Jonathan Vandermause
Impact in
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- Machine Learning in Materials Science
- Catalytic Processes in Materials Science
- X-ray Diffraction in Crystallography
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- Catalysis and Oxidation Reactions
Papers in
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- Machine Learning in Materials Science 7
- Nuclear Materials and Properties 1
- Electronic and Structural Properties of Oxides 1
- Catalytic Processes in Materials Science 1
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- Protein Structure and Dynamics 4
- Co-authors
- Boris Kozinsky (7 shared papers)Yu Xie (3 shared papers)Jin Soo Lim (2 shared papers)Cameron J. Owen (1 shared paper)Cheol Woo Park (1 shared paper)Mordechai Kornbluth (1 shared paper)Chris Wolverton (1 shared paper)Jonathan P. Mailoa (1 shared paper)
- Journals
- npj Computational Materials (3 papers)Nature Communications (1 paper)Journal of the American Chemical Society (1 paper)Physical review. A (1 paper)Journal of Chemical Theory and Computation (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Jonathan Vandermause
8 papers receiving 369 citations
Peers
Comparison fields: 5 of 47
- Materials Chemistry 301
- Catalysis 38
- Computational Theory and Mathematics 78
- Renewable Energy, Sustainability and the Environment 41
- Structural Biology 3
Countries citing papers authored by Jonathan Vandermause
This map shows the geographic impact of Jonathan Vandermause'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 Jonathan Vandermause with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Vandermause more than expected).
Fields of papers citing papers by Jonathan Vandermause
This network shows the impact of papers produced by Jonathan Vandermause. 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 Jonathan Vandermause. The network helps show where Jonathan Vandermause may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan Vandermause, 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 | 2021 | 114 | |
| 2 | 2022 | 106 | |
| 3 | 2020 | 59 | |
| 4 | 2023 | 46 | |
| 5 | 2022 | 32 | |
| 6 | 2024 | 10 | |
| 7 | 2016 | 6 | |
| 8 | Accelerating atomistic modelling with active learning | 2019 | 1 |
About Jonathan Vandermause
Jonathan Vandermause is a scholar working on Materials Chemistry, Molecular Biology, Atomic and Molecular Physics, and Optics, Artificial Intelligence and Computational Theory and Mathematics, having authored 8 papers that have together received 374 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (7 papers), Protein Structure and Dynamics (4 papers), Advanced Materials Characterization Techniques (1 paper), Nuclear Materials and Properties (1 paper), Electronic and Structural Properties of Oxides (1 paper), Catalytic Processes in Materials Science (1 paper), Fuel Cells and Related Materials (1 paper) and Quantum Information and Cryptography (1 paper). The work is most often cited by research in Materials Chemistry (301 citations), Catalysis (38 citations), Computational Theory and Mathematics (78 citations), Renewable Energy, Sustainability and the Environment (41 citations) and Structural Biology (3 citations). Jonathan Vandermause has collaborated with scholars based in United States and Germany. Frequent co-authors include Boris Kozinsky, Yu Xie, Jin Soo Lim, Cameron J. Owen, Cheol Woo Park, Mordechai Kornbluth, Chris Wolverton, Jonathan P. Mailoa, Lixin Sun and Nakib H. Protik. Their work appears in journals such as npj Computational Materials, Nature Communications, Journal of the American Chemical Society, Physical review. A and Journal of Chemical Theory and Computation.
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.