Jun Cao
Impact in
- Applied Mathematics top 5%
- Advanced Harmonic Analysis Research
- Mathematical Physics top 5%
- Advanced Mathematical Physics Problems
Papers in
-
- Tribology and Wear Analysis 19
- Metal and Thin Film Mechanics 12
-
- Lubricants and Their Additives 9
- Co-authors
- Dachun Yang (14 shared papers)Ming Song (5 shared papers)H. Huang (9 shared papers)Zhongwei Yin (5 shared papers)Der‐Chen Chang (6 shared papers)Sibei Yang (5 shared papers)Xinbo Wang (2 shared papers)Kangyu Wang (2 shared papers)
- Journals
- Tribology International (6 papers)Transactions of the American Mathematical Society (2 papers)Journal of Macromolecular Science Part B (2 papers)Aerospace Science and Technology (2 papers)Surface and Coatings Technology (1 paper)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Jun Cao
71 papers receiving 623 citations
Peers
Comparison fields: 5 of 65
- Applied Mathematics 154
- Mathematical Physics 126
- Mechanics of Materials 213
- Modeling and Simulation 38
- Statistical and Nonlinear Physics 73
Countries citing papers authored by Jun Cao
This map shows the geographic impact of Jun Cao'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 Jun Cao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Cao more than expected).
Fields of papers citing papers by Jun Cao
This network shows the impact of papers produced by Jun Cao. 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 Jun Cao. The network helps show where Jun Cao may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Cao, 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 75 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 48 | |
| 2 | 2024 | 41 | |
| 3 | 2020 | 27 | |
| 4 | 2017 | 25 | |
| 5 | 2013 | 23 | |
| 6 | 2011 | 22 | |
| 7 | 2019 | 20 | |
| 8 | 2010 | 19 | |
| 9 | 2010 | 19 | |
| 10 | 2017 | 19 | |
| 11 | 2020 | 17 | |
| 12 | 2016 | 17 | |
| 13 | 2016 | 17 | |
| 14 | 2022 | 17 | |
| 15 | 2023 | 16 | |
| 16 | 2022 | 16 | |
| 17 | 2022 | 14 | |
| 18 | 2017 | 14 | |
| 19 | 2020 | 14 | |
| 20 | 2015 | 12 |
About Jun Cao
Jun Cao is a scholar working on Mechanics of Materials, Mechanical Engineering, Applied Mathematics, Mathematical Physics and Materials Chemistry, having authored 75 papers that have together received 649 indexed citations. Recurring topics across this work include Tribology and Wear Analysis (19 papers), Advanced Harmonic Analysis Research (18 papers), Metal and Thin Film Mechanics (12 papers), Nonlinear Partial Differential Equations (10 papers), Lubricants and Their Additives (9 papers), Advanced Mathematical Physics Problems (8 papers), Diamond and Carbon-based Materials Research (6 papers) and Nonlinear Photonic Systems (5 papers). The work is most often cited by research in Applied Mathematics (154 citations), Mathematical Physics (126 citations), Mechanics of Materials (213 citations), Modeling and Simulation (38 citations) and Statistical and Nonlinear Physics (73 citations). Jun Cao has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Dachun Yang, Ming Song, H. Huang, Zhongwei Yin, Der‐Chen Chang, Sibei Yang, Xinbo Wang, Kangyu Wang, Xinquan Wang and Shuxin Li. Their work appears in journals such as Tribology International, Transactions of the American Mathematical Society, Journal of Macromolecular Science Part B, Aerospace Science and Technology and Surface and Coatings Technology.
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.