Bin Chu
Impact in
- Rehabilitation top 5%
- Wound Healing and Treatments
- Biomaterials top 5%
- Electrospun Nanofibers in Biomedical Applications
- Supramolecular Self-Assembly in Materials
Papers in
- Hematology 13
- Multiple Myeloma Research and Treatments 13
- Biomaterials 11
- Electrospun Nanofibers in Biomedical Applications 4
- Supramolecular Self-Assembly in Materials 4
- Collagen: Extraction and Characterization 2
- Co-authors
- Chaoxi Wu (9 shared papers)Shunqing Tang (8 shared papers)Annie Lai Man Cheung (1 shared paper)Sai‐Wah Tsao (1 shared paper)Zhong Zheng (1 shared paper)Yong Chuan Wong (1 shared paper)Changsheng Chen (6 shared papers)Yifei Wang (4 shared papers)
In The Last Decade
Bin Chu
51 papers receiving 731 citations
Peers
Comparison fields: 5 of 86
- Rehabilitation 114
- Biomaterials 185
- Molecular Medicine 81
- Otorhinolaryngology 43
- Hematology 66
Countries citing papers authored by Bin Chu
This map shows the geographic impact of Bin Chu'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 Bin Chu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Chu more than expected).
Fields of papers citing papers by Bin Chu
This network shows the impact of papers produced by Bin Chu. 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 Bin Chu. The network helps show where Bin Chu may publish in the future.
Co-authors
The 25 scholars most cited alongside Bin Chu, 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1999 | 135 | |
| 2 | 2015 | 61 | |
| 3 | 2020 | 49 | |
| 4 | 2021 | 45 | |
| 5 | 2016 | 43 | |
| 6 | 2016 | 41 | |
| 7 | 2019 | 36 | |
| 8 | 2021 | 36 | |
| 9 | 2013 | 30 | |
| 10 | 2013 | 21 | |
| 11 | 2010 | 20 | |
| 12 | 2018 | 18 | |
| 13 | 2005 | 16 | |
| 14 | 2025 | 16 | |
| 15 | 2020 | 15 | |
| 16 | 2020 | 12 | |
| 17 | 2020 | 12 | |
| 18 | 2023 | 12 | |
| 19 | 2014 | 11 | |
| 20 | 2020 | 11 |
About Bin Chu
Bin Chu is a scholar working on Hematology, Biomaterials, Molecular Medicine, Rehabilitation and Ecological Modeling, having authored 57 papers that have together received 747 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (13 papers), Hydrogels: synthesis, properties, applications (7 papers), Electrospun Nanofibers in Biomedical Applications (4 papers), Bone Tissue Engineering Materials (4 papers), Supramolecular Self-Assembly in Materials (4 papers), Wound Healing and Treatments (4 papers), GNSS positioning and interference (3 papers) and Collagen: Extraction and Characterization (2 papers). The work is most often cited by research in Rehabilitation (114 citations), Biomaterials (185 citations), Molecular Medicine (81 citations), Otorhinolaryngology (43 citations) and Hematology (66 citations). Bin Chu has collaborated with scholars based in China, Hong Kong and Germany. Frequent co-authors include Chaoxi Wu, Shunqing Tang, Annie Lai Man Cheung, Sai‐Wah Tsao, Zhong Zheng, Yong Chuan Wong, Changsheng Chen, Yifei Wang, Mei Tu and Jinmei He. Their work appears in journals such as Reactive and Functional Polymers, Frontiers in Oncology, Materials Science and Engineering C, Cancer Medicine and ACS Nano.
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.