Shi‐Xia Liu
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- Data Visualization and Analytics 64
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- Magnetism in coordination complexes 102
- Organic and Molecular Conductors Research 70
- Artificial Intelligence top 0.2%
- Computational Mathematics top 2%
- Statistical and Nonlinear Physics top 0.5%
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- Molecular Junctions and Nanostructures 46
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- Lanthanide and Transition Metal Complexes 33
- Porphyrin and Phthalocyanine Chemistry 28
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- Metal-Organic Frameworks: Synthesis and Applications 29
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- Surface Chemistry and Catalysis 29
- Cited by
- Computer Vision and Pattern RecognitionElectronic, Optical and Magnetic MaterialsArtificial Intelligence
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Journal of the American Chemical Society (5 papers)Physical Review Letters (2 papers)
- Partner nations
- SwitzerlandChinaUnited States
In The Last Decade
Shi‐Xia Liu
361 papers receiving 11.7k citations
Hit Papers
Peers
Comparison fields: 5 of 199
- Computer Vision and Pattern Recognition 3.3k
- Electronic, Optical and Magnetic Materials 2.2k
- Artificial Intelligence 2.8k
- Computational Mathematics 51
- Statistical and Nonlinear Physics 915
Countries citing papers authored by Shi‐Xia Liu
This map shows the geographic impact of Shi‐Xia Liu'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 Shi‐Xia Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shi‐Xia Liu more than expected).
Fields of papers citing papers by Shi‐Xia Liu
This network shows the impact of papers produced by Shi‐Xia Liu. 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 Shi‐Xia Liu. The network helps show where Shi‐Xia Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shi‐Xia Liu, 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 | 2024 | 30 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 9 | |
| 6 | 2022 | 34 | |
| 7 | 2022 | 7 | |
| 8 | 2021 | 4 | |
| 9 | 2020 | 123 | |
| 10 | 2020 | 5 | |
| 11 | 2020 | 4 | |
| 12 | 2019 | 9 | |
| 13 | 2019 | 15 | |
| 14 | 2018 | 7 | |
| 15 | 2018 | 1 | |
| 16 | 2017 | 12 | |
| 17 | 2017 | 25 | |
| 18 | 2017 | 5 | |
| 19 | 2015 | 29 | |
| 20 | 2007 | 166 |
About Shi‐Xia Liu
Shi‐Xia Liu is a scholar working on Electronic, Optical and Magnetic Materials, Computer Vision and Pattern Recognition and Inorganic Chemistry, having authored 366 papers that have together received 12.0k indexed citations. Recurring topics across this work include Magnetism in coordination complexes (102 papers), Organic and Molecular Conductors Research (70 papers), Data Visualization and Analytics (64 papers), Molecular Junctions and Nanostructures (46 papers), Lanthanide and Transition Metal Complexes (33 papers), Metal-Organic Frameworks: Synthesis and Applications (29 papers), Surface Chemistry and Catalysis (29 papers) and Porphyrin and Phthalocyanine Chemistry (28 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.3k citations), Electronic, Optical and Magnetic Materials (2.2k citations) and Artificial Intelligence (2.8k citations). Shi‐Xia Liu has collaborated with scholars based in Switzerland, China and United States. Frequent co-authors include Silvio Decurtins, Yingcai Wu, Mengchen Liu, Weiwei Cui, Jun Zhu, Yangqiu Song, A. Neels, Huamin Qu, Furu Wei and Xiting Wang. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Physical Review Letters.
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.