Ya‐Fan Zhao
- Materials Chemistry top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Organic Chemistry top 5%
- Inorganic Chemistry top 2%
- Catalysis top 2%
- Topics
- Boron and Carbon Nanomaterials Research (11 papers)Boron Compounds in Chemistry (8 papers)Machine Learning in Materials Science (7 papers)
- Journals
- Journal of the American Chemical SocietyAngewandte Chemie International EditionNature Communications
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Ya‐Fan Zhao
40 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Materials Chemistry 3.0k
- Radiology, Nuclear Medicine and Imaging 839
- Organic Chemistry 696
- Inorganic Chemistry 550
- Catalysis 440
Countries citing papers authored by Ya‐Fan Zhao
This map shows the geographic impact of Ya‐Fan Zhao'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 Ya‐Fan Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ya‐Fan Zhao more than expected).
Fields of papers citing papers by Ya‐Fan Zhao
This network shows the impact of papers produced by Ya‐Fan Zhao. 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 Ya‐Fan Zhao. The network helps show where Ya‐Fan Zhao may publish in the future.
Co-authorship network of co-authors of Ya‐Fan Zhao
This figure shows the co-authorship network connecting the top 25 collaborators of Ya‐Fan Zhao. A scholar is included among the top collaborators of Ya‐Fan Zhao 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 Ya‐Fan Zhao. Ya‐Fan Zhao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 8 | |
| 3 | 7 | |
| 4 | 72 | |
| 5 | 10 | |
| 6 | 46 | |
| 7 | 12 | |
| 8 | A structural modeling approach to the solid-solution materials based on the similar atomic environment | 1 |
| 9 | A structural modeling approach to the solid-solution materials | 2 |
| 10 | 54 | |
| 11 | 12 | |
| 12 | 156 | |
| 13 | 50 | |
| 14 | 14 | |
| 15 | Planar hexagonal B36 as a potential basis for extended single-atom layer boron sheetsbreakdown → | 697 |
| 16 | Observation of an all-boron fullerenebreakdown → | 763 |
| 17 | 153 | |
| 18 | 13 | |
| 19 | 19 | |
| 20 | Innovation Ability of Knowledge Intensive Business Services Cluster on the Basis of Rough Set Theories | 0 |
About Ya‐Fan Zhao
Ya‐Fan Zhao is a scholar working on Materials Chemistry, Filtration and Separation and Catalysis, having authored 41 papers that have together received 3.7k indexed citations. Recurring topics across this work include Boron and Carbon Nanomaterials Research (11 papers), Boron Compounds in Chemistry (8 papers) and Machine Learning in Materials Science (7 papers). The work is most often cited by research in Process Chemistry and Technology (192 citations), Materials Chemistry (3.0k citations) and Catalysis (440 citations). Ya‐Fan Zhao has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Jun Li, Lai‐Sheng Wang, Wei‐Li Li, Han‐Shi Hu, Zachary A. Piazza, Si‐Dian Li, Qiang Chen, Hua‐Jin Zhai, Hui Bai and Wen‐Juan Tian. Their work appears in journals such as Journal of the American Chemical Society, Angewandte Chemie International Edition and Nature Communications.
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.