Hideo Doi
Impact in
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- Machine Learning in Materials Science
- Block Copolymer Self-Assembly
- Material Dynamics and Properties
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- Spectroscopy and Quantum Chemical Studies
Papers in
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- Machine Learning in Materials Science 7
- Block Copolymer Self-Assembly 5
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- Spectroscopy and Quantum Chemical Studies 8
- Advanced Chemical Physics Studies 5
- Co-authors
- Koji Okuwaki (24 shared papers)Yuji Mochizuki (26 shared papers)Takeshi Aoyagi (7 shared papers)Kazuaki Z. Takahashi (7 shared papers)Taku Ozawa (7 shared papers)Kenji Yasuoka (6 shared papers)Jun‐ichi Fukuda (2 shared papers)Kaori Fukuzawa (3 shared papers)
- Journals
- Japanese Journal of Applied Physics (4 papers)Journal of Computational Chemistry (3 papers)Chemistry Letters (3 papers)Applied Physics Express (2 papers)The Journal of Chemical Physics (2 papers)
- Partner nations
- JapanGermanyUnited States
In The Last Decade
Hideo Doi
34 papers receiving 302 citations
Peers
Comparison fields: 5 of 54
- Materials Chemistry 133
- Atomic and Molecular Physics, and Optics 66
- Organic Chemistry 48
- Computational Theory and Mathematics 25
- Physical and Theoretical Chemistry 12
Countries citing papers authored by Hideo Doi
This map shows the geographic impact of Hideo Doi'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 Hideo Doi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideo Doi more than expected).
Fields of papers citing papers by Hideo Doi
This network shows the impact of papers produced by Hideo Doi. 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 Hideo Doi. The network helps show where Hideo Doi may publish in the future.
Co-authors
The 25 scholars most cited alongside Hideo Doi, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 36 | |
| 2 | 2018 | 30 | |
| 3 | 2017 | 27 | |
| 4 | 2017 | 23 | |
| 5 | 2019 | 19 | |
| 6 | 2021 | 18 | |
| 7 | 2020 | 16 | |
| 8 | 2020 | 15 | |
| 9 | 2018 | 15 | |
| 10 | 2023 | 10 | |
| 11 | 2017 | 9 | |
| 12 | 2014 | 8 | |
| 13 | 2021 | 8 | |
| 14 | 2023 | 7 | |
| 15 | 2021 | 7 | |
| 16 | 2022 | 7 | |
| 17 | 2024 | 6 | |
| 18 | 2023 | 6 | |
| 19 | 2017 | 5 | |
| 20 | 2018 | 5 |
About Hideo Doi
Hideo Doi is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics, Molecular Biology, Organic Chemistry and Biomedical Engineering, having authored 37 papers that have together received 307 indexed citations. Recurring topics across this work include Spectroscopy and Quantum Chemical Studies (8 papers), Machine Learning in Materials Science (7 papers), Surfactants and Colloidal Systems (6 papers), Protein Structure and Dynamics (6 papers), Lipid Membrane Structure and Behavior (6 papers), Advanced Chemical Physics Studies (5 papers), Block Copolymer Self-Assembly (5 papers) and Phase Equilibria and Thermodynamics (2 papers). The work is most often cited by research in Materials Chemistry (133 citations), Atomic and Molecular Physics, and Optics (66 citations), Organic Chemistry (48 citations), Computational Theory and Mathematics (25 citations) and Physical and Theoretical Chemistry (12 citations). Hideo Doi has collaborated with scholars based in Japan, Germany and United States. Frequent co-authors include Koji Okuwaki, Yuji Mochizuki, Takeshi Aoyagi, Kazuaki Z. Takahashi, Taku Ozawa, Kenji Yasuoka, Jun‐ichi Fukuda, Kaori Fukuzawa, Misako Aida and Yudai Watanabe. Their work appears in journals such as Japanese Journal of Applied Physics, Journal of Computational Chemistry, Chemistry Letters, Applied Physics Express 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.