Jörg Behler
- Materials Chemistry top 0.1%
- Machine Learning in Materials Science 72
- X-ray Diffraction in Crystallography 14
- Phase-change materials and chalcogenides 13
- Electronic and Structural Properties of Oxides 12
- Computational Theory and Mathematics top 0.05%
- Computational Drug Discovery Methods 16
- Catalysis top 1%
-
- Advanced Chemical Physics Studies 29
- Spectroscopy and Quantum Chemical Studies 26
- Quantum, superfluid, helium dynamics 15
- Structural Biology top 1%
- Co-authors
- Michele ParrinelloNongnuch ArtrithChristoph DellagoTobias MorawietzAndreas SingraberMatti HellströmMarco BernasconiGábor Cśanyi
- Journals
- The Journal of Chemical Physics (17 papers)Physical Chemistry Chemical Physics (13 papers)Physical Review B (10 papers)
- Partner nations
- GermanySwitzerlandItaly
In The Last Decade
Jörg Behler
117 papers receiving 15.5k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Materials Chemistry 13.1k
- Computational Theory and Mathematics 3.5k
- Catalysis 980
- Atomic and Molecular Physics, and Optics 4.2k
- Structural Biology 187
Countries citing papers authored by Jörg Behler
This map shows the geographic impact of Jörg Behler's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jörg Behler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jörg Behler more than expected).
Fields of papers citing papers by Jörg Behler
This network shows the impact of papers produced by Jörg Behler. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jörg Behler. The network helps show where Jörg Behler may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jörg Behler, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 3 | |
| 4 | 2025 | 6 | |
| 5 | 2025 | 7 | |
| 6 | 2025 | 1 | |
| 7 | 2024 | 10 | |
| 8 | 2023 | 3 | |
| 9 | 2023 | 3 | |
| 10 | 2021 | 33 | |
| 11 | 2020 | 28 | |
| 12 | 2020 | 19 | |
| 13 | 2019 | 55 | |
| 14 | 2019 | 96 | |
| 15 | High-Dimensional Neural Network Potentials for Complex Systems | 2019 | 0 |
| 16 | 2019 | 23 | |
| 17 | 2019 | 7 | |
| 18 | 2018 | 18 | |
| 19 | 2017 | 129 | |
| 20 | Perspective: Machine learning potentials for atomistic simulationsbreakdown → | 2016 | 993 |
About Jörg Behler
Jörg Behler is a scholar working on Materials Chemistry, Catalysis and Atomic and Molecular Physics, and Optics, having authored 121 papers that have together received 15.7k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (72 papers), Advanced Chemical Physics Studies (29 papers), Spectroscopy and Quantum Chemical Studies (26 papers), Computational Drug Discovery Methods (16 papers), Quantum, superfluid, helium dynamics (15 papers), X-ray Diffraction in Crystallography (14 papers), Phase-change materials and chalcogenides (13 papers) and Electronic and Structural Properties of Oxides (12 papers). The work is most often cited by research in Materials Chemistry (13.1k citations), Computational Theory and Mathematics (3.5k citations) and Catalysis (980 citations). Jörg Behler has collaborated with scholars based in Germany, Switzerland and Italy. Frequent co-authors include Michele Parrinello, Nongnuch Artrith, Christoph Dellago, Tobias Morawietz, Andreas Singraber, Matti Hellström, Marco Bernasconi, Gábor Cśanyi, Karsten Reuter and Gabriele C. Sosso. Their work appears in journals such as The Journal of Chemical Physics, Physical Chemistry Chemical Physics, Physical Review B, The Journal of Physical Chemistry C and The Journal of Physical Chemistry Letters.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.