Stable structures Nanoparticles Atomic configuration Binary nanoparticle Computer simulation Genetic algorithm Molecular dynamics