Jia-An Yan
- Materials Chemistry top 2%
- Graphene research and applications 18
- 2D Materials and Applications 18
- MXene and MAX Phase Materials 8
- Thermal properties of materials 4
- Machine Learning in Materials Science 4
- Boron and Carbon Nanomaterials Research 4
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- Advanced Chemical Physics Studies 5
- Condensed Matter Physics top 10%
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- Graphene and Nanomaterials Applications 4
- Co-authors
- M. Y. ChouLucas WebsterLede XianWeidong RuanShan-Ying WangChong‐Yu WangShang‐Peng GaoLi Yang
- Cited by
- Materials ChemistryElectronic, Optical and Magnetic MaterialsAtomic and Molecular Physics, and Optics
- Journals
- Physical Review B (16 papers)Physical review. B. (3 papers)The Journal of Physical Chemistry C (2 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Jia-An Yan
40 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Materials Chemistry 2.4k
- Electronic, Optical and Magnetic Materials 493
- Atomic and Molecular Physics, and Optics 594
- Electrical and Electronic Engineering 901
- Condensed Matter Physics 149
Countries citing papers authored by Jia-An Yan
This map shows the geographic impact of Jia-An Yan'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 Jia-An Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jia-An Yan more than expected).
Fields of papers citing papers by Jia-An Yan
This network shows the impact of papers produced by Jia-An Yan. 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 Jia-An Yan. The network helps show where Jia-An Yan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jia-An Yan, 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 | 2025 | 4 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 8 | |
| 5 | 2021 | 6 | |
| 6 | 2019 | 57 | |
| 7 | Structural, electronic and vibrational properties of few-layer 2H- and 1T-TaSe$_2$ | 2016 | 2 |
| 8 | 2016 | 9 | |
| 9 | 2016 | 41 | |
| 10 | 2016 | 36 | |
| 11 | 2015 | 42 | |
| 12 | 2015 | 142 | |
| 13 | 2015 | 55 | |
| 14 | 2011 | 17 | |
| 15 | 2010 | 17 | |
| 16 | 2010 | 341 | |
| 17 | 2009 | 456 | |
| 18 | 2008 | 2 | |
| 19 | 2004 | 125 | |
| 20 | 2004 | 19 |
About Jia-An Yan
Jia-An Yan is a scholar working on Materials Chemistry, Structural Biology and Atomic and Molecular Physics, and Optics, having authored 40 papers that have together received 2.8k indexed citations. Recurring topics across this work include Graphene research and applications (18 papers), 2D Materials and Applications (18 papers), MXene and MAX Phase Materials (8 papers), Advanced Chemical Physics Studies (5 papers), Thermal properties of materials (4 papers), Machine Learning in Materials Science (4 papers), Boron and Carbon Nanomaterials Research (4 papers) and Graphene and Nanomaterials Applications (4 papers). The work is most often cited by research in Materials Chemistry (2.4k citations), Electronic, Optical and Magnetic Materials (493 citations) and Atomic and Molecular Physics, and Optics (594 citations). Jia-An Yan has collaborated with scholars based in United States, China and Australia. Frequent co-authors include M. Y. Chou, Lucas Webster, Lede Xian, Weidong Ruan, Shan-Ying Wang, Chong‐Yu Wang, Shang‐Peng Gao, Li Yang, Salvador Barraza‐Lopez and Gaihua Ye. Their work appears in journals such as Physical Review B, Physical review. B., The Journal of Physical Chemistry C, ACS Nano and 2D Materials.
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.