Weiang Yan
Impact in
- Aging top 10%
- Materials Chemistry top 10%
- MXene and MAX Phase Materials
- 2D Materials and Applications
- Graphene research and applications
Papers in
-
- MXene and MAX Phase Materials 12
- Advanced Nanomaterials in Catalysis 4
- Surgery 11
- Tissue Engineering and Regenerative Medicine 3
- Co-authors
- Sanjiv Dhingra (24 shared papers)Alireza Rafieerad (16 shared papers)Glen Lester Sequiera (9 shared papers)Niketa Sareen (10 shared papers)Ahmad Amiri (6 shared papers)Ejlal Abu‐El‐Rub (7 shared papers)Keshav Narayan Alagarsamy (10 shared papers)Meenal Moudgil (5 shared papers)
- Journals
- Advanced Functional Materials (5 papers)Current Opinion in Cardiology (5 papers)The FASEB Journal (2 papers)Advanced Healthcare Materials (2 papers)Cell Death and Disease (2 papers)
- Partner nations
- CanadaUnited StatesIndia
In The Last Decade
Weiang Yan
34 papers receiving 848 citations
Peers
Comparison fields: 5 of 88
- Aging 29
- Materials Chemistry 484
- Biomedical Engineering 348
- Biomaterials 94
- Genetics 56
Countries citing papers authored by Weiang Yan
This map shows the geographic impact of Weiang Yan'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 Weiang Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiang Yan more than expected).
Fields of papers citing papers by Weiang Yan
This network shows the impact of papers produced by Weiang Yan. 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 Weiang Yan. The network helps show where Weiang Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Weiang Yan, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 165 | |
| 2 | 2021 | 111 | |
| 3 | 2021 | 85 | |
| 4 | 2021 | 59 | |
| 5 | 2019 | 56 | |
| 6 | 2020 | 54 | |
| 7 | 2019 | 43 | |
| 8 | 2010 | 34 | |
| 9 | 2019 | 29 | |
| 10 | 2019 | 29 | |
| 11 | 2022 | 26 | |
| 12 | 2022 | 23 | |
| 13 | 2022 | 19 | |
| 14 | 2021 | 18 | |
| 15 | 2020 | 18 | |
| 16 | 2022 | 14 | |
| 17 | 2020 | 14 | |
| 18 | 2020 | 13 | |
| 19 | 2019 | 13 | |
| 20 | 2020 | 11 |
About Weiang Yan
Weiang Yan is a scholar working on Materials Chemistry, Surgery, Biomedical Engineering, Molecular Biology and Genetics, having authored 36 papers that have together received 856 indexed citations. Recurring topics across this work include MXene and MAX Phase Materials (12 papers), Graphene and Nanomaterials Applications (8 papers), Mesenchymal stem cell research (7 papers), Advanced Nanomaterials in Catalysis (4 papers), Cardiac Valve Diseases and Treatments (3 papers), Electrospun Nanofibers in Biomedical Applications (3 papers), Tissue Engineering and Regenerative Medicine (3 papers) and Cardiac Fibrosis and Remodeling (3 papers). The work is most often cited by research in Aging (29 citations), Materials Chemistry (484 citations), Biomedical Engineering (348 citations), Biomaterials (94 citations) and Genetics (56 citations). Weiang Yan has collaborated with scholars based in Canada, United States and India. Frequent co-authors include Sanjiv Dhingra, Alireza Rafieerad, Glen Lester Sequiera, Niketa Sareen, Ahmad Amiri, Ejlal Abu‐El‐Rub, Keshav Narayan Alagarsamy, Meenal Moudgil, Rakesh C. Arora and Abhay Srivastava. Their work appears in journals such as Advanced Functional Materials, Current Opinion in Cardiology, The FASEB Journal, Advanced Healthcare Materials and Cell Death and Disease.
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.