Armin Ai
Impact in
- Biomaterials top 5%
- Electrospun Nanofibers in Biomedical Applications
- Silk-based biomaterials and applications
- Rehabilitation top 2%
- Wound Healing and Treatments
Papers in
-
- Electrospun Nanofibers in Biomedical Applications 9
- Surgery 8
- Tissue Engineering and Regenerative Medicine 7
- Co-authors
- Jafar Ai (16 shared papers)Somayeh Ebrahimi‐Barough (11 shared papers)Arash Goodarzi (8 shared papers)Shiva Asadpour (1 shared paper)Saeid Kargozar (1 shared paper)Hamed Nosrati (1 shared paper)Majid Salehi (3 shared papers)Lida Moradi (1 shared paper)
- Journals
- International Journal of Polymeric Materials (2 papers)Scientific Reports (1 paper)Molecular Neurobiology (1 paper)PLoS ONE (1 paper)International Journal of Biological Macromolecules (1 paper)
- Partner nations
- IranUnited StatesCanada
In The Last Decade
Armin Ai
21 papers receiving 741 citations
Peers
Comparison fields: 5 of 87
- Biomaterials 399
- Rehabilitation 146
- Developmental Neuroscience 40
- Genetics 79
- Cellular and Molecular Neuroscience 136
Countries citing papers authored by Armin Ai
This map shows the geographic impact of Armin 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 Armin Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Armin Ai more than expected).
Fields of papers citing papers by Armin Ai
This network shows the impact of papers produced by Armin 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 Armin Ai. The network helps show where Armin Ai may publish in the future.
Co-authors
The 25 scholars most cited alongside Armin 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 224 | |
| 2 | 2019 | 137 | |
| 3 | 2013 | 82 | |
| 4 | 2014 | 53 | |
| 5 | 2013 | 47 | |
| 6 | 2013 | 46 | |
| 7 | 2018 | 34 | |
| 8 | 2019 | 20 | |
| 9 | 2019 | 15 | |
| 10 | 2016 | 13 | |
| 11 | 2016 | 13 | |
| 12 | 2020 | 9 | |
| 13 | 2018 | 9 | |
| 14 | 2020 | 8 | |
| 15 | 2014 | 8 | |
| 16 | 2020 | 8 | |
| 17 | 2014 | 6 | |
| 18 | 2024 | 6 | |
| 19 | 2013 | 6 | |
| 20 | 2022 | 5 |
About Armin Ai
Armin Ai is a scholar working on Biomaterials, Surgery, Biomedical Engineering, Cellular and Molecular Neuroscience and Molecular Biology, having authored 21 papers that have together received 750 indexed citations. Recurring topics across this work include Electrospun Nanofibers in Biomedical Applications (9 papers), Bone Tissue Engineering Materials (8 papers), Tissue Engineering and Regenerative Medicine (7 papers), Nerve injury and regeneration (5 papers), Osteoarthritis Treatment and Mechanisms (2 papers), Wound Healing and Treatments (2 papers), Research on Leishmaniasis Studies (2 papers) and Mesenchymal stem cell research (2 papers). The work is most often cited by research in Biomaterials (399 citations), Rehabilitation (146 citations), Developmental Neuroscience (40 citations), Genetics (79 citations) and Cellular and Molecular Neuroscience (136 citations). Armin Ai has collaborated with scholars based in Iran, United States and Canada. Frequent co-authors include Jafar Ai, Somayeh Ebrahimi‐Barough, Arash Goodarzi, Shiva Asadpour, Saeid Kargozar, Hamed Nosrati, Majid Salehi, Lida Moradi, Saeed Farzamfar and Arian Ehterami. Their work appears in journals such as International Journal of Polymeric Materials, Scientific Reports, Molecular Neurobiology, PLoS ONE and International Journal of Biological Macromolecules.
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.