Changwon Suh
- Electrical and Electronic Engineering top 2%
- Renewable Energy, Sustainability and the Environment top 2%
- Materials Chemistry top 10%
- Automotive Engineering top 2%
- Electronic, Optical and Magnetic Materials top 10%
- Co-authors
- Alán Aspuru‐GuzikSüleyman ErMichael P. MarshakCooper J. GalvinMichael R. GerhardtXudong ChenBrian HuskinsonMichael J. Aziz
- Topics
- Machine Learning in Materials Science (12 papers)Computational Drug Discovery Methods (8 papers)Membrane Separation Technologies (8 papers)
- Partner nations
- United StatesSouth KoreaJapan
In The Last Decade
Changwon Suh
40 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Electrical and Electronic Engineering 1.7k
- Renewable Energy, Sustainability and the Environment 697
- Materials Chemistry 669
- Automotive Engineering 496
- Electronic, Optical and Magnetic Materials 363
Countries citing papers authored by Changwon Suh
This map shows the geographic impact of Changwon Suh'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 Changwon Suh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Changwon Suh more than expected).
Fields of papers citing papers by Changwon Suh
This network shows the impact of papers produced by Changwon Suh. 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 Changwon Suh. The network helps show where Changwon Suh may publish in the future.
Co-authorship network of co-authors of Changwon Suh
This figure shows the co-authorship network connecting the top 25 collaborators of Changwon Suh. A scholar is included among the top collaborators of Changwon Suh 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 Changwon Suh. Changwon Suh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 19 | |
| 3 | 27 | |
| 4 | 31 | |
| 5 | 65 | |
| 6 | 25 | |
| 7 | 22 | |
| 8 | A metal-free organic–inorganic aqueous flow batterybreakdown → | 1301 |
| 9 | 29 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | 1 | |
| 13 | 10 | |
| 14 | 1 | |
| 15 | 35 | |
| 16 | 14 | |
| 17 | 35 | |
| 18 | Informatics aided design of crystal chemistry | 1 |
| 19 | 50 | |
| 20 | 23 |
About Changwon Suh
Changwon Suh is a scholar working on Water Science and Technology, Pollution and Computational Theory and Mathematics, having authored 40 papers that have together received 2.8k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (12 papers), Computational Drug Discovery Methods (8 papers) and Membrane Separation Technologies (8 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (697 citations), Automotive Engineering (496 citations) and Electrochemistry (185 citations). Changwon Suh has collaborated with scholars based in United States, South Korea and Japan. Frequent co-authors include Alán Aspuru‐Guzik, Süleyman Er, Michael P. Marshak, Cooper J. Galvin, Michael R. Gerhardt, Xudong Chen, Brian Huskinson, Michael J. Aziz, Roy G. Gordon and Seockheon Lee. Their work appears in journals such as Nature, Water Research and Journal of Hazardous Materials.
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.