Meiyan Wu

66 total papers · 2.1k total citations
54 papers, 1.8k citations indexed

About

Meiyan Wu is a scholar working on Biomaterials, Biomedical Engineering and Polymers and Plastics. According to data from OpenAlex, Meiyan Wu has authored 54 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Biomaterials, 15 papers in Biomedical Engineering and 10 papers in Polymers and Plastics. Recurrent topics in Meiyan Wu's work include Advanced Cellulose Research Studies (26 papers), Electrospun Nanofibers in Biomedical Applications (13 papers) and Nanocomposite Films for Food Packaging (13 papers). Meiyan Wu is often cited by papers focused on Advanced Cellulose Research Studies (26 papers), Electrospun Nanofibers in Biomedical Applications (13 papers) and Nanocomposite Films for Food Packaging (13 papers). Meiyan Wu collaborates with scholars based in China, United States and Canada. Meiyan Wu's co-authors include Bin Li, Chao Liu, Guang Yu, Haishun Du, Zhu Long, Youming Li, Changqing Liu, Yingying Liu, Yulong Sui and Fang Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACS Nano and Applied Physics Letters.

In The Last Decade

Meiyan Wu

53 papers receiving 1.7k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Meiyan Wu 1.1k 646 240 160 145 54 1.8k
Danilo M. dos Santos 876 0.8× 661 1.0× 203 0.8× 197 1.2× 141 1.0× 72 1.8k
Marco Beaumont 1.1k 1.0× 628 1.0× 168 0.7× 174 1.1× 184 1.3× 54 1.7k
Tobias Benselfelt 992 0.9× 509 0.8× 181 0.8× 180 1.1× 214 1.5× 36 1.5k
Mohammad Khorram 767 0.7× 581 0.9× 201 0.8× 186 1.2× 108 0.7× 66 2.0k
Seyed Omid Ranaei Siadat 872 0.8× 688 1.1× 257 1.1× 188 1.2× 98 0.7× 69 1.9k
W. Wagenknecht 1.1k 1.1× 653 1.0× 249 1.0× 115 0.7× 242 1.7× 40 1.7k
Zhu Long 799 0.7× 397 0.6× 245 1.0× 184 1.1× 109 0.8× 91 1.5k
Luís Alves 1.0k 1.0× 737 1.1× 170 0.7× 147 0.9× 220 1.5× 64 2.0k
Priyanka R. Sharma 1.2k 1.2× 512 0.8× 235 1.0× 223 1.4× 184 1.3× 44 1.9k
Beibei Ding 967 0.9× 578 0.9× 282 1.2× 263 1.6× 184 1.3× 52 2.1k

Countries citing papers authored by Meiyan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Meiyan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meiyan Wu

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

All Works

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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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