Ming Lei
Impact in
- Metals and Alloys top 10%
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
Papers in
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- Physics of Superconductivity and Magnetism 17
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- ZnO doping and properties 6
- Co-authors
- Bai Sun (9 shared papers)Yong Zhao (23 shared papers)Shouhui Zhu (6 shared papers)Shuangsuo Mao (5 shared papers)Liang Zheng (4 shared papers)Chen Fu (4 shared papers)Zhenghuan Zhao (3 shared papers)Yong Zhang (16 shared papers)
In The Last Decade
Ming Lei
64 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 99
- Metals and Alloys 37
- Cellular and Molecular Neuroscience 221
- Polymers and Plastics 174
- Condensed Matter Physics 90
- Electrical and Electronic Engineering 437
Countries citing papers authored by Ming Lei
This map shows the geographic impact of Ming Lei'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 Ming Lei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Lei more than expected).
Fields of papers citing papers by Ming Lei
This network shows the impact of papers produced by Ming Lei. 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 Ming Lei. The network helps show where Ming Lei may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Lei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 100 | |
| 2 | 2017 | 83 | |
| 3 | 2019 | 75 | |
| 4 | 2018 | 69 | |
| 5 | 2021 | 67 | |
| 6 | 2011 | 64 | |
| 7 | 2017 | 61 | |
| 8 | 2018 | 61 | |
| 9 | 2018 | 54 | |
| 10 | 2008 | 50 | |
| 11 | 2007 | 44 | |
| 12 | 2019 | 37 | |
| 13 | 2018 | 26 | |
| 14 | 2019 | 22 | |
| 15 | 2021 | 18 | |
| 16 | 2022 | 18 | |
| 17 | 2024 | 17 | |
| 18 | 2017 | 16 | |
| 19 | 2020 | 13 | |
| 20 | 2023 | 12 |
About Ming Lei
Ming Lei is a scholar working on Condensed Matter Physics, Materials Chemistry, Electrical and Electronic Engineering, Electronic, Optical and Magnetic Materials and Biomedical Engineering, having authored 65 papers that have together received 1.1k indexed citations. Recurring topics across this work include Physics of Superconductivity and Magnetism (17 papers), Advanced Memory and Neural Computing (8 papers), Copper Interconnects and Reliability (8 papers), ZnO doping and properties (6 papers), Semiconductor materials and devices (6 papers), Conducting polymers and applications (5 papers), Advanced Sensor and Energy Harvesting Materials (5 papers) and Photoreceptor and optogenetics research (5 papers). The work is most often cited by research in Metals and Alloys (37 citations), Cellular and Molecular Neuroscience (221 citations), Polymers and Plastics (174 citations), Condensed Matter Physics (90 citations) and Electrical and Electronic Engineering (437 citations). Ming Lei has collaborated with scholars based in China, Australia and Macao. Frequent co-authors include Bai Sun, Yong Zhao, Shouhui Zhu, Shuangsuo Mao, Liang Zheng, Chen Fu, Zhenghuan Zhao, Yong Zhang, Pingping Zheng and Hongzan Bin. Their work appears in journals such as physica status solidi (a), IEEE Transactions on Applied Superconductivity, Physica C Superconductivity, Materials Today Sustainability and Journal of Bridge Engineering.
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.