Masato Sumita
- Materials Chemistry top 5%
- Biomedical Engineering top 5%
- Mechanical Engineering top 5%
- Electrical and Electronic Engineering top 10%
- Renewable Energy, Sustainability and the Environment top 10%
- Co-authors
- Akiko YamamotoTakao HanawaYoshitaka TateyamaKoji TsudaSwee Hin TeohRyo TamuraKazuya SaitoSachiko Hiromoto
- Topics
- Machine Learning in Materials Science (15 papers)Computational Drug Discovery Methods (12 papers)Photochemistry and Electron Transfer Studies (10 papers)
- Journals
- The Journal of Chemical PhysicsSHILAP Revista de lepidopterologíaAccounts of Chemical Research
- Partner nations
- JapanUnited StatesCanada
In The Last Decade
Masato Sumita
84 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Materials Chemistry 1.2k
- Biomedical Engineering 543
- Mechanical Engineering 536
- Electrical and Electronic Engineering 481
- Renewable Energy, Sustainability and the Environment 226
Countries citing papers authored by Masato Sumita
This map shows the geographic impact of Masato Sumita'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 Masato Sumita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masato Sumita more than expected).
Fields of papers citing papers by Masato Sumita
This network shows the impact of papers produced by Masato Sumita. 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 Masato Sumita. The network helps show where Masato Sumita may publish in the future.
Co-authorship network of co-authors of Masato Sumita
This figure shows the co-authorship network connecting the top 25 collaborators of Masato Sumita. A scholar is included among the top collaborators of Masato Sumita 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 Masato Sumita. Masato Sumita is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 7 | |
| 5 | 14 | |
| 6 | 1 | |
| 7 | 8 | |
| 8 | 6 | |
| 9 | 37 | |
| 10 | 3 | |
| 11 | 2 | |
| 12 | 85 | |
| 13 | 8 | |
| 14 | 19 | |
| 15 | 13 | |
| 16 | 44 | |
| 17 | 23 | |
| 18 | 13 | |
| 19 | 99 | |
| 20 | 21 |
About Masato Sumita
Masato Sumita is a scholar working on Physical and Theoretical Chemistry, Spectroscopy and Materials Chemistry, having authored 87 papers that have together received 2.5k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (15 papers), Computational Drug Discovery Methods (12 papers) and Photochemistry and Electron Transfer Studies (10 papers). The work is most often cited by research in Metals and Alloys (117 citations), Materials Chemistry (1.2k citations) and Physical and Theoretical Chemistry (156 citations). Masato Sumita has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Akiko Yamamoto, Takao Hanawa, Yoshitaka Tateyama, Koji Tsuda, Swee Hin Teoh, Ryo Tamura, Kazuya Saito, Sachiko Hiromoto, Takahisa Ohno and A.‐P. Tsai. Their work appears in journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and Accounts of Chemical Research.
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.