Gen-Que Fu

586 citations
12 papers · 543 · h-index 9

Impact in

  • Biomaterials top 10%
    • Advanced Cellulose Research Studies
    • Electrospun Nanofibers in Biomedical Applications
    • biodegradable polymer synthesis and properties
    • Nanocomposite Films for Food Packaging
    • Hydrogels: synthesis, properties, applications

Papers in

    • Advanced Cellulose Research Studies 7
    • Electrospun Nanofibers in Biomedical Applications 2
    • biodegradable polymer synthesis and properties 2
    • Nanocomposite Films for Food Packaging 2
    • Bamboo properties and applications 3

Gen-Que Fu

12 papers receiving 537 citations

Peers

Gen-Que Fu
Comparison fields: 5 of 99
  • Biomaterials 161
  • Molecular Medicine 50
  • Biomedical Engineering 186
  • Plant Science 120
  • Food Science 54
Replace Tae‐Hee Kim with:
Tae‐Hee Kim South Korea
Arkadiusz Orchel Poland
Lulu Niu China
Panpan Yue China
S. Chandranayaka India
Gregory J. Duns China
Wanpen Tachaboonyakiat Thailand
Anguo Teng China
Danica Zmejkoski Serbia
Raha Ahmad Raus Malaysia
Gen-Que Fu relative to Tae‐Hee Kim South Korea Tae‐Hee Kim's profile →
Citations per field
00.5×
Tae‐Hee Kim · 1×
Citations per year

Countries citing papers authored by Gen-Que Fu

Since Specialization
Citations

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

Fields of papers citing papers by Gen-Que Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gen-Que Fu. 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 Gen-Que Fu. The network helps show where Gen-Que Fu may publish in the future.

Co-authors

The 21 scholars most cited alongside Gen-Que Fu, 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 Gen-Que Fu Line = papers co-authored together Gen-Que Fu links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2017296
2 201444
3 202044
4 201830
5 201630
6 201628
7 201928
8 201915
9 201711
10 20188
11 20186
12 20183

About Gen-Que Fu

Gen-Que Fu is a scholar working on Biomaterials, Plant Science, Biomedical Engineering, Polymers and Plastics and Molecular Medicine, having authored 12 papers that have together received 543 indexed citations. Recurring topics across this work include Advanced Cellulose Research Studies (7 papers), Lignin and Wood Chemistry (3 papers), Bamboo properties and applications (3 papers), Biofuel production and bioconversion (3 papers), Electrospun Nanofibers in Biomedical Applications (2 papers), biodegradable polymer synthesis and properties (2 papers), Hydrogels: synthesis, properties, applications (2 papers) and Nanocomposite Films for Food Packaging (2 papers). The work is most often cited by research in Biomaterials (161 citations), Molecular Medicine (50 citations), Biomedical Engineering (186 citations), Plant Science (120 citations) and Food Science (54 citations). Gen-Que Fu has collaborated with scholars based in China. Frequent co-authors include Feng Peng, Run‐Cang Sun, Panpan Yue, Mingfei Li, Yajie Hu, Changxia Sun, Jing Bian, Chunli Yao, Gegu Chen and Yongfeng Hu. Their work appears in journals such as Scientific Reports, Journal of Agricultural and Food Chemistry, International Journal of Biological Macromolecules, Cellulose and RSC Advances.

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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