Long Gu

34 papers receiving 1.8k citations

Long Gu's Hit Papers

Self-assembled single-atom nanozyme for enhanced photodynamic therapy treatment of tumor 2020 · 487 citations
4870+2+4Years since publication100200300400

Peers

Long Gu
Comparison fields: 5 of 114
  • Inorganic Chemistry 405
  • Renewable Energy, Sustainability and the Environment 460
  • Materials Chemistry 1.2k
  • Biomedical Engineering 614
  • Neurology 53
Replace Jia‐Run Huang with:
Jia‐Run Huang China
Chuan‐Wan Wei China
Yanjing Wang China
Goutam Chandra India
Haile Liu China
Zhaowei Sun China
Huaiying Zhang United States
Lulu Zhou China
Long Gu relative to Jia‐Run Huang China Jia‐Run Huang's profile →
Citations per field
00.5×10×20×30×
Jia‐Run Huang · 1×
Citations per year

Countries citing papers authored by Long Gu

Since Specialization
Citations

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

Fields of papers citing papers by Long Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Long Gu, 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 Long Gu Line = papers co-authored together Long Gu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Self-assembled single-atom nanozyme for enhanced photodynamic therapy treatment of tumor
Hit paper breakdown →
2020487
2
Integrating Suitable Linkage of Covalent Organic Frameworks into Covalently Bridged Inorganic/Organic Hybrids toward Efficient Photocatalysis
Hit paper breakdown →
2020444
3 2020250
4 2020153
5 2016100
6 202094
7 201753
8 201552
9 202040
10 202232
11 201925
12 200214
13 201612
14 202310
15 202110
16 20089
17 20249
18 20069
19 20218
20 20027

About Long Gu

Long Gu is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Neurology, Materials Chemistry and Biomedical Engineering, having authored 35 papers that have together received 1.9k indexed citations. Recurring topics across this work include Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Nanoplatforms for cancer theranostics (4 papers), Metal-Organic Frameworks: Synthesis and Applications (3 papers), Advanced Nanomaterials in Catalysis (3 papers), Mitochondrial Function and Pathology (3 papers), Cyclopropane Reaction Mechanisms (2 papers), Advanced Photocatalysis Techniques (2 papers) and Spectroscopy and Laser Applications (2 papers). The work is most often cited by research in Inorganic Chemistry (405 citations), Renewable Energy, Sustainability and the Environment (460 citations), Materials Chemistry (1.2k citations), Biomedical Engineering (614 citations) and Neurology (53 citations). Long Gu has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Yanli Zhao, Dongdong Wang, Cheng Qian, Hongzhong Chen, Huihui Wu, Zhen Guo, Hou Wang, Weiqiang Zhou, Hongwei Wu and Guofeng Liu. Their work appears in journals such as Journal of the American Chemical Society, Journal of Neurochemistry, Chemical Communications, Organic Letters and Journal of Optics.

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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