Takashi Ikuno
- Materials Chemistry top 5%
- Carbon Nanotubes in Composites 36
- Graphene research and applications 28
- Diamond and Carbon-based Materials Research 15
- Polymers and Plastics top 10%
- Conducting polymers and applications 7
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- Advanced Memory and Neural Computing 6
- Biomedical Engineering top 10%
- Advanced Sensor and Energy Harvesting Materials 9
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- Force Microscopy Techniques and Applications 8
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- Neural Networks and Reservoir Computing 6
- Co-authors
- Alex ZettlDavid OkawaMitsuhiro KatayamaKenjiro OuraJean M. J. FréchetToby SainsburyHideyuki NakanoShin‐ichi Honda
- Journals
- Journal of the American Chemical Society (1 paper)Physical Review Letters (1 paper)Applied Physics Letters (3 papers)
- Partner nations
- JapanUnited StatesSouth Korea
In The Last Decade
Takashi Ikuno
70 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 69
- Materials Chemistry 1.4k
- Polymers and Plastics 137
- Electrical and Electronic Engineering 531
- Biomedical Engineering 362
- Atomic and Molecular Physics, and Optics 242
Countries citing papers authored by Takashi Ikuno
This map shows the geographic impact of Takashi Ikuno'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 Takashi Ikuno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takashi Ikuno more than expected).
Fields of papers citing papers by Takashi Ikuno
This network shows the impact of papers produced by Takashi Ikuno. 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 Takashi Ikuno. The network helps show where Takashi Ikuno may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Takashi Ikuno, 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 | 2025 | 1 | |
| 2 | 2025 | 3 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 0 | |
| 10 | 2023 | 15 | |
| 11 | 2023 | 1 | |
| 12 | 2020 | 10 | |
| 13 | 2010 | 4 | |
| 14 | 2006 | 344 | |
| 15 | 2005 | 24 | |
| 16 | 2005 | 12 | |
| 17 | 2004 | 8 | |
| 18 | 2004 | 40 | |
| 19 | 2002 | 7 | |
| 20 | Spray Combustion Characteristics of a Gas Turbine Combustor (Comparisons between Simulated Results and Measured Data) | 1997 | 2 |
About Takashi Ikuno
Takashi Ikuno is a scholar working on Materials Chemistry, Polymers and Plastics and Atomic and Molecular Physics, and Optics, having authored 72 papers that have together received 1.7k indexed citations. Recurring topics across this work include Carbon Nanotubes in Composites (36 papers), Graphene research and applications (28 papers), Diamond and Carbon-based Materials Research (15 papers), Advanced Sensor and Energy Harvesting Materials (9 papers), Force Microscopy Techniques and Applications (8 papers), Conducting polymers and applications (7 papers), Advanced Memory and Neural Computing (6 papers) and Neural Networks and Reservoir Computing (6 papers). The work is most often cited by research in Materials Chemistry (1.4k citations), Polymers and Plastics (137 citations) and Electrical and Electronic Engineering (531 citations). Takashi Ikuno has collaborated with scholars based in Japan, United States and South Korea. Frequent co-authors include Alex Zettl, David Okawa, Mitsuhiro Katayama, Kenjiro Oura, Jean M. J. Fréchet, Toby Sainsbury, Hideyuki Nakano, Shin‐ichi Honda, Deyu Li and Arun Majumdar. Their work appears in journals such as Journal of the American Chemical Society, Physical Review Letters and Applied Physics Letters.
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.