John E. Herr
Impact in
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- Computational Drug Discovery Methods
- Materials Chemistry top 5%
- Machine Learning in Materials Science
- Quantum Dots Synthesis And Properties
- Solid-state spectroscopy and crystallography
- X-ray Diffraction in Crystallography
Papers in
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- Machine Learning in Materials Science 7
- X-ray Diffraction in Crystallography 2
- Solid-state spectroscopy and crystallography 1
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- Computational Drug Discovery Methods 7
- Co-authors
- John Parkhill (6 shared papers)Kun Yao (5 shared papers)Sergei Rouvimov (1 shared paper)Michael C. Brennan (1 shared paper)Masaru Kuno (1 shared paper)Jessica Zinna (1 shared paper)Sergiu Draguta (1 shared paper)Seth N. Brown (1 shared paper)
- Journals
- The Journal of Chemical Physics (2 papers)Chemical Science (2 papers)Scientific Data (1 paper)Journal of the American Chemical Society (1 paper)Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine (1 paper)
- Partner nations
- United StatesUnited KingdomSweden
In The Last Decade
John E. Herr
9 papers receiving 1.0k citations
John E. Herr's Hit Papers
Peers
Comparison fields: 5 of 64
- Computational Theory and Mathematics 375
- Materials Chemistry 901
- Physical and Theoretical Chemistry 72
- Atomic and Molecular Physics, and Optics 201
- Electrical and Electronic Engineering 331
Countries citing papers authored by John E. Herr
This map shows the geographic impact of John E. Herr'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 John E. Herr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John E. Herr more than expected).
Fields of papers citing papers by John E. Herr
This network shows the impact of papers produced by John E. Herr. 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 John E. Herr. The network helps show where John E. Herr may publish in the future.
Co-authors
The 25 scholars most cited alongside John E. Herr, 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 | The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics Hit paper breakdown → | 2018 | 369 |
| 2 | 2017 | 293 | |
| 3 | SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials Hit paper breakdown → | 2023 | 119 |
| 4 | 2017 | 104 | |
| 5 | 2023 | 88 | |
| 6 | 2018 | 54 | |
| 7 | 2018 | 19 | |
| 8 | 2019 | 7 | |
| 9 | 1989 | 3 |
About John E. Herr
John E. Herr is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Molecular Biology, Surgery and Physical and Theoretical Chemistry, having authored 9 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (7 papers), Protein Structure and Dynamics (3 papers), X-ray Diffraction in Crystallography (2 papers), Perovskite Materials and Applications (1 paper), Orthopedic Surgery and Rehabilitation (1 paper), Solid-state spectroscopy and crystallography (1 paper) and Metabolomics and Mass Spectrometry Studies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (375 citations), Materials Chemistry (901 citations), Physical and Theoretical Chemistry (72 citations), Atomic and Molecular Physics, and Optics (201 citations) and Electrical and Electronic Engineering (331 citations). John E. Herr has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include John Parkhill, Kun Yao, Sergei Rouvimov, Michael C. Brennan, Masaru Kuno, Jessica Zinna, Sergiu Draguta, Seth N. Brown, Yuanqing Wang and David Dotson. Their work appears in journals such as The Journal of Chemical Physics, Chemical Science, Scientific Data, Journal of the American Chemical Society and Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine.
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.