Yan Hui
Impact in
- Inorganic Chemistry top 10%
- Metal-Organic Frameworks: Synthesis and Applications
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- Covalent Organic Framework Applications
- Catalytic Processes in Materials Science
Papers in
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- Machine Learning in Materials Science 2
- Ferroelectric and Piezoelectric Materials 1
- Electronic and Structural Properties of Oxides 1
- Porphyrin and Phthalocyanine Chemistry 1
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- Computational Drug Discovery Methods 3
- Co-authors
- Pin Chen (5 shared papers)Kefeng Shang (3 shared papers)Nan Jiang (3 shared papers)Rui‐Kang Huang (1 shared paper)Zong‐Wen Mo (1 shared paper)Ning‐Yu Huang (1 shared paper)Zi‐Ming Ye (1 shared paper)Shasha Wang (1 shared paper)
In The Last Decade
Yan Hui
10 papers receiving 351 citations
Peers
Comparison fields: 5 of 58
- Inorganic Chemistry 160
- Materials Chemistry 223
- Renewable Energy, Sustainability and the Environment 77
- Computational Theory and Mathematics 36
- Process Chemistry and Technology 6
Countries citing papers authored by Yan Hui
This map shows the geographic impact of Yan Hui'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 Yan Hui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Hui more than expected).
Fields of papers citing papers by Yan Hui
This network shows the impact of papers produced by Yan Hui. 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 Yan Hui. The network helps show where Yan Hui may publish in the future.
Co-authors
The 25 scholars most cited alongside Yan Hui, 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 | 179 | |
| 2 | 2019 | 71 | |
| 3 | 2019 | 37 | |
| 4 | 2018 | 21 | |
| 5 | 2018 | 14 | |
| 6 | 2022 | 9 | |
| 7 | 2022 | 8 | |
| 8 | 2020 | 5 | |
| 9 | 2011 | 4 | |
| 10 | 2022 | 4 |
About Yan Hui
Yan Hui is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Electrical and Electronic Engineering, Radiology, Nuclear Medicine and Imaging and Organic Chemistry, having authored 10 papers that have together received 352 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (3 papers), Plasma Applications and Diagnostics (2 papers), Machine Learning in Materials Science (2 papers), Ferroelectric and Piezoelectric Materials (1 paper), Electronic and Structural Properties of Oxides (1 paper), Porphyrin and Phthalocyanine Chemistry (1 paper), Advanced Photocatalysis Techniques (1 paper) and Metal-Organic Frameworks: Synthesis and Applications (1 paper). The work is most often cited by research in Inorganic Chemistry (160 citations), Materials Chemistry (223 citations), Renewable Energy, Sustainability and the Environment (77 citations), Computational Theory and Mathematics (36 citations) and Process Chemistry and Technology (6 citations). Yan Hui has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Pin Chen, Kefeng Shang, Nan Jiang, Rui‐Kang Huang, Zong‐Wen Mo, Ning‐Yu Huang, Zi‐Ming Ye, Shasha Wang, Chao Wang and Dong‐Dong Zhou. Their work appears in journals such as Journal of Cheminformatics, Bioinformatics, The Journal of Physical Chemistry C, Plasma Chemistry and Plasma Processing and Nature 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.