Stephen J. DeWitt
Impact in
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- Solidification and crystal growth phenomena
- Machine Learning in Materials Science
- Microstructure and mechanical properties
Papers in
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- Solidification and crystal growth phenomena 11
- Machine Learning in Materials Science 3
- Anodic Oxide Films and Nanostructures 3
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- Magnesium Alloys: Properties and Applications 4
- Co-authors
- Katsuyo S. Thornton (10 shared papers)Shiva Rudraraju (2 shared papers)David Montiel (2 shared papers)Balasubramaniam Radhakrishnan (5 shared papers)George Biros (3 shared papers)Raúl A. Enrique (1 shared paper)Nathan T. Hahn (1 shared paper)Kevin R. Zavadil (1 shared paper)
- Journals
- Computational Materials Science (4 papers)MRS Communications (2 papers)Journal of The Electrochemical Society (2 papers)The International Journal of High Performance Computing Applications (1 paper)Acta Materialia (1 paper)
- Partner nations
- United StatesGermanyIndia
In The Last Decade
Stephen J. DeWitt
22 papers receiving 379 citations
Peers
Comparison fields: 5 of 36
- Metals and Alloys 11
- Materials Chemistry 172
- Biomaterials 50
- Mechanical Engineering 78
- Statistical and Nonlinear Physics 16
Countries citing papers authored by Stephen J. DeWitt
This map shows the geographic impact of Stephen J. DeWitt'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 Stephen J. DeWitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen J. DeWitt more than expected).
Fields of papers citing papers by Stephen J. DeWitt
This network shows the impact of papers produced by Stephen J. DeWitt. 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 Stephen J. DeWitt. The network helps show where Stephen J. DeWitt may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephen J. DeWitt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 57 | |
| 2 | 2017 | 42 | |
| 3 | 2018 | 36 | |
| 4 | 2022 | 34 | |
| 5 | 2015 | 32 | |
| 6 | 2017 | 32 | |
| 7 | 2016 | 27 | |
| 8 | 2022 | 21 | |
| 9 | 2022 | 14 | |
| 10 | 2024 | 14 | |
| 11 | 2019 | 12 | |
| 12 | 2014 | 11 | |
| 13 | 2022 | 11 | |
| 14 | 2017 | 10 | |
| 15 | 2025 | 8 | |
| 16 | 2023 | 7 | |
| 17 | 2016 | 6 | |
| 18 | 2024 | 4 | |
| 19 | 2015 | 2 | |
| 20 | 2024 | 2 |
About Stephen J. DeWitt
Stephen J. DeWitt is a scholar working on Materials Chemistry, Biomaterials, Information Systems and Management, Mechanical Engineering and Statistical and Nonlinear Physics, having authored 26 papers that have together received 385 indexed citations. Recurring topics across this work include Solidification and crystal growth phenomena (11 papers), Additive Manufacturing Materials and Processes (5 papers), Magnesium Alloys: Properties and Applications (4 papers), Machine Learning in Materials Science (3 papers), Anodic Oxide Films and Nanostructures (3 papers), Scientific Computing and Data Management (3 papers), Electrodeposition and Electroless Coatings (2 papers) and Model Reduction and Neural Networks (2 papers). The work is most often cited by research in Metals and Alloys (11 citations), Materials Chemistry (172 citations), Biomaterials (50 citations), Mechanical Engineering (78 citations) and Statistical and Nonlinear Physics (16 citations). Stephen J. DeWitt has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Katsuyo S. Thornton, Shiva Rudraraju, David Montiel, Balasubramaniam Radhakrishnan, George Biros, Raúl A. Enrique, Nathan T. Hahn, Kevin R. Zavadil, Larry K. Aagesen and Donald J. Siegel. Their work appears in journals such as Computational Materials Science, MRS Communications, Journal of The Electrochemical Society, The International Journal of High Performance Computing Applications and Acta Materialia.
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.