Yujun Tao
- Molecular Biology
- Renewable Energy, Sustainability and the Environment top 10%
- Computational Theory and Mathematics top 5%
- Materials Chemistry
- Atomic and Molecular Physics, and Optics
- Co-authors
- Darrin M. YorkTimothy J. GieseHsu‐Chun TsaiTai‐Sung LeeChengwu ZhangAifen LiYuanming ZhangCharles Lin
- Topics
- Protein Structure and Dynamics (8 papers)Machine Learning in Materials Science (5 papers)Spectroscopy and Quantum Chemical Studies (4 papers)
- Cited by
- Renewable Energy, Sustainability and the EnvironmentComputational Theory and MathematicsEnvironmental Chemistry
- Partner nations
- United StatesChinaGermany
In The Last Decade
Yujun Tao
11 papers receiving 591 citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Molecular Biology 307
- Renewable Energy, Sustainability and the Environment 177
- Computational Theory and Mathematics 155
- Materials Chemistry 137
- Atomic and Molecular Physics, and Optics 64
Countries citing papers authored by Yujun Tao
This map shows the geographic impact of Yujun Tao'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 Yujun Tao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yujun Tao more than expected).
Fields of papers citing papers by Yujun Tao
This network shows the impact of papers produced by Yujun Tao. 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 Yujun Tao. The network helps show where Yujun Tao may publish in the future.
Co-authorship network of co-authors of Yujun Tao
This figure shows the co-authorship network connecting the top 25 collaborators of Yujun Tao. A scholar is included among the top collaborators of Yujun Tao 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 Yujun Tao. Yujun Tao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 3 | |
| 3 | 10 | |
| 4 | 15 | |
| 5 | 17 | |
| 6 | 30 | |
| 7 | 0 | |
| 8 | Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discoverybreakdown → | 247 |
| 9 | 22 | |
| 10 | 44 | |
| 11 | 46 | |
| 12 | 167 |
About Yujun Tao
Yujun Tao is a scholar working on Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics and Molecular Biology, having authored 12 papers that have together received 609 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (8 papers), Machine Learning in Materials Science (5 papers) and Spectroscopy and Quantum Chemical Studies (4 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (177 citations), Computational Theory and Mathematics (155 citations) and Environmental Chemistry (53 citations). Yujun Tao has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Darrin M. York, Timothy J. Giese, Hsu‐Chun Tsai, Tai‐Sung Lee, Chengwu Zhang, Aifen Li, Yuanming Zhang, Charles Lin, Woody Sherman and Brian K. Radak. Their work appears in journals such as The Journal of Chemical Physics, The Journal of Physical Chemistry B and Bioresource 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.