Minmin Ai
Impact in
- Food Science top 1%
- Proteins in Food Systems
- Microencapsulation and Drying Processes
- Polysaccharides Composition and Applications
- Food Chemistry and Fat Analysis
- Animal Science and Zoology top 2%
- Meat and Animal Product Quality
Papers in
- Food Science 28
- Proteins in Food Systems 28
- Microencapsulation and Drying Processes 14
- Polysaccharides Composition and Applications 5
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- Meat and Animal Product Quality 9
- Co-authors
- Aimin Jiang (16 shared papers)Shanguang Guo (24 shared papers)Nan Xiao (7 shared papers)Yuanyuan Cao (7 shared papers)Quan Zhou (4 shared papers)Hong Fan (5 shared papers)Ting Tang (1 shared paper)Nan Xiao (11 shared papers)
In The Last Decade
Minmin Ai
31 papers receiving 857 citations
Peers
Comparison fields: 5 of 70
- Food Science 664
- Animal Science and Zoology 228
- Nutrition and Dietetics 144
- Biotechnology 39
- Biomaterials 53
Countries citing papers authored by Minmin Ai
This map shows the geographic impact of Minmin 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 Minmin Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minmin Ai more than expected).
Fields of papers citing papers by Minmin Ai
This network shows the impact of papers produced by Minmin 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 Minmin Ai. The network helps show where Minmin Ai may publish in the future.
Co-authors
The 25 scholars most cited alongside Minmin 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 168 | |
| 2 | 2020 | 102 | |
| 3 | 2019 | 75 | |
| 4 | 2020 | 68 | |
| 5 | 2017 | 63 | |
| 6 | 2019 | 60 | |
| 7 | 2020 | 48 | |
| 8 | 2020 | 43 | |
| 9 | 2020 | 26 | |
| 10 | 2023 | 26 | |
| 11 | 2023 | 25 | |
| 12 | 2021 | 20 | |
| 13 | 2023 | 19 | |
| 14 | 2018 | 17 | |
| 15 | 2023 | 16 | |
| 16 | 2022 | 14 | |
| 17 | 2024 | 13 | |
| 18 | 2024 | 11 | |
| 19 | 2022 | 9 | |
| 20 | 2025 | 7 |
About Minmin Ai
Minmin Ai is a scholar working on Food Science, Animal Science and Zoology, Molecular Biology, Materials Chemistry and Nutrition and Dietetics, having authored 32 papers that have together received 862 indexed citations. Recurring topics across this work include Proteins in Food Systems (28 papers), Microencapsulation and Drying Processes (14 papers), Meat and Animal Product Quality (9 papers), Protein Hydrolysis and Bioactive Peptides (8 papers), Pickering emulsions and particle stabilization (7 papers), Polysaccharides Composition and Applications (5 papers), Food composition and properties (4 papers) and Biochemical effects in animals (3 papers). The work is most often cited by research in Food Science (664 citations), Animal Science and Zoology (228 citations), Nutrition and Dietetics (144 citations), Biotechnology (39 citations) and Biomaterials (53 citations). Minmin Ai has collaborated with scholars based in China, Hong Kong and Japan. Frequent co-authors include Aimin Jiang, Shanguang Guo, Nan Xiao, Yuanyuan Cao, Quan Zhou, Hong Fan, Ting Tang, Nan Xiao, Xingguo Tian and Zheng Zhang. Their work appears in journals such as Food Hydrocolloids, Food Chemistry, Food Research International, LWT 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.