Published in Computer Physics Communications, 2022
KLIFF: A framework to develop physics-based and machine learning interatomic potentials.
Recommended citation: M Wen, Y Afshar, RS Elliott, EB Tadmor, "KLIFF: A framework to develop physics-based and machine learning interatomic potentials." Computer Physics Communications, 272, 108218, (2022). https://doi.org/10.1016/j.cpc.2021.108218
Published in Chemical Science, 2022
Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining.
Recommended citation: M Wen, SM Blau, X Xie, S Dwaraknath, K Persson, "Improving machine learning performance on small chemical reaction data with unsupervised contrastive pretraining." Chemical Science, 13, 1446-1458, (2022). https://doi.org/10.1039/D1SC06515G
Published in Scientific Data, 2021
Quantum Chemical Calculations of Lithium-Ion Battery Electrolyte and Interphase Species.
Recommended citation: EW Spotte-Smith, S Blau, X Xie, H Patel, M Wen, B Wood, S Dwaraknath, K Persson, "Quantum Chemical Calculations of Lithium-Ion Battery Electrolyte and Interphase Species." Scientific Data, 8, 203, (2021). https://doi.org/10.1038/s41597-021-00986-9
Published in Journal of the American Chemical Society, 2021
Data-Driven prediction of formation mechanisms of lithium ethylene monocarbonate with an automated reaction network.
Recommended citation: X Xie, EW Spotte-Smith, M Wen, HD Patel, SM Blau, KA Persson, "Data-Driven prediction of formation mechanisms of lithium ethylene monocarbonate with an automated reaction network." Journal of the American Chemical Society, 143, 13245-13258, (2021). https://doi.org/10.1021/jacs.1c05807
Published in npj Comput. Mater., 2020
Uncertainty quantification in molecular simulations with dropout neural network potentials.
Recommended citation: M Wen, EB Tadmor, "Uncertainty quantification in molecular simulations with dropout neural network potentials." npj Comput. Mater., 6, 124, (2020). https://doi.org/10.1038/s41524-020-00390-8
Published in Chemical Science, 2020
BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules.
Recommended citation: M Wen, SM Blau, EW Spotte-Smith, S Dwaraknath, KA Persson, "BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules." Chemical Science, 12, 1858-1868, (2020). https://doi.org/10.1039/D0SC05251E
Published in Phys. Rev. B, 2019
Hybrid neural network potential for multilayer graphene.
Recommended citation: M Wen, EB Tadmor, "Hybrid neural network potential for multilayer graphene." Phys. Rev. B, 100, 195419, (2019). https://doi.org/10.1103/physrevb.100.195419
Published in Phys. Rev. B, 2018
Dihedral-angle-corrected registry-dependent interlayer potential for multilayer graphene structures.
Recommended citation: M Wen, S Carr, S Fang, E Kaxiras, EB Tadmor, "Dihedral-angle-corrected registry-dependent interlayer potential for multilayer graphene structures." Phys. Rev. B, 98, 235404, (2018). https://doi.org/10.1103/physrevb.98.235404
Published in J. Appl. Phys., 2017
A force-matching Stillinger-Weber potential for MoS2: Parameterization and Fisher information theory based sensitivity analysis.
Recommended citation: M Wen, SN Shirodkar, P Plech{\'{a}}{\v{c}}, E Kaxiras, RS Elliott, EB Tadmor, "A force-matching Stillinger-Weber potential for MoS2: Parameterization and Fisher information theory based sensitivity analysis." J. Appl. Phys., 122, 244301, (2017). https://doi.org/10.1063/1.5007842
Published in Modell. Simul. Mater. Sci. Eng., 2017
A KIM-compliantpotfitfor fitting sloppy interatomic potentials: application to the EDIP model for silicon.
Recommended citation: M Wen, J Li, P Brommer, RS Elliott, JP Sethna, EB Tadmor, "A KIM-compliantpotfitfor fitting sloppy interatomic potentials: application to the EDIP model for silicon." Modell. Simul. Mater. Sci. Eng., 25, 014001, (2017). https://doi.org/10.1088/0965-0393/25/1/014001
Published in Modell. Simul. Mater. Sci. Eng., 2015
Interpolation effects in tabulated interatomic potentials.
Recommended citation: M Wen, SM Whalen, RS Elliott, EB Tadmor, "Interpolation effects in tabulated interatomic potentials." Modell. Simul. Mater. Sci. Eng., 23, 074008, (2015). https://doi.org/10.1088/0965-0393/23/7/074008
Published in J. Nucl. Mater., 2013
Constitutive modeling for the anisotropic uniaxial ratcheting behavior of Zircaloy-4 alloy at room temperature.
Recommended citation: H Li, M Wen, G Chen, W Yu, X Chen, "Constitutive modeling for the anisotropic uniaxial ratcheting behavior of Zircaloy-4 alloy at room temperature." J. Nucl. Mater., 443, 152-160, (2013). https://doi.org/10.1016/j.jnucmat.2013.06.052
Published in Mater. Des., 2013
Uniaxial ratcheting behavior of Zircaloy-4 tubes at room temperature.
Recommended citation: M Wen, H Li, D Yu, G Chen, X Chen, "Uniaxial ratcheting behavior of Zircaloy-4 tubes at room temperature." Mater. Des., 46, 426-434, (2013). https://doi.org/10.1016/j.matdes.2012.10.049