Kun Fu
Impact in
- Surfaces, Coatings and Films top 10%
- Surface Modification and Superhydrophobicity
-
- Supercapacitor Materials and Fabrication
Papers in
-
- Graphene and Nanomaterials Applications 2
- Dielectric materials and actuators 2
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- Graphene research and applications 5
- Co-authors
- Liangbing Hu (5 shared papers)Jiaqi Dai (5 shared papers)Jiayu Wan (4 shared papers)Yuanzhan Wang (3 shared papers)Yanbin Wang (4 shared papers)Yonggang Yao (3 shared papers)Wei Luo (3 shared papers)Shuze Zhu (3 shared papers)
- Journals
- Construction and Building Materials (2 papers)Computer Vision and Image Understanding (1 paper)Advanced Materials (1 paper)Computational Materials Science (1 paper)Cold Regions Science and Technology (1 paper)
- Partner nations
- ChinaUnited StatesSlovakia
In The Last Decade
Kun Fu
16 papers receiving 832 citations
Peers
Comparison fields: 5 of 61
- Surfaces, Coatings and Films 65
- Electronic, Optical and Magnetic Materials 154
- Renewable Energy, Sustainability and the Environment 121
- Materials Chemistry 326
- Civil and Structural Engineering 134
Countries citing papers authored by Kun Fu
This map shows the geographic impact of Kun Fu'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 Kun Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Fu more than expected).
Fields of papers citing papers by Kun Fu
This network shows the impact of papers produced by Kun Fu. 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 Kun Fu. The network helps show where Kun Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Fu, 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 | 2016 | 214 | |
| 2 | 2016 | 193 | |
| 3 | 2014 | 88 | |
| 4 | 2016 | 86 | |
| 5 | 2023 | 73 | |
| 6 | 2019 | 67 | |
| 7 | 2016 | 51 | |
| 8 | 2019 | 40 | |
| 9 | 2019 | 9 | |
| 10 | 2022 | 7 | |
| 11 | 2022 | 7 | |
| 12 | 2018 | 6 | |
| 13 | 2024 | 2 | |
| 14 | 2023 | 2 | |
| 15 | 2005 | 1 | |
| 16 | 2005 | 1 |
About Kun Fu
Kun Fu is a scholar working on Biomedical Engineering, Materials Chemistry, Mechanical Engineering, Civil and Structural Engineering and Artificial Intelligence, having authored 16 papers that have together received 847 indexed citations. Recurring topics across this work include Graphene research and applications (5 papers), Concrete and Cement Materials Research (3 papers), Concrete Corrosion and Durability (3 papers), Advanced Graph Neural Networks (2 papers), Graphene and Nanomaterials Applications (2 papers), Dielectric materials and actuators (2 papers), Supercapacitor Materials and Fabrication (2 papers) and Smart Materials for Construction (2 papers). The work is most often cited by research in Surfaces, Coatings and Films (65 citations), Electronic, Optical and Magnetic Materials (154 citations), Renewable Energy, Sustainability and the Environment (121 citations), Materials Chemistry (326 citations) and Civil and Structural Engineering (134 citations). Kun Fu has collaborated with scholars based in China, United States and Slovakia. Frequent co-authors include Liangbing Hu, Jiaqi Dai, Jiayu Wan, Yuanzhan Wang, Yanbin Wang, Yonggang Yao, Wei Luo, Shuze Zhu, Teng Li and Yanan Chen. Their work appears in journals such as Construction and Building Materials, Computer Vision and Image Understanding, Advanced Materials, Computational Materials Science and Cold Regions Science and Technology.
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.