Machine learning for metallurgy I. A neural-network potential for Al-Cu D Marchand, A Jain, A Glensk, WA Curtin Physical Review Materials 4 (10), 103601, 2020 | 75 | 2020 |
Designing Optimal Perovskite Structure for High Ionic Conduction R Gao, ACP Jain, S Pandya, Y Dong, Y Yuan, H Zhou, LR Dedon, ... Advanced Materials 32 (1), 1905178, 2020 | 35 | 2020 |
Machine learning for metallurgy III: A neural network potential for Al-Mg-Si ACP Jain, D Marchand, A Glensk, M Ceriotti, WA Curtin Physical Review Materials 5 (5), 053805, 2021 | 31 | 2021 |
First-principles calculations of solute transport in zirconium: Vacancy-mediated diffusion with metastable states and interstitial diffusion ACP Jain, PA Burr, DR Trinkle Physical Review Materials 3 (3), 033402, 2019 | 29 | 2019 |
First principles calculations of beryllium stability in zirconium surfaces ACP Jain, DR Trinkle Acta Materialia 122, 359-368, 2017 | 11 | 2017 |
Natural aging and vacancy trapping in Al-6xxx ACP Jain, M Ceriotti, WA Curtin Journal of Materials Research, 1-17, 2023 | 2 | 2023 |
Atomic scale diffusion in complex systems from first principles A Jain University of Illinois at Urbana-Champaign, 2019 | | 2019 |
Vacancy Mediated and Interstitial Solute Transport in Zr from Density Functional Theory Calculations ACP Jain, PA Burr, DR Trinkle Materials Data Facility, 2018 | | 2018 |