Jun Bai
Impact in
- Surfaces, Coatings and Films top 10%
- Polymer Surface Interaction Studies
-
- Electrospun Nanofibers in Biomedical Applications
Papers in
-
- Bone Tissue Engineering Materials 4
- Graphene and Nanomaterials Applications 2
- 3D Printing in Biomedical Research 2
-
- Aquaculture disease management and microbiota 2
- Co-authors
- Changyou Gao (5 shared papers)Hao Lan Zhang (2 shared papers)Zhongru Gou (2 shared papers)Yue Xi (1 shared paper)Zhijian Yang (1 shared paper)Zhiwei Jiang (1 shared paper)Shuqin Wang (1 shared paper)Wei Dai (1 shared paper)
- Journals
- ACS Applied Materials & Interfaces (2 papers)Journal of Physics D Applied Physics (2 papers)Frontiers in Microbiology (1 paper)RSC Advances (1 paper)Journal of Biomedical Materials Research Part A (1 paper)
- Partner nations
- China
In The Last Decade
Jun Bai
26 papers receiving 377 citations
Peers
Comparison fields: 5 of 90
- Surfaces, Coatings and Films 40
- Biomaterials 70
- Rehabilitation 20
- Biomedical Engineering 141
- Pharmaceutical Science 18
Countries citing papers authored by Jun Bai
This map shows the geographic impact of Jun Bai'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 Jun Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Bai more than expected).
Fields of papers citing papers by Jun Bai
This network shows the impact of papers produced by Jun Bai. 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 Jun Bai. The network helps show where Jun Bai may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Bai, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 132 | |
| 2 | 2018 | 40 | |
| 3 | 2022 | 31 | |
| 4 | 2019 | 22 | |
| 5 | 2016 | 21 | |
| 6 | 2016 | 17 | |
| 7 | 2020 | 15 | |
| 8 | 2001 | 12 | |
| 9 | Error analysis of shear-velocity prediction by the Xu-White model | 2012 | 9 |
| 10 | 2017 | 9 | |
| 11 | 2019 | 9 | |
| 12 | 2025 | 9 | |
| 13 | 2021 | 9 | |
| 14 | 2021 | 7 | |
| 15 | 2014 | 7 | |
| 16 | 2018 | 7 | |
| 17 | 2016 | 6 | |
| 18 | 2024 | 4 | |
| 19 | 2023 | 4 | |
| 20 | 2015 | 3 |
About Jun Bai
Jun Bai is a scholar working on Biomedical Engineering, Immunology, Molecular Biology, Materials Chemistry and Biomaterials, having authored 27 papers that have together received 386 indexed citations. Recurring topics across this work include Bone Tissue Engineering Materials (4 papers), Aquaculture disease management and microbiota (2 papers), Cellular Mechanics and Interactions (2 papers), Graphene and Nanomaterials Applications (2 papers), CRISPR and Genetic Engineering (2 papers), 3D Printing in Biomedical Research (2 papers), Ion-surface interactions and analysis (2 papers) and Chemical Synthesis and Analysis (2 papers). The work is most often cited by research in Surfaces, Coatings and Films (40 citations), Biomaterials (70 citations), Rehabilitation (20 citations), Biomedical Engineering (141 citations) and Pharmaceutical Science (18 citations). Jun Bai has collaborated with scholars based in China. Frequent co-authors include Changyou Gao, Hao Lan Zhang, Zhongru Gou, Yue Xi, Zhijian Yang, Zhiwei Jiang, Shuqin Wang, Wei Dai, Guoli Yang and Zongqian Shi. Their work appears in journals such as ACS Applied Materials & Interfaces, Journal of Physics D Applied Physics, Frontiers in Microbiology, RSC Advances and Journal of Biomedical Materials Research Part A.
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.