Jörg Behler
Affiliations: | Georg-August-Universität Göttingen, Göttingen, Niedersachsen, Germany |
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Parents
Sign in to add mentor| Karsten Reuter | grad student | 2000-2004 | Fritz Haber Institute of the Max Planck Society (Physics Tree) |
| Matthias Scheffler | grad student | 2000-2004 | Fritz Haber Institute (Physics Tree) |
| Michele Parrinello | post-doc | 2005-2007 | ETH Zürich |
| Dominik Marx | post-doc | 2007-2008 | Ruhr-Universität Bochum |
Children
Sign in to add trainee| Nongnuch Artrith | grad student | ||
| Tobias Morawietz | grad student | Ruhr University–Bochum, Bochum, German |
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Publications
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| Kocer E, Ko TW, Behler J. (2022) Neural Network Potentials: A Concise Overview of Methods. Annual Review of Physical Chemistry. 73: 163-186 |
| Eckhoff M, Behler J. (2022) Insights into lithium manganese oxide-water interfaces using machine learning potentials. The Journal of Chemical Physics. 155: 244703 |
| Behler J. (2021) Four Generations of High-Dimensional Neural Network Potentials. Chemical Reviews |
| Ko TW, Finkler JA, Goedecker S, et al. (2021) General-Purpose Machine Learning Potentials Capturing Nonlocal Charge Transfer. Accounts of Chemical Research |
| Ko TW, Finkler JA, Goedecker S, et al. (2021) A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer. Nature Communications. 12: 398 |
| Wille S, Jiang H, Bünermann O, et al. (2020) An experimentally validated neural-network potential energy surface for H-atom on free-standing graphene in full dimensionality. Physical Chemistry Chemical Physics : Pccp |
| Ghorbanfekr H, Behler J, Peeters FM. (2020) Insights into Water Permeation through hBN Nanocapillaries by Ab Initio Machine Learning Molecular Dynamics Simulations. The Journal of Physical Chemistry Letters |
| Paleico ML, Behler J. (2020) Global optimization of copper clusters at the ZnO(101¯0) surface using a DFT-based neural network potential and genetic algorithms. The Journal of Chemical Physics. 153: 054704 |
| Lu D, Behler J, Li J. (2020) Accurate Global Potential Energy Surfaces for the H + CHOH Reaction by Neural Network Fitting with Permutation Invariance. The Journal of Physical Chemistry. A |
| Zuo Y, Chen C, Li XG, et al. (2020) A Performance and Cost Assessment of Machine Learning Interatomic Potentials. The Journal of Physical Chemistry. A |