James R. Kermode
- Materials Chemistry top 2%
- Atomic and Molecular Physics, and Optics top 5%
- Computational Theory and Mathematics top 1%
- Mechanical Engineering top 5%
- Metals and Alloys top 1%
- Co-authors
- Noam BernsteinAlessandro De VitaGábor CśanyiAlbert P. BartókZhenwei LiGábor CsányiCarl PoelkingMichele Ceriotti
- Topics
- Machine Learning in Materials Science (24 papers)X-ray Diffraction in Crystallography (9 papers)Computational Drug Discovery Methods (8 papers)
- Partner nations
- United KingdomUnited StatesFrance
In The Last Decade
James R. Kermode
54 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Materials Chemistry 2.3k
- Atomic and Molecular Physics, and Optics 490
- Computational Theory and Mathematics 480
- Mechanical Engineering 428
- Metals and Alloys 400
Countries citing papers authored by James R. Kermode
This map shows the geographic impact of James R. Kermode'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 James R. Kermode with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James R. Kermode more than expected).
Fields of papers citing papers by James R. Kermode
This network shows the impact of papers produced by James R. Kermode. 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 James R. Kermode. The network helps show where James R. Kermode may publish in the future.
Co-authorship network of co-authors of James R. Kermode
This figure shows the co-authorship network connecting the top 25 collaborators of James R. Kermode. A scholar is included among the top collaborators of James R. Kermode based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James R. Kermode. James R. Kermode is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 10 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 20 | |
| 8 | 28 | |
| 9 | 2 | |
| 10 | 37 | |
| 11 | 8 | |
| 12 | 41 | |
| 13 | Understanding and mitigating hydrogen embrittlement of steels: a review of experimental, modelling and design progress from atomistic to continuumbreakdown → | 337 |
| 14 | 8 | |
| 15 | 12 | |
| 16 | 61 | |
| 17 | 28 | |
| 18 | 24 | |
| 19 | 45 | |
| 20 | Multiscale modeling of defects in semiconductors : a novel molecular-dynamics scheme | 1 |
About James R. Kermode
James R. Kermode is a scholar working on Metals and Alloys, Ceramics and Composites and Materials Chemistry, having authored 54 papers that have together received 2.9k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (24 papers), X-ray Diffraction in Crystallography (9 papers) and Computational Drug Discovery Methods (8 papers). The work is most often cited by research in Metals and Alloys (400 citations), Materials Chemistry (2.3k citations) and Structural Biology (48 citations). James R. Kermode has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Noam Bernstein, Alessandro De Vita, Gábor Cśanyi, Albert P. Bartók, Zhenwei Li, Gábor Csányi, Carl Poelking, Michele Ceriotti, Sandip De and Peter Gumbsch. Their work appears in journals such as Nature, Physical Review Letters and Circulation.
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.