Masao Sakuraba
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- Semiconductor materials and devices 84
- Thin-Film Transistor Technologies 49
- Silicon and Solar Cell Technologies 44
- Advancements in Semiconductor Devices and Circuit Design 30
- Silicon Carbide Semiconductor Technologies 13
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- Semiconductor materials and interfaces 22
- Semiconductor Quantum Structures and Devices 21
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- Silicon Nanostructures and Photoluminescence 33
- Co-authors
- Junichi MurotaTakashi MatsuuraBernd TillackShoichi OnoTakeshi WatanabeShigeo SatoKuniaki TakahashiToshiaki Tsuchiya
- Cited by
- Electrical and Electronic EngineeringAtomic and Molecular Physics, and OpticsMaterials Chemistry
In The Last Decade
Masao Sakuraba
122 papers receiving 886 citations
Peers
Comparison fields: 5 of 42
- Electrical and Electronic Engineering 826
- Atomic and Molecular Physics, and Optics 261
- Materials Chemistry 296
- Surfaces, Coatings and Films 29
- Condensed Matter Physics 43
Countries citing papers authored by Masao Sakuraba
This map shows the geographic impact of Masao Sakuraba'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 Masao Sakuraba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masao Sakuraba more than expected).
Fields of papers citing papers by Masao Sakuraba
This network shows the impact of papers produced by Masao Sakuraba. 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 Masao Sakuraba. The network helps show where Masao Sakuraba may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masao Sakuraba, 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 | 1 | |
| 2 | 2021 | 3 | |
| 3 | Unsupervised learning based on local interactions between reservoir and readout neurons | 2020 | 1 |
| 4 | 2017 | 5 | |
| 5 | 2013 | 4 | |
| 6 | 2013 | 3 | |
| 7 | 2011 | 0 | |
| 8 | 2011 | 1 | |
| 9 | 2009 | 3 | |
| 10 | 2009 | 7 | |
| 11 | 2008 | 2 | |
| 12 | 2008 | 7 | |
| 13 | 2006 | 3 | |
| 14 | 2005 | 1 | |
| 15 | 2005 | 12 | |
| 16 | 2003 | 2 | |
| 17 | 2002 | 3 | |
| 18 | 2001 | 3 | |
| 19 | 2000 | 15 | |
| 20 | 1994 | 20 |
About Masao Sakuraba
Masao Sakuraba is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Materials Chemistry, having authored 128 papers that have together received 926 indexed citations. Recurring topics across this work include Semiconductor materials and devices (84 papers), Thin-Film Transistor Technologies (49 papers), Silicon and Solar Cell Technologies (44 papers), Silicon Nanostructures and Photoluminescence (33 papers), Advancements in Semiconductor Devices and Circuit Design (30 papers), Semiconductor materials and interfaces (22 papers), Semiconductor Quantum Structures and Devices (21 papers) and Silicon Carbide Semiconductor Technologies (13 papers). The work is most often cited by research in Electrical and Electronic Engineering (826 citations), Atomic and Molecular Physics, and Optics (261 citations) and Materials Chemistry (296 citations). Masao Sakuraba has collaborated with scholars based in Japan, Poland and Germany. Frequent co-authors include Junichi Murota, Takashi Matsuura, Bernd Tillack, Shoichi Ono, Takeshi Watanabe, Shigeo Sato, Kuniaki Takahashi, Toshiaki Tsuchiya, Daisuke Muto and Nobuo Mikoshiba. Their work appears in journals such as Thin Solid Films, Applied Surface Science, Materials Science in Semiconductor Processing, Japanese Journal of Applied Physics and Semiconductor Science and Technology.
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.