Nian Duan
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 9
- Ferroelectric and Negative Capacitance Devices 4
- CCD and CMOS Imaging Sensors 3
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- Neuroscience and Neural Engineering 5
- Photoreceptor and optogenetics research 4
- Co-authors
- Yi Li (9 shared papers)Ting‐Chang Chang (8 shared papers)Xiangshui Miao (6 shared papers)Yaxiong Zhou (5 shared papers)Jia Chen (3 shared papers)Yuhui He (3 shared papers)Kan‐Hao Xue (4 shared papers)Xiangshui Miao (3 shared papers)
In The Last Decade
Nian Duan
11 papers receiving 346 citations
Peers
Comparison fields: 5 of 29
- Cellular and Molecular Neuroscience 151
- Electrical and Electronic Engineering 331
- Polymers and Plastics 57
- Cognitive Neuroscience 47
- Artificial Intelligence 54
Countries citing papers authored by Nian Duan
This map shows the geographic impact of Nian Duan'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 Nian Duan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nian Duan more than expected).
Fields of papers citing papers by Nian Duan
This network shows the impact of papers produced by Nian Duan. 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 Nian Duan. The network helps show where Nian Duan may publish in the future.
Co-authors
The 25 scholars most cited alongside Nian Duan, 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 | 2019 | 92 | |
| 2 | 2020 | 57 | |
| 3 | 2016 | 54 | |
| 4 | 2020 | 39 | |
| 5 | 2018 | 26 | |
| 6 | 2018 | 24 | |
| 7 | 2018 | 23 | |
| 8 | 2018 | 21 | |
| 9 | 2014 | 8 | |
| 10 | 2015 | 4 | |
| 11 | 2018 | 2 |
About Nian Duan
Nian Duan is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials and Cognitive Neuroscience, having authored 11 papers that have together received 350 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (9 papers), Neuroscience and Neural Engineering (5 papers), Photoreceptor and optogenetics research (4 papers), Ferroelectric and Negative Capacitance Devices (4 papers), CCD and CMOS Imaging Sensors (3 papers), Magnetic properties of thin films (2 papers), Multiferroics and related materials (1 paper) and Magnetic Properties and Synthesis of Ferrites (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (151 citations), Electrical and Electronic Engineering (331 citations), Polymers and Plastics (57 citations), Cognitive Neuroscience (47 citations) and Artificial Intelligence (54 citations). Nian Duan has collaborated with scholars based in China and Taiwan. Frequent co-authors include Yi Li, Ting‐Chang Chang, Xiangshui Miao, Yaxiong Zhou, Jia Chen, Yuhui He, Kan‐Hao Xue, Xiangshui Miao, Ke Lu and Rui Kuang. Their work appears in journals such as IEEE Transactions on Electron Devices, ACS Applied Electronic Materials, IEEE Electron Device Letters, Advanced Electronic Materials and Journal of Magnetism and Magnetic Materials.
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.