| Architectural design of advanced aluminum matrix composites: A review of recent developments B Sadeghi, P Cavaliere, CI Pruncu, M Balog, M Marques de Castro, ... Critical Reviews in Solid State and Materials Sciences 49 (1), 1-71, 2024 | 17 | 2024 |
| Transferable Deep Learning Potential Reveals Intermediate-Range Ordering Effects in LiF–NaF–ZrF4 Molten Salt R Chahal, S Roy, M Brehm, S Banerjee, V Bryantsev, ST Lam JACS Au 2 (12), 2693-2702, 2022 | 17 | 2022 |
| Molecular dynamics for the prediction of the interfacial shear stress and interface dielectric properties of carbon fiber epoxy composites R Chahal, A Adnan, K Reifsnider, R Raihan, Y Ting Wu, V Vadlamudi, ... Proceedings of the American Society for Composites—Thirty-third Technical …, 2018 | 10 | 2018 |
| Short-to Intermediate-Range Structure, Transport, and Thermophysical Properties of LiF–NaF–ZrF4 Molten Salts R Chahal, S Banerjee, ST Lam Frontiers in Physics 10, 830468, 2022 | 9 | 2022 |
| Radiation effect on MHD casson fluid flow over a power-law stretching sheet with chemical reaction M Reza, R Chahal, N Sharma World Academy of Science, Engineering and Technology International Journal …, 2016 | 7 | 2016 |
| Ab-initio Molecular Dynamics Study of LiF-NaF-ZrF4 Molten Salt System R Chahal, S Lam Transactions of the American Nuclear Society 125 (1), 549-553, 2021 | 3 | 2021 |
| Complex Structure of Molten FLiBe (2–) Examined by Experimental Neutron Scattering, X-Ray Scattering, and Deep-Neural-Network Based Molecular … S Fayfar, R Chahal, H Williams, DN Gardner, G Zheng, D Sprouster, ... PRX Energy 3 (1), 013001, 2024 | 2 | 2024 |
| Three-Dimensional Stochastic Modelling of Wavy Carbon Nanotube Reinforced Epoxy Nanocomposites R Chahal, A Adnan Multiscale Science and Engineering 3 (1), 51-61, 2021 | 2 | 2021 |
| Elastic constants of carbon nanotube reinforced polymer nanocomposites R Chahal, A Adnan, A Roy American Society of Composites 32nd Technical Conference, 2017 | 2 | 2017 |
| Molecular dynamics study of carbon nanotube/epoxy interfaces using ReaxFF R Chahal, A Adnan, A Roy American Society of Composites 32nd Technical Conference, 2017 | 2 | 2017 |
| Structure Analysis of LiF-NaF-ZrF4 Molten Salts with Deep Learning Potentials R Chahal, S Lam Transactions of the American Nuclear Society 126 (1), 113-116, 2022 | 1 | 2022 |
| Generating Representative Volume Element (RVE) for Finite Element Analysis of Random Fiber Composites/Nanocomposites R Chahal, A Adnan, A Roy | 1 | 2017 |
| Chemistry Informed Machine Learning-Based Heat Capacity Prediction of Solid Mixed Oxides J Barra, R Chahal, S Audesse, J Zhang, Y Zhong, J Kabel, S Lam The Journal of Physical Chemistry Letters 15, 4721-4728, 2024 | | 2024 |
| Deep Learning Interatomic Potential Connects Molecular Structural Ordering to Macroscale Properties of Polyacrylonitrile (PAN) Polymer R Chahal, MD Toomey, LT Kearney, A Sedova, JT Damron, AK Naskar, ... arXiv preprint arXiv:2404.16187, 2024 | | 2024 |
| X-ray and molecular dynamics study of the temperature-dependent structure of molten NaF-ZrF4 A Wadehra, R Chahal, S Banerjee, A Levy, Y Zhang, H Yan, D Olds, ... arXiv preprint arXiv:2403.06049, 2024 | | 2024 |
| Free energy simulations with machine learning-based forcefields for prediction of thermodynamic properties of molten salts V Bryantsev, L Gibson, R Chahal, S Roy Bulletin of the American Physical Society, 2024 | | 2024 |
| Deep learning potentials for hydration and protonation in biomolecular simulations: bond breaking is the goal and the problem A Sedova, M Smith, M Coletti, R Chahal, S Roy Bulletin of the American Physical Society, 2024 | | 2024 |
| Tracing mechanistic pathways and reaction kinetics toward equilibrium in reactive molten salts LD Gibson, S Roy, R Khanal, R Chahal, A Sedova, VS Bryantsev Chemical Science, 2024 | | 2024 |
| ab initio informed inelastic neutron scattering for time-resolved local dynamics in molten MgCl2 S Banerjee, R Chahal, AS Ivanov, S Roy, VS Bryantsev, Y Shinohara, ... arXiv preprint arXiv:2311.13537, 2023 | | 2023 |
| High-Throughput Prediction of Molten Salt Mixture Density with Supervised Machine Learning J Barra Otondo, S Shahbazi, T Starkus, T Birri, S Audesse, P Balaprakash, ... Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States), 2023 | | 2023 |
Stephen T. LamUniversity of Massachusetts Lowell, Formerly @ MITVerified email at uml.edu
