Molecular identification of polymers and anthropogenic particles extracted from oceanic water and fish stomach–A Raman micro-spectroscopy study S Ghosal, M Chen, J Wagner, ZM Wang, S Wall Environmental pollution 233, 1113-1124, 2018 | 126 | 2018 |
Exploiting machine learning to efficiently predict multidimensional optical spectra in complex environments MS Chen, TJ Zuehlsdorff, T Morawietz, CM Isborn, TE Markland The Journal of Physical Chemistry Letters 11 (18), 7559-7568, 2020 | 42 | 2020 |
A framework for automated structure elucidation from routine NMR spectra Z Huang, MS Chen, CP Woroch, TE Markland, MW Kanan Chemical Science 12 (46), 15329-15338, 2021 | 23 | 2021 |
Data-efficient machine learning potentials from transfer learning of periodic correlated electronic structure methods: Liquid water at AFQMC, CCSD, and CCSD (T) accuracy MS Chen, J Lee, HZ Ye, TC Berkelbach, DR Reichman, TE Markland Journal of Chemical Theory and Computation 19 (14), 4510-4519, 2023 | 21 | 2023 |
AENET–LAMMPS and AENET–TINKER: Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials MS Chen, T Morawietz, H Mori, TE Markland, N Artrith The Journal of Chemical Physics 155 (7), 2021 | 16 | 2021 |
Elucidating the Role of Hydrogen Bonding in the Optical Spectroscopy of the Solvated Green Fluorescent Protein Chromophore: Using Machine Learning to Establish the Importance … MS Chen, Y Mao, A Snider, P Gupta, A Montoya-Castillo, TJ Zuehlsdorff, ... The Journal of Physical Chemistry Letters 14 (29), 6610-6619, 2023 | 7 | 2023 |
Optically Induced Anisotropy in Time-Resolved Scattering: Imaging Molecular-Scale Structure and Dynamics in Disordered Media with Experiment and Theory A Montoya-Castillo, MS Chen, SL Raj, KA Jung, KS Kjaer, T Morawietz, ... Physical Review Letters 129 (5), 056001, 2022 | 4 | 2022 |
Building Models of Spectroscopy for Condensed Phase Systems with Atomistic Detail Using Theory and Machine Learning MS Chen Stanford University, 2023 | | 2023 |