Less is more: Sampling chemical space with active learning JS Smith, B Nebgen, N Lubbers, O Isayev, AE Roitberg The Journal of chemical physics 148 (24), 2018 | 750 | 2018 |
Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning JS Smith, BT Nebgen, R Zubatyuk, N Lubbers, C Devereux, K Barros, ... Nature communications 10 (1), 2903, 2019 | 673 | 2019 |
Non-adiabatic excited-state molecular dynamics: Theory and applications for modeling photophysics in extended molecular materials TR Nelson, AJ White, JA Bjorgaard, AE Sifain, Y Zhang, B Nebgen, ... Chemical reviews 120 (4), 2215-2287, 2020 | 341 | 2020 |
The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules JS Smith, R Zubatyuk, B Nebgen, N Lubbers, K Barros, AE Roitberg, ... Scientific data 7 (1), 134, 2020 | 229 | 2020 |
Discovering a transferable charge assignment model using machine learning AE Sifain, N Lubbers, BT Nebgen, JS Smith, AY Lokhov, O Isayev, ... The journal of physical chemistry letters 9 (16), 4495-4501, 2018 | 131 | 2018 |
Transferable dynamic molecular charge assignment using deep neural networks B Nebgen, N Lubbers, JS Smith, AE Sifain, A Lokhov, O Isayev, ... Journal of chemical theory and computation 14 (9), 4687-4698, 2018 | 114 | 2018 |
Teaching a neural network to attach and detach electrons from molecules R Zubatyuk, JS Smith, BT Nebgen, S Tretiak, O Isayev Nature communications 12 (1), 4870, 2021 | 96 | 2021 |
Automated discovery of a robust interatomic potential for aluminum JS Smith, B Nebgen, N Mathew, J Chen, N Lubbers, L Burakovsky, ... Nature communications 12 (1), 1257, 2021 | 96 | 2021 |
Extending machine learning beyond interatomic potentials for predicting molecular properties N Fedik, R Zubatyuk, M Kulichenko, N Lubbers, JS Smith, B Nebgen, ... Nature Reviews Chemistry 6 (9), 653-672, 2022 | 91 | 2022 |
Dynamics of a myoglobin mutant enzyme: 2D IR vibrational echo experiments and simulations S Bagchi, BT Nebgen, RF Loring, MD Fayer Journal of the American Chemical Society 132 (51), 18367-18376, 2010 | 78 | 2010 |
NEXMD software package for nonadiabatic excited state molecular dynamics simulations W Malone, B Nebgen, A White, Y Zhang, H Song, JA Bjorgaard, AE Sifain, ... Journal of Chemical Theory and Computation 16 (9), 5771-5783, 2020 | 77 | 2020 |
The rise of neural networks for materials and chemical dynamics M Kulichenko, JS Smith, B Nebgen, YW Li, N Fedik, AI Boldyrev, ... The Journal of Physical Chemistry Letters 12 (26), 6227-6243, 2021 | 69 | 2021 |
Uncertainty-driven dynamics for active learning of interatomic potentials M Kulichenko, K Barros, N Lubbers, YW Li, R Messerly, S Tretiak, ... Nature Computational Science 3 (3), 230-239, 2023 | 58 | 2023 |
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential S Zhang, MZ Makoś, RB Jadrich, E Kraka, K Barros, BT Nebgen, S Tretiak, ... Nature Chemistry 16 (5), 727-734, 2024 | 49 | 2024 |
Photoexcited nonadiabatic dynamics of solvated push–pull π-conjugated oligomers with the NEXMD software AE Sifain, JA Bjorgaard, TR Nelson, BT Nebgen, AJ White, BJ Gifford, ... Journal of chemical theory and computation 14 (8), 3955-3966, 2018 | 46 | 2018 |
Machine learned Hückel theory: Interfacing physics and deep neural networks T Zubatiuk, B Nebgen, N Lubbers, JS Smith, R Zubatyuk, G Zhou, C Koh, ... The Journal of Chemical Physics 154 (24), 2021 | 42 | 2021 |
Graphics processing unit-accelerated semiempirical Born Oppenheimer molecular dynamics using PyTorch G Zhou, B Nebgen, N Lubbers, W Malone, AMN Niklasson, S Tretiak Journal of Chemical Theory and Computation 16 (8), 4951-4962, 2020 | 35 | 2020 |
Deep learning of dynamically responsive chemical Hamiltonians with semiempirical quantum mechanics G Zhou, N Lubbers, K Barros, S Tretiak, B Nebgen Proceedings of the National Academy of Sciences 119 (27), e2120333119, 2022 | 34 | 2022 |
Intermolecular conical intersections in molecular aggregates A De Sio, E Sommer, XT Nguyen, L Groß, D Popović, BT Nebgen, ... Nature Nanotechnology 16 (1), 63-68, 2021 | 33 | 2021 |
Vibronic coupling in asymmetric bichromophores: Theory and application to diphenylmethane B Nebgen, FL Emmert, LV Slipchenko The Journal of Chemical Physics 137 (8), 2012 | 29 | 2012 |