# 논문

## Applying Machine Learning Algorithms to Predict Potential Energies and Atomic Forces during C-H Activation

• 저자Hyun Woo KIM,Hyunju CHANG,Jino IM,Seok Ki KIM,Yong Tae KIM,고태욱,이승희,이종걸,현윤경
• 학술지Journal of the Korean Physical Society (0374-4884), 77, 680 ~ 688
• 등재유형SCIE
• 게재일자 20201001
Molecular dynamics (MD) simulations are useful in understanding the interaction between solid materials and molecules. However, performing MD simulations is possible only when interatomic potentials are available and constructing such interatomic potentials usually requires additional computational work. Recently, generating interatomic potentials was shown to be much easier when machine learning (ML) algorithms were used. In addition, ML algorithms require new deors for improved performance. Here, we present an ML approach with several categories of atomic deors to predict the parameters necessary for MD simulations, such as the potential energies and the atomic forces.

이 페이지에서 제공하는 정보에 대해 만족하십니까?

Ranking TOP5
채용공고
조직도
산업수학기반연구부
의료수학연구부
인사말

TOP