litlas
Log inCreate account

Jörg Behler

Active 2005–2025

43
Papers
18,820
Citations
36
h-index
39
i10-index

Citations

Citations per year for Jörg Behler1968: 1 citations1998: 1 citations2005: 1 citations2006: 5 citations2007: 3 citations2008: 4 citations2009: 7 citations2010: 9 citations2011: 21 citations2012: 31 citations2013: 39 citations2014: 44 citations2015: 51 citations2016: 117 citations2017: 188 citations2018: 283 citations2019: 483 citations2020: 773 citations2021: 764 citations2022: 592 citations2023: 636 citations2024: 734 citations2025: 539 citations2026: 92 citations1969–1997: no citations, so these years are not shown1999–2004: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 941 citing papers, 27% of this breakdownChina: 436 citing papers, 12.5% of this breakdownGermany: 338 citing papers, 9.7% of this breakdownUnited Kingdom: 278 citing papers, 8% of this breakdownSwitzerland: 207 citing papers, 5.9% of this breakdownJapan: 115 citing papers, 3.3% of this breakdownCanada: 105 citing papers, 3% of this breakdownFrance: 98 citing papers, 2.8% of this breakdownSouth Korea: 92 citing papers, 2.6% of this breakdownAustria: 82 citing papers, 2.4% of this breakdownItaly: 82 citing papers, 2.4% of this breakdownSpain: 54 citing papers, 1.6% of this breakdown
0%27%Other 18.8%

Institutions

Fields

  • Materials Science71.3%
  • Computer Science10.4%
  • Physics and Astronomy5%
  • Biochemistry, Genetics and Molecular Biology4.6%
  • Engineering3.5%
  • Chemistry1.7%
  • Other3.5%

Topics

  • Machine Learning in Materials Science27%
  • Computational Drug Discovery Methods17%
  • Protein Structure and Dynamics9.3%
  • X-ray Diffraction in Crystallography3.4%
  • Advanced Chemical Physics Studies2.8%
  • Spectroscopy and Quantum Chemical Studies2%
  • Other38.5%

Coauthors

All papers

Open in search
  1. Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces

    Authors: Jörg Behler, Michele Parrinello - Physical Review Letters 2007 cited by 4,950

  2. Four Generations of High-Dimensional Neural Network Potentials

    Authors: Jörg Behler - Chemical Reviews 2021 cited by 856

  3. Atom-centered symmetry functions for constructing high-dimensional neural network potentials

    Authors: Jörg Behler - The Journal of Chemical Physics 2011 cited by 1,620

  4. Perspective: Machine learning potentials for atomistic simulations

    Authors: Jörg Behler - The Journal of Chemical Physics 2016 cited by 1,495

  5. A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer

    Authors: Tsz Wai Ko, Jonas A. Finkler, Stefan Goedecker, Jörg Behler - Nature Communications 2021 cited by 503

  6. Constructing high‐dimensional neural network potentials: A tutorial review

    Authors: Jörg Behler - International Journal of Quantum Chemistry 2015 cited by 879

  7. Machine learning molecular dynamics for the simulation of infrared spectra

    Authors: Michael Gastegger, Jörg Behler, Philipp Marquetand - Chemical Science 2017 cited by 512

  8. Performance and Cost Assessment of Machine Learning Interatomic Potentials

    Authors: Yunxing Zuo, Chi Chen, Xiangguo Li, Zhi Deng, Yiming Chen, Jörg Behler, Gábor Cśanyi, Alexander V. Shapeev, Aidan P. Thompson, Mitchell Wood, Shyue Ping Ong - The Journal of Physical Chemistry A 2020 cited by 927

  9. First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems

    Authors: Jörg Behler - Angewandte Chemie International Edition 2017 cited by 733

  10. Machine learning potentials for extended systems: a perspective

    Authors: Jörg Behler, Gábor Cśanyi - The European Physical Journal B 2021 cited by 219

  11. Representing potential energy surfaces by high-dimensional neural network potentials

    Authors: Jörg Behler - Journal of Physics Condensed Matter 2014 cited by 410

  12. Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

    Authors: Jörg Behler - Physical Chemistry Chemical Physics 2011 cited by 815

  13. Ab initio thermodynamics of liquid and solid water

    Authors: Bingqing Cheng, Edgar A. Engel, Jörg Behler, Christoph Dellago, Michele Ceriotti - National Academy of Sciences, Proceedings of the National Academy of Sciences 2019 cited by 363

  14. High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide

    Authors: Nongnuch Artrith, Tobias Morawietz, Jörg Behler - Physical Review B 2011 cited by 410

  15. How van der Waals interactions determine the unique properties of water

    Authors: Tobias Morawietz, Andreas Singraber, Christoph Dellago, Jörg Behler - National Academy of Sciences, Proceedings of the National Academy of Sciences 2016 cited by 499

  16. Library-Based LAMMPS Implementation of High-Dimensional Neural Network Potentials

    Authors: Andreas Singraber, Jörg Behler, Christoph Dellago - Journal of Chemical Theory and Computation 2019 cited by 295

  17. High-dimensional neural network potentials for metal surfaces: A prototype study for copper

    Authors: Nongnuch Artrith, Jörg Behler - Physical Review B 2012 cited by 340

  18. Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

    Authors: Giulio Imbalzano, Andrea Anelli, Daniele Giofré, Sinja Klees, Jörg Behler, Michele Ceriotti - The Journal of Chemical Physics 2018 cited by 301

  19. General-Purpose Machine Learning Potentials Capturing Nonlocal Charge Transfer

    Authors: Tsz Wai Ko, Jonas A. Finkler, Stefan Goedecker, Jörg Behler - Accounts of Chemical Research 2021 cited by 136

  20. Parallel Multistream Training of High-Dimensional Neural Network Potentials

    Authors: Andreas Singraber, Tobias Morawietz, Jörg Behler, Christoph Dellago - Journal of Chemical Theory and Computation 2019 cited by 228

  21. Accurate Fourth-Generation Machine Learning Potentials by Electrostatic Embedding

    Authors: Tsz Wai Ko, Jonas A. Finkler, Stefan Goedecker, Jörg Behler - Journal of Chemical Theory and Computation 2023 cited by 47

  22. Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground

    Authors: Christoph Schran, Jörg Behler, Dominik Marx - Journal of Chemical Theory and Computation 2019 cited by 136

  23. Neural network molecular dynamics simulations of solid–liquid interfaces: water at low-index copper surfaces

    Authors: Suresh Kondati Natarajan, Jörg Behler - Physical Chemistry Chemical Physics 2016 cited by 216

  24. A Density-Functional Theory-Based Neural Network Potential for Water Clusters Including van der Waals Corrections

    Authors: Tobias Morawietz, Jörg Behler - The Journal of Physical Chemistry A 2013 cited by 208