Mingyuan Xu
- Materials Chemistry top 10%
- Biomedical Engineering top 10%
- Renewable Energy, Sustainability and the Environment top 5%
- Electrical and Electronic Engineering
- Catalysis top 5%
- Co-authors
- Tong ZhuJohn Z. H. ZhangMengqing GuoLiang‐Shih FanJinzhe ZengLiqun CaoLang QinJonathan A. Fan
- Topics
- Computational Drug Discovery Methods (13 papers)Protein Structure and Dynamics (12 papers)Machine Learning in Materials Science (10 papers)
- Journals
- Journal of the American Chemical SocietyNature CommunicationsSHILAP Revista de lepidopterología
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Mingyuan Xu
42 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 118
- Materials Chemistry 667
- Biomedical Engineering 420
- Renewable Energy, Sustainability and the Environment 359
- Electrical and Electronic Engineering 253
- Catalysis 194
Countries citing papers authored by Mingyuan Xu
This map shows the geographic impact of Mingyuan Xu'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 Mingyuan Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyuan Xu more than expected).
Fields of papers citing papers by Mingyuan Xu
This network shows the impact of papers produced by Mingyuan Xu. 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 Mingyuan Xu. The network helps show where Mingyuan Xu may publish in the future.
Co-authorship network of co-authors of Mingyuan Xu
This figure shows the co-authorship network connecting the top 25 collaborators of Mingyuan Xu. A scholar is included among the top collaborators of Mingyuan Xu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mingyuan Xu. Mingyuan Xu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 17 | |
| 7 | 1 | |
| 8 | 38 | |
| 9 | 4 | |
| 10 | 3 | |
| 11 | 18 | |
| 12 | 3 | |
| 13 | 9 | |
| 14 | 13 | |
| 15 | 13 | |
| 16 | 4 | |
| 17 | 189 | |
| 18 | 14 | |
| 19 | 23 | |
| 20 | 7 |
About Mingyuan Xu
Mingyuan Xu is a scholar working on Computational Theory and Mathematics, Catalysis and Renewable Energy, Sustainability and the Environment, having authored 45 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Protein Structure and Dynamics (12 papers) and Machine Learning in Materials Science (10 papers). The work is most often cited by research in Catalysis (194 citations), Renewable Energy, Sustainability and the Environment (359 citations) and Materials Chemistry (667 citations). Mingyuan Xu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Tong Zhu, John Z. H. Zhang, Mengqing Guo, Liang‐Shih Fan, Jinzhe Zeng, Liqun Cao, Lang Qin, Jonathan A. Fan, Zhuo Cheng and Luting Yan. Their work appears in journals such as Journal of the American Chemical Society, Nature Communications and SHILAP Revista de lepidopterología.
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.