Eric Lindgren
Impact in
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- Machine Learning in Materials Science
- Thermal properties of materials
- Advanced Thermoelectric Materials and Devices
- Graphene research and applications
Papers in
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- Machine Learning in Materials Science 3
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- Lipid Membrane Structure and Behavior 1
- Co-authors
- Paul Erhart (6 shared papers)Zheyong Fan (3 shared papers)J. Magnus Rahm (2 shared papers)Zezhu Zeng (1 shared paper)Yue Chen (1 shared paper)Jian Sun (1 shared paper)Yanzhou Wang (1 shared paper)Junjie Wang (1 shared paper)
- Journals
- Computer Physics Communications (1 paper)Journal of the American Chemical Society (1 paper)Water Air & Soil Pollution (1 paper)Engineering Fracture Mechanics (1 paper)The Journal of Chemical Physics (1 paper)
- Partner nations
- SwedenUnited StatesUnited Kingdom
In The Last Decade
Eric Lindgren
7 papers receiving 295 citations
Eric Lindgren's Hit Papers
Peers
Comparison fields: 5 of 45
- Materials Chemistry 241
- Structural Biology 5
- Atomic and Molecular Physics, and Optics 59
- Metals and Alloys 4
- Ceramics and Composites 8
Countries citing papers authored by Eric Lindgren
This map shows the geographic impact of Eric Lindgren'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 Eric Lindgren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Lindgren more than expected).
Fields of papers citing papers by Eric Lindgren
This network shows the impact of papers produced by Eric Lindgren. 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 Eric Lindgren. The network helps show where Eric Lindgren may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric Lindgren, 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 | GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations Hit paper breakdown → | 2022 | 239 |
| 2 | 2024 | 20 | |
| 3 | 2024 | 19 | |
| 4 | 2024 | 16 | |
| 5 | 1995 | 3 | |
| 6 | 2025 | 1 | |
| 7 | 2025 | 1 | |
| 8 | 2025 | 0 |
About Eric Lindgren
Eric Lindgren is a scholar working on Materials Chemistry, Molecular Biology, Cognitive Neuroscience, Structural Biology and Civil and Structural Engineering, having authored 8 papers that have together received 299 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (3 papers), Neural dynamics and brain function (2 papers), Computational Drug Discovery Methods (1 paper), Lipid Membrane Structure and Behavior (1 paper), Neural Networks and Applications (1 paper), Strong Light-Matter Interactions (1 paper), Atmospheric chemistry and aerosols (1 paper) and Fault Detection and Control Systems (1 paper). The work is most often cited by research in Materials Chemistry (241 citations), Structural Biology (5 citations), Atomic and Molecular Physics, and Optics (59 citations), Metals and Alloys (4 citations) and Ceramics and Composites (8 citations). Eric Lindgren has collaborated with scholars based in Sweden, United States and United Kingdom. Frequent co-authors include Paul Erhart, Zheyong Fan, J. Magnus Rahm, Zezhu Zeng, Yue Chen, Jian Sun, Yanzhou Wang, Junjie Wang, Jianyang Wu and Keke Song. Their work appears in journals such as Computer Physics Communications, Journal of the American Chemical Society, Water Air & Soil Pollution, Engineering Fracture Mechanics and The Journal of Chemical Physics.
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.