| Lattice thermal conductivity: an accelerated discovery guided by machine learning R Jaafreh, YS Kang, K Hamad ACS Applied Materials & Interfaces 13 (48), 57204-57213, 2021 | 34 | 2021 |
| Machine learning guided discovery of super-hard high entropy ceramics R Jaafreh, YS Kang, JG Kim, K Hamad Materials Letters 306, 130899, 2022 | 20 | 2022 |
| Effect of CaO on structure and properties of AZ61 magnesium alloy UM Chaudry, Y Noh, G Han, R Jaafreh, TS Jun, K Hamad Materials Science and Engineering: A 844, 143189, 2022 | 15 | 2022 |
| A deep learning perspective into the figure-of-merit of thermoelectric materials R Jaafreh, KY Seong, JG Kim, K Hamad Materials Letters 319, 132299, 2022 | 14 | 2022 |
| Age-hardening behavior guided by the multi-objective evolutionary algorithm and machine learning R Jaafreh, UM Chaudry, K Hamad, T Abuhmed Journal of Alloys and Compounds 893, 162104, 2022 | 12 | 2022 |
| Brittle and ductile characteristics of intermetallic compounds in magnesium alloys: A large-scale screening guided by machine learning R Jaafreh, YS Kang, K Hamad Journal of Magnesium and Alloys 11 (1), 392-404, 2023 | 10 | 2023 |
| Incorporation of machine learning in additive manufacturing: a review A Raza, KM Deen, R Jaafreh, K Hamad, A Haider, W Haider The International Journal of Advanced Manufacturing Technology 122 (3), 1143 …, 2022 | 9 | 2022 |
| A comparative study of strain rate constitutive and machine learning models for flow behavior of AZ31-0.5 Ca Mg alloy during hot deformation UM Chaudry, R Jaafreh, A Malik, TS Jun, K Hamad, T Abuhmed Mathematics 10 (5), 766, 2022 | 9 | 2022 |
| Solid electrolytes for Li-ion batteries via machine learning S Pereznieto, R Jaafreh, J Kim, K Hamad Materials Letters 337, 133926, 2023 | 8 | 2023 |
| A Machine Learning‐Assisted Approach to a Rapid and Reliable Screening for Mechanically Stable Perovskite‐Based Materials R Jaafreh, A Sharan, M Sajjad, N Singh, K Hamad Advanced Functional Materials 33 (1), 2210374, 2023 | 8 | 2023 |
| Crystal structure guided machine learning for the discovery and design of intrinsically hard materials R Jaafreh, T Abuhmed, JG Kim, K Hamad Journal of Materiomics 8 (3), 678-684, 2022 | 7 | 2022 |
| Learning techniques for designing solid-state lithium-ion batteries with high thermomechanical stability S Kumar, R Jaafreh, S Dutta, S Pereznieto, K Hamad, DH Yoon Materials Letters 351, 135049, 2023 | 3 | 2023 |
| Discovery of solid-state electrolytes for Na-ion batteries using machine learning S Pereznieto, R Jaafreh, J Kim, K Hamad Materials Letters 349, 134848, 2023 | 2 | 2023 |
| Interpretable Machine Learning Analysis of Stress Concentration in Magnesium: An Insight beyond the Black Box of Predictive Modeling R Jaafreh, JG Kim, K Hamad Crystals 12 (9), 1247, 2022 | 2 | 2022 |
| Phonon DOS-Based Machine Learning Model for Designing High-Performance Solid Electrolytes in Li-Ion Batteries R Jaafreh, S Pereznieto, S Jeong, IP Widiantara, JM Oh, JH Kang, J Mun, ... International Journal of Energy Research 2024, 2024 | 1 | 2024 |
| Accelerated discovery of perovskite materials guided by machine learning techniques S Kumar, S Dutta, R Jaafreh, N Singh, A Sharan, K Hamad, DH Yoon Materials Letters 353, 135311, 2023 | 1 | 2023 |
| Utilizing machine learning and phonon density of states for innovative approaches to design and optimize high-performance solid-state Mg-ion electrolytes R Jaafreh, JG Kim, K Hamad Journal of Power Sources 606, 234575, 2024 | | 2024 |
| Predictive modeling of critical temperatures in magnesium compounds using transfer learning S Kumar, R Jaafreh, S Dutta, JH Yoo, S Pereznieto, K Hamad, DH Yoon Journal of Magnesium and Alloys, 2024 | | 2024 |
Kotiba HamadAssociate Professor, School of Advanced Materials Science & Engineering, Sungkyunkwan universityVerified email at skku.edu
