Rhys E. A. Goodall
Impact in
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- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Electronic and Structural Properties of Oxides
- Advanced Thermoelectric Materials and Devices
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- Computational Drug Discovery Methods
Papers in
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- Machine Learning in Materials Science 7
- X-ray Diffraction in Crystallography 5
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- Computational Drug Discovery Methods 3
- Co-authors
- Alpha A. Lee (7 shared papers)Felix A. Faber (2 shared papers)Rickard Armiento (2 shared papers)Janosh Riebesell (4 shared papers)Mark Asta (2 shared papers)Philipp Benner (2 shared papers)Yuan Chiang (2 shared papers)Gerbrand Ceder (3 shared papers)
- Journals
- Nature Machine Intelligence (2 papers)Nature Communications (1 paper)Physical Review Materials (1 paper)Chemistry of Materials (1 paper)Journal of The Electrochemical Society (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Rhys E. A. Goodall
11 papers receiving 398 citations
Rhys E. A. Goodall's Hit Papers
Peers
Comparison fields: 5 of 53
- Materials Chemistry 333
- Computational Theory and Mathematics 83
- Catalysis 26
- Metals and Alloys 6
- Automotive Engineering 23
Countries citing papers authored by Rhys E. A. Goodall
This map shows the geographic impact of Rhys E. A. Goodall'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 Rhys E. A. Goodall with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rhys E. A. Goodall more than expected).
Fields of papers citing papers by Rhys E. A. Goodall
This network shows the impact of papers produced by Rhys E. A. Goodall. 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 Rhys E. A. Goodall. The network helps show where Rhys E. A. Goodall may publish in the future.
Co-authors
The 19 scholars most cited alongside Rhys E. A. Goodall, 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 | 2020 | 249 | |
| 2 | A framework to evaluate machine learning crystal stability predictions Hit paper breakdown → | 2025 | 48 |
| 3 | 2022 | 39 | |
| 4 | 2023 | 32 | |
| 5 | 2021 | 14 | |
| 6 | 2021 | 10 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 3 | |
| 9 | 2025 | 3 | |
| 10 | 2020 | 2 | |
| 11 | 2025 | 1 |
About Rhys E. A. Goodall
Rhys E. A. Goodall is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Biomedical Engineering, Automotive Engineering and Atomic and Molecular Physics, and Optics, having authored 11 papers that have together received 405 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (7 papers), X-ray Diffraction in Crystallography (5 papers), Computational Drug Discovery Methods (3 papers), Surface Chemistry and Catalysis (2 papers), Advanced Battery Technologies Research (1 paper), Fuel Cells and Related Materials (1 paper), Quantum many-body systems (1 paper) and Advancements in Battery Materials (1 paper). The work is most often cited by research in Materials Chemistry (333 citations), Computational Theory and Mathematics (83 citations), Catalysis (26 citations), Metals and Alloys (6 citations) and Automotive Engineering (23 citations). Rhys E. A. Goodall has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Alpha A. Lee, Felix A. Faber, Rickard Armiento, Janosh Riebesell, Mark Asta, Philipp Benner, Yuan Chiang, Gerbrand Ceder, Bowen Deng and Kristin A. Persson. Their work appears in journals such as Nature Machine Intelligence, Nature Communications, Physical Review Materials, Chemistry of Materials and Journal of The Electrochemical Society.
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.