| Molecular dynamics simulations of brittle to ductile transition in failure mechanism of silicon nitride nanoporous membranes AK Shargh, GR Madejski, JL McGrath, N Abdolrahim Materials Today Communications 25, 101657, 2020 | 16 | 2020 |
| Mechanical properties and deformation mechanisms of amorphous nanoporous silicon nitride membranes via combined atomistic simulations and experiments AK Shargh, GR Madejski, JL McGrath, N Abdolrahim Acta Materialia 222, 117451, 2022 | 13 | 2022 |
| Molecular dynamics simulation of structural changes in single crystalline silicon nitride nanomembrane AK Shargh, N Abdolrahim Ceramics International 45 (17), 23070-23077, 2019 | 10 | 2019 |
| Mining structure-property linkage in nanoporous materials using an interpretative deep learning approach H Liu, AK Shargh, N Abdolrahim Materialia 21, 101275, 2022 | 9 | 2022 |
| An interpretable deep learning approach for designing nanoporous silicon nitride membranes with tunable mechanical properties AK Shargh, N Abdolrahim npj Computational Materials 9 (1), 82, 2023 | 7 | 2023 |
| Mechanisms of helium nanobubble growth and defect interactions in irradiated copper: A molecular dynamics study AK Shargh, O Bosić, N Abdolrahim Journal of Nuclear Materials 574, 154199, 2023 | 6 | 2023 |
| Coexistence of vitreous and crystalline phases of H2O at ambient temperature AK Shargh, A Picard, R Hrubiak, D Zhang, RJ Hemley, S Deemyad, ... Proceedings of the National Academy of Sciences 119 (27), e2117281119, 2022 | 6 | 2022 |
| Phase-transformation assisted twinning in Molybdenum nanowires A Mostafa, L Vu, Z Guo, AK Shargh, A Dey, H Askari, N Abdolrahim Computational Materials Science 244, 113273, 2024 | | 2024 |
| Deep Learning Accelerated Phase Prediction of Refractory Multi-Principal Element Alloys AK Shargh, CD Stiles, JA El-Awady arXiv preprint arXiv:2408.06237, 2024 | | 2024 |
| Mechanics of Materials With Engineered Microstructures: Physics-Based Modeling and Deep Learning Investigation AK Shargh University of Rochester, 2023 | | 2023 |
