| Data-driven methods for predicting the state of health, state of charge, and remaining useful life of li-ion batteries: A comprehensive review E Kim, M Kim, J Kim, J Kim, JH Park, KT Kim, JH Park, T Kim, K Min International Journal of Precision Engineering and Manufacturing 24 (7 …, 2023 | 33 | 2023 |
| Prediction of dielectric constants of ABO 3-type perovskites using machine learning and first-principles calculations E Kim, J Kim, K Min Physical Chemistry Chemical Physics 24 (11), 7050-7059, 2022 | 22 | 2022 |
| Synthesizable Double Perovskite Oxide Search via Machine Learning and High‐Throughput Computational Screening J Kim, E Kim, K Min Advanced Theory and Simulations 4 (10), 2100263, 2021 | 20 | 2021 |
| Enhanced Hydrogen Evolution Performance at the Lateral Interface between Two Layered Materials Predicted with Machine Learning TH Pham, E Kim, K Min, YH Shin ACS Applied Materials & Interfaces 15 (23), 27995-28007, 2023 | 10 | 2023 |
| Rapid discovery of promising materials via active learning with multi-objective optimization T Park, E Kim, J Sun, M Kim, E Hong, K Min Materials Today Communications 37, 107245, 2023 | 5 | 2023 |
| Impact of Data Partitioning to Improve Prediction Accuracy for Remaining Useful Life of Li‐Ion Batteries J Kim, E Kim, JH Park, KT Kim, JH Park, T Kim, K Min International Journal of Energy Research 2023 (1), 9305309, 2023 | 3 | 2023 |
| Online Battery Data Analytics Pipeline using Bigdata Tools for Electric Vehicles A Akash, D Yendluri, J Kim, T Kim, E Kim, JH Park, KT Kim, JH Park, K Min 2023 11th International Conference on Power Electronics and ECCE Asia (ICPE …, 2023 | 2 | 2023 |
| Measuring the water content of polymer electrolyte membranes using double points of proton magic angle spinning nuclear magnetic resonance data RY Hwang, Y Moon, HM Kim, E Kim, S Park, OH Han Polymer 309, 127431, 2024 | 1 | 2024 |