Simon Batzner
Impact in
- Materials Chemistry top 2%
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Electronic and Structural Properties of Oxides
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- Computational Drug Discovery Methods
Papers in ⓘ
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- Machine Learning in Materials Science 16
- X-ray Diffraction in Crystallography 3
- Electronic and Structural Properties of Oxides 1
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- Computational Drug Discovery Methods 3
- Co-authors
- Boris Kozinsky (11 shared papers)Albert Musaelian (9 shared papers)Lixin Sun (5 shared papers)Mordechai Kornbluth (2 shared papers)Nicola Molinari (2 shared papers)Mario Geiger (2 shared papers)Jonathan P. Mailoa (1 shared paper)Ekin D. Cubuk (5 shared papers)
- Journals
- Nature Communications (2 papers)Nature Computational Science (2 papers)Journal of the American Chemical Society (1 paper)ACS Omega (1 paper)npj Computational Materials (1 paper)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Simon Batzner
17 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Materials Chemistry 1.8k
- Computational Theory and Mathematics 527
- Catalysis 129
- Structural Biology 20
- Metals and Alloys 26
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 | 1022 |
| 2 | Scaling deep learning for materials discovery Hit paper breakdown → | 2023 | 667 |
| 3 | Learning local equivariant representations for large-scale atomistic dynamics Hit paper breakdown → | 2023 | 370 |
| 4 | The design space of E(3)-equivariant atom-centred interatomic potentials Hit paper breakdown → | 2025 | 61 |
| 5 | 2023 | 49 | |
| 6 | 2022 | 31 | |
| 7 | 2023 | 24 | |
| 8 | 2024 | 23 | |
| 9 | 2023 | 21 | |
| 10 | 2024 | 20 | |
| 11 | 2024 | 11 | |
| 12 | 2024 | 4 | |
| 13 | 2023 | 3 | |
| 14 | 2024 | 2 | |
| 15 | Accelerating atomistic modelling with active learning | 2019 | 1 |
| 16 | 2024 | 1 | |
| 17 | 2021 | 1 |
About Simon Batzner
Simon Batzner is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Electrochemistry, Catalysis and Industrial and Manufacturing Engineering, having authored 17 papers that have together received 2.3k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (16 papers), Protein Structure and Dynamics (7 papers), Computational Drug Discovery Methods (3 papers), Topic Modeling (3 papers), X-ray Diffraction in Crystallography (3 papers), Electronic and Structural Properties of Oxides (1 paper), Chemical Synthesis and Characterization (1 paper) and Advanced Chemical Physics Studies (1 paper). The work is most often cited by research in Materials Chemistry (1.8k citations), Computational Theory and Mathematics (527 citations), Catalysis (129 citations), Structural Biology (20 citations) and Metals and Alloys (26 citations). Simon Batzner has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Boris Kozinsky, Albert Musaelian, Lixin Sun, Mordechai Kornbluth, Nicola Molinari, Mario Geiger, Jonathan P. Mailoa, Ekin D. Cubuk, Tess Smidt and Amil Merchant. Their work appears in journals such as Nature Communications, Nature Computational Science, Journal of the American Chemical Society, ACS Omega and npj Computational Materials.
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.