Simon Batzner
Impact in
- Materials Chemistry top 1%
- Machine Learning in Materials Science
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- Advanced Chemical Physics Studies
Papers in
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- Machine Learning in Materials Science 16
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- Advanced Physical and Chemical Molecular Interactions 2
- Co-authors
- Boris Kozinsky (12 shared papers)Lixin Sun (6 shared papers)Albert Musaelian (9 shared papers)Mordechai Kornbluth (2 shared papers)Ekin D. Cubuk (5 shared papers)Muratahan Aykol (4 shared papers)Amil Merchant (3 shared papers)Samuel S. Schoenholz (1 shared paper)
- Journals
- Nature Communications (2 papers)Nature Computational Science (2 papers)npj Computational Materials (2 papers)Journal of Chemical Theory and Computation (1 paper)The Journal of Chemical Physics (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Simon Batzner
17 papers receiving 3.5k citations
Simon Batzner's Hit Papers
Peers
Comparison fields: 5 of 95
- Materials Chemistry 2.7k
- Atomic and Molecular Physics, and Optics 422
- Computational Theory and Mathematics 194
- Physical and Theoretical Chemistry 123
- Catalysis 37
Countries citing papers authored by Simon Batzner
This map shows the geographic impact of Simon Batzner'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 Simon Batzner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Batzner more than expected).
Fields of papers citing papers by Simon Batzner
This network shows the impact of papers produced by Simon Batzner. 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 Simon Batzner. The network helps show where Simon Batzner may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Batzner, 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 | E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials Hit paper breakdown → | 2022 | 1361 |
| 2 | Scaling deep learning for materials discovery Hit paper breakdown → | 2023 | 940 |
| 3 | Learning local equivariant representations for large-scale atomistic dynamics Hit paper breakdown → | 2023 | 497 |
| 4 | On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events Hit paper breakdown → | 2020 | 381 |
| 5 | The design space of E(3)-equivariant atom-centred interatomic potentials Hit paper breakdown → | 2025 | 129 |
| 6 | 2023 | 63 | |
| 7 | 2023 | 40 | |
| 8 | 2022 | 35 | |
| 9 | 2024 | 30 | |
| 10 | 2024 | 27 | |
| 11 | 2023 | 26 | |
| 12 | 2024 | 18 | |
| 13 | 2024 | 8 | |
| 14 | 2023 | 4 | |
| 15 | 2024 | 4 | |
| 16 | 2024 | 2 | |
| 17 | Accelerating atomistic modelling with active learning | 2019 | 1 |
About Simon Batzner
Simon Batzner is a scholar working on Materials Chemistry, Physical and Theoretical Chemistry, Catalysis, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics, having authored 17 papers that have together received 3.6k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (16 papers), Advanced Physical and Chemical Molecular Interactions (2 papers), Advanced Chemical Physics Studies (2 papers), Ionic liquids properties and applications (1 paper), Model Reduction and Neural Networks (1 paper), Protein Structure and Dynamics (1 paper) and Computational Drug Discovery Methods (1 paper). The work is most often cited by research in Materials Chemistry (2.7k citations), Atomic and Molecular Physics, and Optics (422 citations), Computational Theory and Mathematics (194 citations), Physical and Theoretical Chemistry (123 citations) and Catalysis (37 citations). Simon Batzner has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Boris Kozinsky, Lixin Sun, Albert Musaelian, Mordechai Kornbluth, Ekin D. Cubuk, Muratahan Aykol, Amil Merchant, Samuel S. Schoenholz, Gowoon Cheon and Nicola Molinari. Their work appears in journals such as Nature Communications, Nature Computational Science, npj Computational Materials, Journal of Chemical Theory and Computation and The Journal of Chemical Physics.
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.