| Embedded atom neural network potentials: Efficient and accurate machine learning with a physically inspired representation Y Zhang, C Hu, B Jiang The journal of physical chemistry letters 10 (17), 4962-4967, 2019 | 200 | 2019 |
| Constructing high-dimensional neural network potential energy surfaces for gas–surface scattering and reactions Q Liu, X Zhou, L Zhou, Y Zhang, X Luo, H Guo, B Jiang The Journal of Physical Chemistry C 122 (3), 1761-1769, 2018 | 89 | 2018 |
| Bridging the gap between direct dynamics and globally accurate reactive potential energy surfaces using neural networks Y Zhang, X Zhou, B Jiang The Journal of Physical Chemistry Letters 10 (6), 1185-1191, 2019 | 73 | 2019 |
| Efficient and accurate simulations of vibrational and electronic spectra with symmetry-preserving neural network models for tensorial properties Y Zhang, S Ye, J Zhang, C Hu, J Jiang, B Jiang The Journal of Physical Chemistry B 124 (33), 7284-7290, 2020 | 63 | 2020 |
| Physically Motivated Recursively Embedded Atom Neural Networks: Incorporating Local Completeness and Nonlocality Y Zhang, J Xia, B Jiang PHYSICAL REVIEW LETTERS 127 (15), 156002, 2021 | 50 | 2021 |
| Searching configurations in uncertainty space: Active learning of high-dimensional neural network reactive potentials Q Lin, L Zhang, Y Zhang, B Jiang Journal of Chemical Theory and Computation 17 (5), 2691-2701, 2021 | 50 | 2021 |
| Automatically growing global reactive neural network potential energy surfaces: A trajectory-free active learning strategy Q Lin, Y Zhang, B Zhao, B Jiang The Journal of Chemical Physics 152 (15), 2020 | 50 | 2020 |
| Symmetry-adapted high dimensional neural network representation of electronic friction tensor of adsorbates on metals Y Zhang, RJ Maurer, B Jiang The Journal of Physical Chemistry C 124 (1), 186-195, 2019 | 48 | 2019 |
| Dissociative Chemisorption of O2 on Al(111): Dynamics on a Correlated Wave-Function-Based Potential Energy Surface R Yin, Y Zhang, F Libisch, EA Carter, H Guo, B Jiang The journal of physical chemistry letters 9 (12), 3271-3277, 2018 | 46 | 2018 |
| Unified and transferable description of dynamics of H 2 dissociative adsorption on multiple copper surfaces via machine learning L Zhu, Y Zhang, L Zhang, X Zhou, B Jiang Physical Chemistry Chemical Physics 22 (25), 13958-13964, 2020 | 43 | 2020 |
| Strong vibrational relaxation of NO scattered from Au (111): Importance of the adiabatic potential energy surface R Yin, Y Zhang, B Jiang The Journal of Physical Chemistry Letters 10 (19), 5969-5974, 2019 | 41 | 2019 |
| Dissociative chemisorption of methane on Ni (111) using a chemically accurate fifteen dimensional potential energy surface X Zhou, F Nattino, Y Zhang, J Chen, GJ Kroes, H Guo, B Jiang Physical Chemistry Chemical Physics 19 (45), 30540-30550, 2017 | 41 | 2017 |
| Hot-electron effects during reactive scattering of H 2 from Ag (111): the interplay between mode-specific electronic friction and the potential energy landscape Y Zhang, RJ Maurer, H Guo, B Jiang Chemical science 10 (4), 1089-1097, 2019 | 40 | 2019 |
| New Perspectives on CO2–Pt(111) Interaction with a High-Dimensional Neural Network Potential Energy Surface M del Cueto, X Zhou, L Zhou, Y Zhang, B Jiang, H Guo The Journal of Physical Chemistry C 124 (9), 5174-5181, 2020 | 39 | 2020 |
| Vibrational control of selective bond cleavage in dissociative chemisorption of methanol on Cu (111) J Chen, X Zhou, Y Zhang, B Jiang Nature communications 9 (1), 4039, 2018 | 38 | 2018 |
| Determining the effect of hot electron dissipation on molecular scattering experiments at metal surfaces CL Box, Y Zhang, R Yin, B Jiang, RJ Maurer JACS Au 1 (2), 164-173, 2020 | 37 | 2020 |
| Towards bridging the structure gap in heterogeneous catalysis: the impact of defects in dissociative chemisorption of methane on Ir surfaces X Zhou, Y Zhang, H Guo, B Jiang Physical Chemistry Chemical Physics 23 (7), 4376-4385, 2021 | 33 | 2021 |
| Accelerating atomistic simulations with piecewise machine-learned ab Initio potentials at a classical force field-like cost Y Zhang, C Hu, B Jiang Physical Chemistry Chemical Physics 23 (3), 1815-1821, 2021 | 33 | 2021 |
| REANN: A PyTorch-based End-to-End Multi-functional Deep Neural Network Package for Molecular, Reactive and Periodic Systems Y Zhang, J Xia, B Jiang arXiv preprint arXiv:2112.01774, 2021 | 29 | 2021 |
| Efficient construction of excited-state Hessian matrices with machine learning accelerated multilayer energy-based fragment method WK Chen, Y Zhang, B Jiang, WH Fang, G Cui The Journal of Physical Chemistry A 124 (27), 5684-5695, 2020 | 27 | 2020 |
