Qianxiang Ai
- Electrical and Electronic Engineering
- Materials Chemistry
- Organic Chemistry
- Polymers and Plastics top 10%
- Electronic, Optical and Magnetic Materials
- Co-authors
- Chad RiskoJohn E. AnthonyOana D. JurchescuKarol JarolimekHu ChenIain McCullochKarl J. ThorleyMichael M. Haley
- Topics
- Organic Electronics and Photovoltaics (9 papers)Machine Learning in Materials Science (6 papers)Synthesis and Properties of Aromatic Compounds (5 papers)
- Cited by
- Polymers and PlasticsPhysical and Theoretical ChemistryElectrical and Electronic Engineering
- Partner nations
- United StatesUnited KingdomUkraine
In The Last Decade
Qianxiang Ai
25 papers receiving 546 citations
Peers
Comparison fields: 5 of 51
- Electrical and Electronic Engineering 299
- Materials Chemistry 232
- Organic Chemistry 136
- Polymers and Plastics 112
- Electronic, Optical and Magnetic Materials 60
Countries citing papers authored by Qianxiang Ai
This map shows the geographic impact of Qianxiang Ai'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 Qianxiang Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qianxiang Ai more than expected).
Fields of papers citing papers by Qianxiang Ai
This network shows the impact of papers produced by Qianxiang Ai. 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 Qianxiang Ai. The network helps show where Qianxiang Ai may publish in the future.
Co-authorship network of co-authors of Qianxiang Ai
This figure shows the co-authorship network connecting the top 25 collaborators of Qianxiang Ai. A scholar is included among the top collaborators of Qianxiang Ai 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 Qianxiang Ai. Qianxiang Ai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 14 | |
| 3 | 9 | |
| 4 | 7 | |
| 5 | 3 | |
| 6 | 4 | |
| 7 | 9 | |
| 8 | 7 | |
| 9 | 77 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | 36 | |
| 13 | 1 | |
| 14 | 51 | |
| 15 | 23 | |
| 16 | 55 | |
| 17 | 1 | |
| 18 | 27 | |
| 19 | 23 | |
| 20 | 5 |
About Qianxiang Ai
Qianxiang Ai is a scholar working on Catalysis, Physical and Theoretical Chemistry and Organic Chemistry, having authored 25 papers that have together received 548 indexed citations. Recurring topics across this work include Organic Electronics and Photovoltaics (9 papers), Machine Learning in Materials Science (6 papers) and Synthesis and Properties of Aromatic Compounds (5 papers). The work is most often cited by research in Polymers and Plastics (112 citations), Physical and Theoretical Chemistry (51 citations) and Electrical and Electronic Engineering (299 citations). Qianxiang Ai has collaborated with scholars based in United States, United Kingdom and Ukraine. Frequent co-authors include Chad Risko, John E. Anthony, Oana D. Jurchescu, Karol Jarolimek, Hu Chen, Iain McCulloch, Karl J. Thorley, Michael M. Haley, Sean Parkin and Simon Dowland. Their work appears in journals such as Journal of the American Chemical Society, Advanced Materials 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.