| Accelerated recrystallization behavior of commercially pure titanium subjected to an alternating-current electropulse M Lee, J Yu, MH Bae, JW Won, T Lee Journal of Materials Research and Technology 15, 5706-5711, 2021 | 21 | 2021 |
| Prediction of electropulse-induced nonlinear temperature variation of Mg alloy based on machine learning J Yu, M Lee, YH Moon, Y Noh, T Lee Korean Journal of Metals and Materials 58 (6), 413-422, 2020 | 20 | 2020 |
| Deep-learning approach to predict a severe plastic anisotropy of caliber-rolled Mg alloy T Lee, BJ Kwak, J Yu, JH Lee, Y Noh, YH Moon Materials Letters 269, 127652, 2020 | 18 | 2020 |
| Anisotropic microstructural evolutions of extruded ZK60 Mg alloy subjected to electropulsing treatment SJ Oh, J Yu, S Cheon, SH Lee, SY Lee, T Lee Journal of Materials Research and Technology 26, 3322-3331, 2023 | 10 | 2023 |
| Exploiting Electropulses to Optimize Microstructure in Ti–6Al–4V Fabricated by Selective Laser Melting SH Lee, J Yu, S Cheon, JG Kim, T Lee Metals and Materials International 30 (4), 886-894, 2024 | 8 | 2024 |
| Enhanced kinetics of microstructural evolution in Ti–6Al–4V through electropulsing treatment M Kim, SH Lee, J Yu, S Cheon, S Byun, CS Lee, T Lee Journal of Materials Research and Technology 26, 8500-8508, 2023 | 7 | 2023 |
| Enhanced processing map of Ti–6Al–2Sn–2Zr–2Mo–2Cr–0.15 Si aided by extreme gradient boosting MH Bae, M Kim, J Yu, MS Lee, SW Lee, T Lee Heliyon 8 (10), 2022 | 6 | 2022 |
| Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation S Byun, J Yu, S Cheon, SH Lee, SH Park, T Lee Journal of Magnesium and Alloys 12 (1), 186-196, 2024 | 4 | 2024 |
| Predicting the Effect of Processing Parameters on Caliber-Rolled Mg Alloys through Machine Learning J Yu, SJ Oh, S Baek, J Kim, T Lee Applied Sciences 12 (20), 10646, 2022 | 4 | 2022 |
| Predicting deformation behavior of additively manufactured Ti-6Al-4V based on XGB and LGBM S Cheon, J Yu, JG Kim, JS Oh, TH Nam, T Lee Transactions of Materials Processing 31 (4), 173-178, 2022 | 4 | 2022 |
| Microstructural evolution of multi-pass caliber-rolled Mg–Sn and Mg–Sn–Mn alloys J Yu, H Liao, JH Lee, YH Moon, HS Yoon, J Kim, T Lee Metals 10 (9), 1203, 2020 | 3 | 2020 |
| Alternative predictive approach for low-cycle fatigue life based on machine learning and energy-based modeling J Yu, SH Lee, S Cheon, SH Park, T Lee Journal of Magnesium and Alloys 12 (10), 4075-4084, 2024 | 1 | 2024 |
| Improved Prediction for Nonlinear Thermal History of Mg Alloy Subjected to Multiple Electropulses J Yu, S Cheon, SH Lee, T Lee Advanced Engineering Materials 26 (21), 2400575, 2024 | | 2024 |
| Electropulsing anisotropy of cold-rolled Grade 2 titanium sheet: Effect of electric current direction on recrystallization and hardness SH Lee, MH Bae, J Yu, S Cheon, JW Won, SH Kim, T Lee Journal of Materials Research and Technology 31, 2249-2256, 2024 | | 2024 |
| Microstructural Evolution Near Microcrack in AZ31 Mg Alloy Under Electropulses J Yu, SH Lee, S Cheon, M Mun, JH Lee, T Lee TMS Annual Meeting & Exhibition, 47-48, 2024 | | 2024 |
| Microstructural Evolution of Hot-Rolled AZ31 Mg Plate Induced by Electropulsing Treatment S Cheon, J Yu, SH Lee, SH Park, T Lee TMS Annual Meeting & Exhibition, 61-62, 2024 | | 2024 |
| Thermal Gradient Change of T-shaped Mg Alloy Specimen Exposed to Electropulses JH Song, DJ Park, S Cheon, J Yu, SH Lee, T Lee Transactions of Materials Processing 33 (4), 285-290, 2024 | | 2024 |
| Prediction of Cryogenic-and Room-Temperature Deformation Behavior of Rolled Titanium using Machine Learning S Cheon, J Yu, SH Lee, MS Lee, TS Jun, T Lee Transactions of Materials Processing 32 (2), 74-80, 2023 | | 2023 |
Taekyung LeeSchool of Mechanical Engineering, Pusan National University, KoreaVerified email at pnu.edu
