Makoto Urushihara
- Catalysis top 2%
- Ionic liquids properties and applications 2
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- CO2 Reduction Techniques and Catalysts 3
- Electrochemistry top 5%
- Electrochemical Analysis and Applications 2
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- Machine Learning in Materials Science 2
- Magnetic Properties and Synthesis of Ferrites 1
- Corrosion Behavior and Inhibition 1
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- Nanomaterials and Printing Technologies 1
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- Neural Networks and Applications 1
- Co-authors
- Karen ChanJens K. NørskovLeanne D. ChenChuan ShiStephanie NitopiThomas F. JaramilloChristopher HahnJeremy T. Feaster
- Cited by
- CatalysisRenewable Energy, Sustainability and the EnvironmentProcess Chemistry and Technology
- Journals
- SHILAP Revista de lepidopterología (2 papers)Langmuir (1 paper)Scientific Reports (1 paper)
- Partner nations
- JapanUnited States
In The Last Decade
Makoto Urushihara
6 papers receiving 693 citations
Hit Papers
Peers
Comparison fields: 5 of 44
- Catalysis 405
- Renewable Energy, Sustainability and the Environment 618
- Process Chemistry and Technology 75
- Electrochemistry 155
- Materials Chemistry 176
Countries citing papers authored by Makoto Urushihara
This map shows the geographic impact of Makoto Urushihara'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 Makoto Urushihara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Makoto Urushihara more than expected).
Fields of papers citing papers by Makoto Urushihara
This network shows the impact of papers produced by Makoto Urushihara. 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 Makoto Urushihara. The network helps show where Makoto Urushihara may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Makoto Urushihara, 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 | 2024 | 0 | |
| 2 | 2023 | 4 | |
| 3 | 2023 | 1 | |
| 4 | 2022 | 10 | |
| 5 | 2017 | 64 | |
| 6 | Electric Field Effects in Electrochemical CO2 Reductionbreakdown → | 2016 | 571 |
| 7 | 2015 | 50 |
About Makoto Urushihara
Makoto Urushihara is a scholar working on Electrochemistry, Catalysis and Renewable Energy, Sustainability and the Environment, having authored 7 papers that have together received 700 indexed citations. Recurring topics across this work include CO2 Reduction Techniques and Catalysts (3 papers), Machine Learning in Materials Science (2 papers), Ionic liquids properties and applications (2 papers), Electrochemical Analysis and Applications (2 papers), Nanomaterials and Printing Technologies (1 paper), Neural Networks and Applications (1 paper), Magnetic Properties and Synthesis of Ferrites (1 paper) and Corrosion Behavior and Inhibition (1 paper). The work is most often cited by research in Catalysis (405 citations), Renewable Energy, Sustainability and the Environment (618 citations) and Process Chemistry and Technology (75 citations). Makoto Urushihara has collaborated with scholars based in Japan and United States. Frequent co-authors include Karen Chan, Jens K. Nørskov, Leanne D. Chen, Chuan Shi, Stephanie Nitopi, Thomas F. Jaramillo, Christopher Hahn, Jeremy T. Feaster, A. Jongerius and Xinyan Liu. Their work appears in journals such as SHILAP Revista de lepidopterología, Langmuir and Scientific Reports.
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.