Fangxi Wang
Impact in
- Biomaterials top 10%
- Magnesium Alloys: Properties and Applications
- Mechanical Engineering top 10%
- Aluminum Alloys Composites Properties
Papers in
-
- Microstructure and mechanical properties 5
- Machine Learning in Materials Science 2
- Hydrogen Storage and Materials 2
- Nuclear Materials and Properties 1
-
- Aluminum Alloys Composites Properties 6
- Co-authors
- Peng Chen (6 shared papers)Bin Li (3 shared papers)Bin Li (1 shared paper)Sanket A. Deshmukh (5 shared papers)Bin Li (2 shared papers)Samrendra Singh (2 shared papers)Soumil Y. Joshi (1 shared paper)Karteek K. Bejagam (1 shared paper)
- Journals
- Computational Materials Science (2 papers)Acta Materialia (2 papers)Journal of Chemical Theory and Computation (2 papers)Acta Metallurgica Sinica (English Letters) (1 paper)Scientific Reports (1 paper)
- Partner nations
- United StatesChinaRussia
In The Last Decade
Fangxi Wang
16 papers receiving 324 citations
Peers
Comparison fields: 5 of 41
- Biomaterials 157
- Mechanical Engineering 196
- Materials Chemistry 228
- Mechanics of Materials 62
- Metals and Alloys 5
Countries citing papers authored by Fangxi Wang
This map shows the geographic impact of Fangxi Wang'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 Fangxi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fangxi Wang more than expected).
Fields of papers citing papers by Fangxi Wang
This network shows the impact of papers produced by Fangxi Wang. 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 Fangxi Wang. The network helps show where Fangxi Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Fangxi Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 80 | |
| 2 | 2019 | 57 | |
| 3 | 2018 | 39 | |
| 4 | 2023 | 37 | |
| 5 | 2023 | 21 | |
| 6 | 2019 | 20 | |
| 7 | 2018 | 19 | |
| 8 | 2019 | 16 | |
| 9 | 2022 | 14 | |
| 10 | 2018 | 13 | |
| 11 | 2025 | 5 | |
| 12 | 2022 | 4 | |
| 13 | 2023 | 3 | |
| 14 | 2024 | 2 | |
| 15 | 2025 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2025 | 0 |
About Fangxi Wang
Fangxi Wang is a scholar working on Materials Chemistry, Mechanical Engineering, Biomaterials, Aerospace Engineering and Biomedical Engineering, having authored 17 papers that have together received 332 indexed citations. Recurring topics across this work include Magnesium Alloys: Properties and Applications (8 papers), Aluminum Alloys Composites Properties (6 papers), Microstructure and mechanical properties (5 papers), Aluminum Alloy Microstructure Properties (2 papers), Machine Learning in Materials Science (2 papers), Metal-Organic Frameworks: Synthesis and Applications (2 papers), Hydrogen Storage and Materials (2 papers) and Nuclear Materials and Properties (1 paper). The work is most often cited by research in Biomaterials (157 citations), Mechanical Engineering (196 citations), Materials Chemistry (228 citations), Mechanics of Materials (62 citations) and Metals and Alloys (5 citations). Fangxi Wang has collaborated with scholars based in United States, China and Russia. Frequent co-authors include Peng Chen, Bin Li, Bin Li, Sanket A. Deshmukh, Bin Li, Samrendra Singh, Soumil Y. Joshi, Karteek K. Bejagam, Hongwei Wang and Kolan Madhav Reddy. Their work appears in journals such as Computational Materials Science, Acta Materialia, Journal of Chemical Theory and Computation, Acta Metallurgica Sinica (English Letters) and Scientific Reports.
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.