Binling Ai
Impact in
- Clinical Biochemistry top 5%
- Advanced Glycation End Products research
- Biochemistry top 5%
- Phytochemicals and Antioxidant Activities
Papers in
- Food Science 17
- Proteins in Food Systems 11
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- Advanced Glycation End Products research 12
- Co-authors
- Zhanwu Sheng (42 shared papers)Lili Zheng (38 shared papers)Xiaoyan Zheng (33 shared papers)Dao Xiao (31 shared papers)Shenwan Wang (15 shared papers)Shanying Zhang (7 shared papers)Zhimin Xu (6 shared papers)Jianzheng Li (7 shared papers)
- Journals
- Food Hydrocolloids (5 papers)International Journal of Food Science & Technology (4 papers)LWT (4 papers)International Journal of Biological Macromolecules (3 papers)Food Chemistry X (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Binling Ai
50 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 91
- Clinical Biochemistry 115
- Biochemistry 100
- Food Science 283
- Biomaterials 170
- Nutrition and Dietetics 148
Countries citing papers authored by Binling Ai
This map shows the geographic impact of Binling Ai'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 Binling Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Binling Ai more than expected).
Fields of papers citing papers by Binling Ai
This network shows the impact of papers produced by Binling Ai. 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 Binling Ai. The network helps show where Binling Ai may publish in the future.
Co-authors
The 25 scholars most cited alongside Binling Ai, 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 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 104 | |
| 2 | 2020 | 74 | |
| 3 | 2021 | 67 | |
| 4 | 2019 | 58 | |
| 5 | 2016 | 38 | |
| 6 | 2022 | 38 | |
| 7 | A review on bio-butyric acid production and its optimization. | 2014 | 37 |
| 8 | 2017 | 36 | |
| 9 | 2021 | 34 | |
| 10 | 2021 | 33 | |
| 11 | 2022 | 30 | |
| 12 | 2022 | 30 | |
| 13 | 2016 | 29 | |
| 14 | 2023 | 27 | |
| 15 | 2023 | 26 | |
| 16 | 2016 | 25 | |
| 17 | 2014 | 24 | |
| 18 | 2024 | 23 | |
| 19 | 2016 | 21 | |
| 20 | 2022 | 20 |
About Binling Ai
Binling Ai is a scholar working on Food Science, Clinical Biochemistry, Plant Science, Biomedical Engineering and Molecular Biology, having authored 50 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Glycation End Products research (12 papers), Proteins in Food Systems (11 papers), Phytochemicals and Antioxidant Activities (8 papers), Nanocomposite Films for Food Packaging (7 papers), Natural Antidiabetic Agents Studies (7 papers), Food composition and properties (7 papers), Biofuel production and bioconversion (7 papers) and Microbial Metabolic Engineering and Bioproduction (5 papers). The work is most often cited by research in Clinical Biochemistry (115 citations), Biochemistry (100 citations), Food Science (283 citations), Biomaterials (170 citations) and Nutrition and Dietetics (148 citations). Binling Ai has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Zhanwu Sheng, Lili Zheng, Xiaoyan Zheng, Dao Xiao, Shenwan Wang, Shanying Zhang, Zhimin Xu, Jianzheng Li, Yang Yang and Yonggui Pan. Their work appears in journals such as Food Hydrocolloids, International Journal of Food Science & Technology, LWT, International Journal of Biological Macromolecules and Food Chemistry X.
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.