BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules M Wen, SM Blau, EWC Spotte-Smith, S Dwaraknath, KA Persson Chemical Science 12 (5), 1858-1868, 2020 | 66 | 2020 |
Dihedral-angle-corrected registry-dependent interlayer potential for multilayer graphene structures M Wen, S Carr, S Fang, E Kaxiras, EB Tadmor Physical Review B 98 (23), 235404, 2018 | 61 | 2018 |
Uncertainty quantification in molecular simulations with dropout neural network potentials M Wen, EB Tadmor npj Computational Materials 6 (1), 124, 2020 | 60 | 2020 |
Uniaxial ratcheting behavior of Zircaloy-4 tubes at room temperature M Wen, H Li, D Yu, G Chen, X Chen Materials & Design (1980-2015) 46, 426-434, 2013 | 59 | 2013 |
Hybrid neural network potential for multilayer graphene M Wen, EB Tadmor Physical Review B 100 (19), 195419, 2019 | 58 | 2019 |
Data-driven prediction of formation mechanisms of lithium ethylene monocarbonate with an automated reaction network X Xie, E Spotte-Smith, M Wen, H Patel, S Blau, K Persson Journal of the American Chemical Society 143 (33), 13245--13258, 2021 | 41 | 2021 |
A force-matching Stillinger-Weber potential for MoS2: Parameterization and Fisher information theory based sensitivity analysis M Wen, SN Shirodkar, P Plecháč, E Kaxiras, RS Elliott, EB Tadmor Journal of Applied Physics 122 (24), 2017 | 35 | 2017 |
Chemical reaction networks and opportunities for machine learning M Wen, EWC Spotte-Smith, SM Blau, MJ McDermott, AS Krishnapriyan, ... Nature Computational Science 3 (1), 12-24, 2023 | 32 | 2023 |
Interpolation effects in tabulated interatomic potentials M Wen, SM Whalen, RS Elliott, EB Tadmor Modelling and Simulation in Materials Science and Engineering 23 (7), 074008, 2015 | 29 | 2015 |
Quantum chemical calculations of lithium-ion battery electrolyte and interphase species EWC Spotte-Smith, SM Blau, X Xie, HD Patel, M Wen, B Wood, ... Scientific Data 8 (1), 203, 2021 | 27 | 2021 |
Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining M Wen, SM Blau, X Xie, S Dwaraknath, K Persson Chemical Science 13 (5), 1446-1458, 2022 | 26 | 2022 |
A KIM-compliant potfit for fitting sloppy interatomic potentials: application to the EDIP model for silicon M Wen, J Li, P Brommer, RS Elliott, JP Sethna, EB Tadmor Modelling and Simulation in Materials Science and Engineering 25 (1), 014001, 2016 | 18 | 2016 |
KLIFF: A framework to develop physics-based and machine learning interatomic potentials M Wen, Y Afshar, RS Elliott, EB Tadmor Computer Physics Communications 272, 108218, 2022 | 17 | 2022 |
Bayesian, frequentist, and information geometric approaches to parametric uncertainty quantification of classical empirical interatomic potentials Y Kurniawan, CL Petrie, KJ Williams, MK Transtrum, EB Tadmor, ... The Journal of Chemical Physics 156 (21), 2022 | 12 | 2022 |
Constitutive modeling for the anisotropic uniaxial ratcheting behavior of Zircaloy-4 alloy at room temperature H Li, M Wen, G Chen, W Yu, X Chen Journal of nuclear materials 443 (1-3), 152-160, 2013 | 12 | 2013 |
Machine learning full NMR chemical shift tensors of silicon oxides with equivariant graph neural networks MC Venetos, M Wen, KA Persson The Journal of Physical Chemistry A 127 (10), 2388-2398, 2023 | 6 | 2023 |
Development of Interatomic Potentials with Uncertainty Quantification: Applications to Two-dimensional Materials M Wen University of Minnesota, 2019 | 4 | 2019 |
Jobflow: Computational Workflows Made Simple AS Rosen, M Gallant, J George, J Riebesell, H Sahasrabuddhe, JX Shen, ... Journal of Open Source Software 9 (93), 5995, 2024 | 3 | 2024 |
Injecting domain knowledge from empirical interatomic potentials to neural networks for predicting material properties Z Shui, D Karls, M Wen, E Tadmor, G Karypis Advances in Neural Information Processing Systems 35, 14839-14851, 2022 | 2 | 2022 |
A universal equivariant graph neural network for the elasticity tensors of any crystal system M Wen, MK Horton, JM Munro, P Huck, KA Persson arXiv preprint arXiv:2307.15242, 2023 | 1 | 2023 |