Enlong Li
Impact in
- Polymers and Plastics top 2%
- Conducting polymers and applications
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
Papers in
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- Advanced Memory and Neural Computing 40
- Ferroelectric and Negative Capacitance Devices 14
- Perovskite Materials and Applications 14
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- Conducting polymers and applications 19
- Co-authors
- Huipeng Chen (50 shared papers)Tailiang Guo (41 shared papers)Rengjian Yu (25 shared papers)Yaqian Liu (14 shared papers)Yujie Yan (21 shared papers)Yuanyuan Hu (12 shared papers)Qizhen Chen (14 shared papers)Xiumei Wang (10 shared papers)
In The Last Decade
Enlong Li
59 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 80
- Polymers and Plastics 795
- Cellular and Molecular Neuroscience 904
- Electrical and Electronic Engineering 2.2k
- Biomedical Engineering 665
- Cognitive Neuroscience 266
Countries citing papers authored by Enlong Li
This map shows the geographic impact of Enlong Li'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 Enlong Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Enlong Li more than expected).
Fields of papers citing papers by Enlong Li
This network shows the impact of papers produced by Enlong Li. 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 Enlong Li. The network helps show where Enlong Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Enlong Li, 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 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 157 | |
| 2 | 2020 | 132 | |
| 3 | 2020 | 129 | |
| 4 | 2021 | 122 | |
| 5 | 2021 | 110 | |
| 6 | 2021 | 107 | |
| 7 | 2022 | 106 | |
| 8 | 2020 | 103 | |
| 9 | 2019 | 101 | |
| 10 | 2023 | 95 | |
| 11 | 2022 | 91 | |
| 12 | 2021 | 90 | |
| 13 | 2020 | 75 | |
| 14 | 2022 | 65 | |
| 15 | 2021 | 61 | |
| 16 | 2021 | 60 | |
| 17 | 2021 | 58 | |
| 18 | 2018 | 56 | |
| 19 | 2022 | 56 | |
| 20 | 2020 | 54 |
About Enlong Li
Enlong Li is a scholar working on Electrical and Electronic Engineering, Polymers and Plastics, Cellular and Molecular Neuroscience, Biomedical Engineering and Materials Chemistry, having authored 63 papers that have together received 2.6k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (40 papers), Conducting polymers and applications (19 papers), Ferroelectric and Negative Capacitance Devices (14 papers), Perovskite Materials and Applications (14 papers), Advanced Sensor and Energy Harvesting Materials (13 papers), Neuroscience and Neural Engineering (11 papers), Photoreceptor and optogenetics research (9 papers) and Neural Networks and Reservoir Computing (9 papers). The work is most often cited by research in Polymers and Plastics (795 citations), Cellular and Molecular Neuroscience (904 citations), Electrical and Electronic Engineering (2.2k citations), Biomedical Engineering (665 citations) and Cognitive Neuroscience (266 citations). Enlong Li has collaborated with scholars based in China, Singapore and Macao. Frequent co-authors include Huipeng Chen, Tailiang Guo, Rengjian Yu, Yaqian Liu, Yujie Yan, Yuanyuan Hu, Qizhen Chen, Xiumei Wang, Xiaomin Wu and Changsong Gao. Their work appears in journals such as Nano Energy, ACS Applied Materials & Interfaces, Nature Communications, Journal of Materials Chemistry C and Advanced Functional 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.