| Artificial intelligence in the design of innovative metamaterials: A comprehensive review JH Song, JH Lee, N Kim, K Min International Journal of Precision Engineering and Manufacturing 25 (1), 225-244, 2024 | 15 | 2024 |
| Correlating atomistic characteristics of zeolites to their 3D-Printed Macro structural properties for prediction of mechanical response J Kim, M Hong, J Song, N Kim, K Min Materials & Design 233, 112189, 2023 | 3 | 2023 |
| Molecular Dynamics and Machine Learning Insights into the Mechanical Behavior of Zeolites under Large Deformation JH Song, D Lee, N Kim, K Min Materials Today Communications, 110922, 2024 | | 2024 |
| Integrating Data Mining and Natural Language Processing to Construct a Melting Point Database for Organometallic Compounds J Jeong, T Park, JH Song, S Kang, J Won, J Han, K Min Journal of Chemical Information and Modeling, 2024 | | 2024 |
| Interpretable machine learning boosting the discovery of targeted organometallic compounds with optimal bandgap T Park, JH Song, J Jeong, S Kang, J Kim, J Won, J Han, K Min Materials Today Advances 23, 100520, 2024 | | 2024 |
| Enhancing protein aggregation prediction: a unified analysis leveraging graph convolutional networks and active learning J Sun, JH Song, J Kim, S Kang, E Park, S Seo, K Min RSC advances 14 (43), 31439-31450, 2024 | | 2024 |
