Jörg Behler

Health Research Alliance — United States

Materials Science · Physical Sciences

59h-index21.7kcitations203works7.82yr avg
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Research Topics

Machine Learning in Materials Science(112), Advanced Chemical Physics Studies(39), Spectroscopy and Quantum Chemical Studies(32), Computational Drug Discovery Methods(28), X-ray Diffraction in Crystallography(24)

Publications203 total

Molecular Dynamics Simulations of $γ$-Belite(010)-Water Interfaces with High-Dimensional Neural Network Potentials
arXiv (Cornell University)·2025Open Access
Insights into the Structure and Dynamics of Water at Co3O4${\rm Co}_3{\rm O}_4$(001) Using a High‐Dimensional Neural Network Potential
ChemCatChem·2025· 2 citedOpen Access
Long-Range Interactions in High-Dimensional Neural Network Potentials: A Benchmark Study for Small Organic Molecules
The Journal of Physical Chemistry B·2025
Computation of the heat capacity of water from first principles
The Journal of Chemical Physics·2025
Atomistic simulations of oxide–water interfaces using machine learning potentials
Chemical Physics Reviews·2025· 1 citedOpen Access
Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential
arXiv (Cornell University)·2025Open Access
Long-Range Interactions in High-Dimensional Neural Network Potentials: A Benchmark Study for Small Organic Molecules
2025
Impact of the damping function in dispersion-corrected density functional theory on the properties of liquid water
The Journal of Chemical Physics·2025· 3 citedOpen Access
Impact of the damping function in dispersion-corrected density functional theory on the properties of liquid water
arXiv (Cornell University)·2025Open Access
Free energy profiles for chemical reactions in solution from high-dimensional neural network potentials: The case of the Strecker synthesis
The Journal of Chemical Physics·2025· 2 citedOpen Access
Iterative charge equilibration for fourth-generation high-dimensional neural network potentials
The Journal of Chemical Physics·2025· 7 cited
Accuracy of charge densities in electronic structure calculations
The Journal of Chemical Physics·2025· 11 citedOpen Access
Iterative charge equilibration for fourth-generation high-dimensional neural network potentials
arXiv (Cornell University)·2025Open Access
Machine Learning Potentials for Heterogeneous Catalysis
ACS Catalysis·2025· 53 citedOpen Access
Random Sampling Versus Active Learning Algorithms for Machine Learning Potentials of Quantum Liquid Water
Journal of Chemical Theory and Computation·2025· 9 cited
Roadmap on Advancements of the FHI-aims Software Package
JuSER Publikationsportal·2025Open Access
A high-dimensional neural network potential for Co<sub>3</sub>O<sub>4</sub>
Journal of Physics Condensed Matter·2024· 4 citedOpen Access
Roadmap for the development of machine learning-based interatomic potentials
Modelling and Simulation in Materials Science and Engineering·2024· 35 citedOpen Access
Nuclear Quantum Effects in Liquid Water Are Marginal for Its Average Structure but Significant for Dynamics
The Journal of Physical Chemistry Letters·2024· 19 cited
From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows
npj Computational Materials·2024· 17 citedOpen Access
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Frequent Co-authors

Michele Parrinello(5), Karsten Reuter(5), Matthias Scheffler(5), Tobias Morawietz(4), Christoph Dellago(4), Nongnuch Artrith(4), Michele Ceriotti(4), Gabriele C. Sosso(4), S. Caravati(4), Marco Bernasconi(4), Matti Hellström(4), Gábor Cśanyi(3), Andreas Singraber(3), Davide Donadio(3), Tsz Wai Ko(2), Jonas A. Finkler(2), Stefan Goedecker(2), Tobias Morawietz(2), Bingqing Cheng(2), B. Delley(2)