Nicholas E. Charron
Impact in
- Geology top 5%
- 3D Surveying and Cultural Heritage
- Instrumentation top 10%
Papers in ⓘ
-
- Protein Structure and Dynamics 8
- Lipid Membrane Structure and Behavior 4
- Biochemical and Structural Characterization 2
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- Machine Learning in Materials Science 8
- Enzyme Structure and Function 4
- Co-authors
- Cecilia Clementi (7 shared papers)Frank Noé (7 shared papers)Simon Olsson (3 shared papers)Jiang Wang (3 shared papers)Adrià Pérez (3 shared papers)Gianni De Fabritiis (3 shared papers)Steven L. Waslander (3 shared papers)Stephen Phillips (2 shared papers)
- Journals
- Biophysical Journal (2 papers)Journal of Computing in Civil Engineering (1 paper)Journal of Structural Engineering (1 paper)The Journal of Physical Chemistry Letters (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Nicholas E. Charron
17 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Geology 77
- Instrumentation 39
- Microbiology 69
- Materials Chemistry 501
- Computational Theory and Mathematics 155
Countries citing papers authored by Nicholas E. Charron
This map shows the geographic impact of Nicholas E. Charron'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 Nicholas E. Charron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas E. Charron more than expected).
Fields of papers citing papers by Nicholas E. Charron
This network shows the impact of papers produced by Nicholas E. Charron. 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 Nicholas E. Charron. The network helps show where Nicholas E. Charron may publish in the future.
Co-authors
The 25 scholars most cited alongside Nicholas E. Charron, 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 | Machine Learning of Coarse-Grained Molecular Dynamics Force Fields Hit paper breakdown → | 2019 | 343 |
| 2 | 2018 | 122 | |
| 3 | 2020 | 121 | |
| 4 | 2020 | 63 | |
| 5 | 2023 | 62 | |
| 6 | 2022 | 58 | |
| 7 | 2017 | 53 | |
| 8 | 2023 | 47 | |
| 9 | 2021 | 41 | |
| 10 | 2019 | 41 | |
| 11 | 2018 | 34 | |
| 12 | 2016 | 31 | |
| 13 | 2023 | 20 | |
| 14 | 2023 | 19 | |
| 15 | 2022 | 13 | |
| 16 | 2019 | 10 | |
| 17 | 2019 | 1 | |
| 18 | 2025 | 0 |
About Nicholas E. Charron
Nicholas E. Charron is a scholar working on Molecular Biology, Materials Chemistry, Civil and Structural Engineering, Aerospace Engineering and Geology, having authored 18 papers that have together received 1.1k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (8 papers), Protein Structure and Dynamics (8 papers), Lipid Membrane Structure and Behavior (4 papers), Enzyme Structure and Function (4 papers), Robotics and Sensor-Based Localization (3 papers), Infrastructure Maintenance and Monitoring (3 papers), 3D Surveying and Cultural Heritage (3 papers) and Biochemical and Structural Characterization (2 papers). The work is most often cited by research in Geology (77 citations), Instrumentation (39 citations), Microbiology (69 citations), Materials Chemistry (501 citations) and Computational Theory and Mathematics (155 citations). Nicholas E. Charron has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Cecilia Clementi, Frank Noé, Simon Olsson, Jiang Wang, Adrià Pérez, Gianni De Fabritiis, Steven L. Waslander, Stephen Phillips, Christoph Wehmeyer and Huey W. Huang. Their work appears in journals such as Biophysical Journal, Journal of Computing in Civil Engineering, Journal of Structural Engineering, The Journal of Physical Chemistry Letters and Nature Communications.
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.