| 유전알고리즘을 이용한 이원계 나노입자의 원자배열 예측 |
| 오정수, 류원룡1, 이승철, 최정혜 |
한국과학기술연구원 계산과학연구센터
1서울과학고등학교 |
| Prediction of Atomic Configuration in Binary Nanoparticles by Genetic Algorithm |
| Jung-Soo Oh, Won-Ryong Ryou1, Seung-Cheol Lee, Jung-Hae Choi |
Computational Science Research Center, Korea Institute of Science and Technology
1Seoul Science High School |
|
|
|
|
|
| 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. |
| Key words:
Atomic configuration, Binary nanoparticle, Computer simulation, Genetic algorithm, Molecular dynamics |
|
|
|
PDF Links
Full text via DOI
Download Citation 
