Sha Nie
Impact in
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- CCD and CMOS Imaging Sensors
Papers in
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- Advanced Memory and Neural Computing 7
- CCD and CMOS Imaging Sensors 4
- Thin-Film Transistor Technologies 3
- Semiconductor materials and devices 2
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- ZnO doping and properties 9
- Copper-based nanomaterials and applications 4
- Co-authors
- Qing Wan (10 shared papers)Yongli He (8 shared papers)Rui Liu (4 shared papers)Yi Shi (7 shared papers)Yi Yang (3 shared papers)Huaming Yang (1 shared paper)Shanshan Jiang (3 shared papers)Jing Ouyang (1 shared paper)
In The Last Decade
Sha Nie
17 papers receiving 827 citations
Peers
Comparison fields: 5 of 37
- Cellular and Molecular Neuroscience 323
- Electrical and Electronic Engineering 725
- Polymers and Plastics 175
- Bioengineering 26
- Materials Chemistry 211
Countries citing papers authored by Sha Nie
This map shows the geographic impact of Sha Nie'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 Sha Nie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sha Nie more than expected).
Fields of papers citing papers by Sha Nie
This network shows the impact of papers produced by Sha Nie. 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 Sha Nie. The network helps show where Sha Nie may publish in the future.
Co-authors
The 25 scholars most cited alongside Sha Nie, 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 | 2018 | 206 | |
| 2 | 2019 | 189 | |
| 3 | 2018 | 104 | |
| 4 | 2008 | 76 | |
| 5 | 2019 | 43 | |
| 6 | 2019 | 39 | |
| 7 | 2007 | 36 | |
| 8 | 2018 | 35 | |
| 9 | 2018 | 33 | |
| 10 | 2019 | 29 | |
| 11 | 2016 | 14 | |
| 12 | 2018 | 14 | |
| 13 | 2016 | 12 | |
| 14 | 2015 | 8 | |
| 15 | 2016 | 6 | |
| 16 | 2017 | 2 | |
| 17 | 2018 | 1 | |
| 18 | 2025 | 0 | |
| 19 | 2020 | 0 |
About Sha Nie
Sha Nie is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Cellular and Molecular Neuroscience, Cognitive Neuroscience and Polymers and Plastics, having authored 19 papers that have together received 847 indexed citations. Recurring topics across this work include ZnO doping and properties (9 papers), Advanced Memory and Neural Computing (7 papers), Neuroscience and Neural Engineering (5 papers), Copper-based nanomaterials and applications (4 papers), CCD and CMOS Imaging Sensors (4 papers), Transition Metal Oxide Nanomaterials (3 papers), Thin-Film Transistor Technologies (3 papers) and Semiconductor materials and devices (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (323 citations), Electrical and Electronic Engineering (725 citations), Polymers and Plastics (175 citations), Bioengineering (26 citations) and Materials Chemistry (211 citations). Sha Nie has collaborated with scholars based in China and Singapore. Frequent co-authors include Qing Wan, Yongli He, Rui Liu, Yi Shi, Yi Yang, Huaming Yang, Shanshan Jiang, Jing Ouyang, Yu Xiao and Aidong Tang. Their work appears in journals such as IEEE Electron Device Letters, Materials Chemistry and Physics, Journal of Alloys and Compounds, Advanced Electronic Materials and Journal of Materials Chemistry C.
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.