| A band-gap database for semiconducting inorganic materials calculated with hybrid functional S Kim, M Lee, C Hong, Y Yoon, H An, D Lee, W Jeong, D Yoo, Y Kang, ... Scientific Data 7 (1), 387, 2020 | 63 | 2020 |
| Training machine-learning potentials for crystal structure prediction using disordered structures C Hong, JM Choi, W Jeong, S Kang, S Ju, K Lee, J Jung, Y Youn, S Han Physical Review B 102 (22), 224104, 2020 | 30 | 2020 |
| Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials S Kang, W Jeong, C Hong, S Hwang, Y Yoon, S Han npj Computational Materials 8 (1), 108, 2022 | 19 | 2022 |
| AMP2: A fully automated program for ab initio calculations of crystalline materials Y Youn, M Lee, C Hong, D Kim, S Kim, J Jung, K Yim, S Han Computer Physics Communications 256, 107450, 2020 | 11 | 2020 |
| Stability and equilibrium structures of unknown ternary metal oxides explored by machine-learned potentials S Hwang, J Jung, C Hong, W Jeong, S Kang, S Han Journal of the American Chemical Society 145 (35), 19378-19386, 2023 | 9 | 2023 |
| Applications and training sets of machine learning potentials C Hong, J Kim, J Kim, J Jung, S Ju, JM Choi, S Han Science and Technology of Advanced Materials: Methods 3 (1), 2269948, 2023 | 5 | 2023 |
| Atomistic Simulation of HF Etching Process of Amorphous Si3N4 Using Machine Learning Potential C Hong, S Oh, H An, P Kim, Y Kim, J Ko, J Sue, D Oh, S Park, S Han ACS Applied Materials & Interfaces, 2024 | | 2024 |
Seungwu HanSeoul National University在 snu.ac.kr 的电子邮件经过验证
Seungwu HanSeoul National University在 snu.ac.kr 的电子邮件经过验证