Prediction of Atomic Configuration in Binary Nanoparticles by Genetic Algorithm
- Prediction of Atomic Configuration in Binary Nanoparticles by Genetic Algorithm
- 오정수; 류원룡; 이승철; 최정혜
- Atomic Configuration; Binary nanoparticle; Computer simulation; Genetic Algorithm; Molecular dynamics
- Issue Date
- 한국세라믹학회지; Journal of the Korean Ceramic Society
- VOL 48, NO 6, 493-498
- 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.
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- KIST Publication > Article
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