Xiaoyan Fei

758 citations
32 papers · 618 · h-index 14

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Quantum Dots Synthesis And Properties
    • ZnO doping and properties
    • Copper-based nanomaterials and applications

Papers in

Xiaoyan Fei

30 papers receiving 611 citations

Peers

Xiaoyan Fei
Comparison fields: 5 of 108
  • Cancer Research 85
  • Materials Chemistry 193
  • Renewable Energy, Sustainability and the Environment 60
  • Artificial Intelligence 101
  • Electrical and Electronic Engineering 157
Replace Shengyi Chen with:
Shengyi Chen China
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Lingzhi Qu China
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Miao Dai China
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Citations per field
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Shengyi Chen · 1×
Citations per year

Countries citing papers authored by Xiaoyan Fei

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoyan Fei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoyan Fei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaoyan Fei Line = papers co-authored together Xiaoyan Fei links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202091
2 201783
3 201565
4 201965
5 201343
6 201434
7 201728
8 200725
9 202124
10 202122
11 202120
12 200819
13 201918
14 201515
15 202013
16 202210
17 200810
18 20186
19 20215
20 20195

About Xiaoyan Fei

Xiaoyan Fei is a scholar working on Materials Chemistry, Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering and Electronic, Optical and Magnetic Materials, having authored 32 papers that have together received 618 indexed citations. Recurring topics across this work include ZnO doping and properties (7 papers), Ga2O3 and related materials (5 papers), Gas Sensing Nanomaterials and Sensors (5 papers), Ultrasound Imaging and Elastography (3 papers), Photoacoustic and Ultrasonic Imaging (3 papers), Quantum Dots Synthesis And Properties (3 papers), Machine Learning and ELM (3 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Cancer Research (85 citations), Materials Chemistry (193 citations), Renewable Energy, Sustainability and the Environment (60 citations), Artificial Intelligence (101 citations) and Electrical and Electronic Engineering (157 citations). Xiaoyan Fei has collaborated with scholars based in China and United States. Frequent co-authors include Rongkuan Hu, Jun Shi, Shihui Ying, Jun Wang, Shuwang Duo, Tingzhi Liu, Zhongyi Hu, Yajie Zhang, Wenjie Hou and Liu Liu. Their work appears in journals such as Cancer Letters, Materials Letters, Materials Science in Semiconductor Processing, Superlattices and Microstructures and Acta Pharmacologica Sinica.

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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