Fei Yan

4.7k total citations · 3 hit papers
60 papers, 2.9k citations indexed

About

Fei Yan is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Mechanical Engineering. According to data from OpenAlex, Fei Yan has authored 60 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Atomic and Molecular Physics, and Optics, 35 papers in Artificial Intelligence and 8 papers in Mechanical Engineering. Recurrent topics in Fei Yan's work include Quantum Information and Cryptography (34 papers), Quantum and electron transport phenomena (29 papers) and Quantum Computing Algorithms and Architecture (23 papers). Fei Yan is often cited by papers focused on Quantum Information and Cryptography (34 papers), Quantum and electron transport phenomena (29 papers) and Quantum Computing Algorithms and Architecture (23 papers). Fei Yan collaborates with scholars based in China, United States and Japan. Fei Yan's co-authors include Simon Gustavsson, William D. Oliver, Terry P. Orlando, Fumiki Yoshihara, Jonas Bylander, Yasunobu Nakamura, David G. Cory, K. Harrabi, George Fitch and Jaw Shen Tsai and has published in prestigious journals such as Nature, Physical Review Letters and Nature Communications.

In The Last Decade

Fei Yan

57 papers receiving 2.9k citations

Hit Papers

Noise spectroscopy through dynamical decoupling with a su... 2011 2026 2016 2021 2011 2016 2023 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fei Yan China 27 2.1k 1.9k 354 272 233 60 2.9k
Tomohiro Taniguchi Japan 31 2.1k 1.0× 439 0.2× 624 1.8× 104 0.4× 1.3k 5.4× 142 3.1k
M. Oestreich Germany 34 2.6k 1.2× 238 0.1× 679 1.9× 117 0.4× 1.5k 6.3× 119 3.6k
Yu He China 26 2.7k 1.3× 1.7k 0.9× 991 2.8× 76 0.3× 1.7k 7.5× 85 4.1k
Dohun Kim South Korea 25 1.5k 0.7× 447 0.2× 1.3k 3.6× 54 0.2× 895 3.8× 120 2.9k
Yi‐Tao Wang China 21 568 0.3× 324 0.2× 408 1.2× 260 1.0× 270 1.2× 82 1.4k
Linbo Shao United States 26 2.6k 1.3× 322 0.2× 740 2.1× 59 0.2× 2.4k 10.4× 66 3.6k
Yanfeng Zhang China 24 1.1k 0.5× 142 0.1× 489 1.4× 143 0.5× 999 4.3× 118 2.4k
Roland Brunner Austria 19 497 0.2× 175 0.1× 215 0.6× 171 0.6× 426 1.8× 84 1.2k
Takuro Fujii Japan 28 1.4k 0.7× 276 0.1× 597 1.7× 132 0.5× 2.7k 11.6× 283 3.5k

Countries citing papers authored by Fei Yan

Since Specialization
Citations

This map shows the geographic impact of Fei 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 Fei Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Yan more than expected).

Fields of papers citing papers by Fei Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fei 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 Fei Yan. The network helps show where Fei Yan may publish in the future.

Co-authorship network of co-authors of Fei Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Fei Yan. A scholar is included among the top collaborators of Fei Yan 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 Fei Yan. Fei Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dai, Shengtao, Fei Yan, Xuyang Li, et al.. (2024). Exploiting the neutralizer to optimize amide content in bio-based waterborne polyurethane sizing agent for enhancing the interfacial properties of CF/PA6 composites. Composites Communications. 48. 101961–101961. 4 indexed citations
2.
Yu, Haiyang, et al.. (2024). Mechanisms of surfactant improving water injection huff and puff efficiency in tight reservoir. Journal of Molecular Liquids. 413. 125992–125992. 1 indexed citations
3.
Yan, Fei, Shengtao Dai, Jintang Duan, et al.. (2024). Improving the interfacial properties of carbon fiber/low melting point PAEK composites by embellishing of bio-based PAEK sizing agent. Composites Science and Technology. 256. 110741–110741. 8 indexed citations
4.
Dai, Shengtao, Chang Yang, Fei Yan, et al.. (2024). Constructing an interaction in plant polyphenol-modified carbon fiber with amylopectin-based waterborne polyurethane sizing agent via hydrogen bonding to improve the interfacial performance of carbon fiber/nylon 6 composites. International Journal of Biological Macromolecules. 276(Pt 1). 133877–133877. 5 indexed citations
5.
Han, Zhikun, Yuxuan Zhou, Jiahao Yuan, et al.. (2024). Multilevel variational spectroscopy using a programmable quantum simulator. Physical Review Research. 6(1). 6 indexed citations
7.
Dai, Shengtao, Fei Yan, Jiaming Guo, et al.. (2023). A novel bio-based hyperbranched waterborne polyurethane sizing agent with superior UV-resistance and interfacial properties for CF/PA6 composites. Composites Science and Technology. 242. 110214–110214. 33 indexed citations
8.
Liu, Chuan‐Pu, Jilei Chen, Song Liu, et al.. (2023). Spin-wave-based tunable coupler between superconducting flux qubits. Physical review. A. 107(1). 3 indexed citations
9.
Hu, Chang-Kang, Jiawei Qiu, Yuxuan Zhou, et al.. (2023). Native Conditional iswap Operation with Superconducting Artificial Atoms. Physical Review Applied. 20(3). 6 indexed citations
10.
Li, Sai, Xiaowei Deng, Libo Zhang, et al.. (2023). Beating the break-even point with a discrete-variable-encoded logical qubit. Nature. 616(7955). 56–60. 111 indexed citations breakdown →
11.
Zhou, Yuxuan, Weiwei Wei, Libo Zhang, et al.. (2022). Engineering superconducting qubits to reduce quasiparticles and charge noise. Nature Communications. 13(1). 7196–7196. 43 indexed citations
12.
Gong, Meihua, et al.. (2022). A dopamine-methacrylated hyaluronic acid hydrogel as an effective carrier for stem cells in skin regeneration therapy. Cell Death and Disease. 13(8). 738–738. 36 indexed citations
13.
Sung, Youngkyu, F. Beaudoin, Leigh Norris, et al.. (2019). Non-Gaussian noise spectroscopy with a superconducting qubit sensor. Nature Communications. 10(1). 3715–3715. 61 indexed citations
14.
Wang, Joel I-Jan, Daniel Rodan‐Legrain, Landry Bretheau, et al.. (2018). Coherent control of a hybrid superconducting circuit made with graphene-based van der Waals heterostructures. Nature Nanotechnology. 14(2). 120–125. 121 indexed citations
16.
Yan, Fei, Philip Krantz, Youngkyu Sung, et al.. (2018). Tunable Coupling Scheme for Implementing High-Fidelity Two-Qubit Gates. Physical Review Applied. 10(5). 221 indexed citations
17.
Bretheau, Landry, Fei Yan, Morten Kjærgaard, et al.. (2018). Gate-tunable Transmon Qubit made with Graphene/hBN Heterostructures. Bulletin of the American Physical Society. 2018. 1 indexed citations
18.
Yan, Fei, Dan H. Campbell, Philip Krantz, et al.. (2018). Distinguishing Coherent and Thermal Photon Noise in a Circuit Quantum Electrodynamical System. Physical Review Letters. 120(26). 260504–260504. 55 indexed citations
19.
Yan, Fei, Simon Gustavsson, Archana Kamal, et al.. (2015). The Flux Qubit Revisited. arXiv (Cornell University). 4 indexed citations
20.
Jin, Xueying, Simon Gustavsson, Jonas Bylander, et al.. (2015). Z-Gate Operation on a Superconducting Flux Qubit via Its Readout SQUID. Physical Review Letters. 1 indexed citations

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.

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