Jun Zhou

8.6k total citations
339 papers, 6.6k citations indexed

About

Jun Zhou is a scholar working on Molecular Biology, Electronic, Optical and Magnetic Materials and Electrical and Electronic Engineering. According to data from OpenAlex, Jun Zhou has authored 339 papers receiving a total of 6.6k indexed citations (citations by other indexed papers that have themselves been cited), including 107 papers in Molecular Biology, 98 papers in Electronic, Optical and Magnetic Materials and 96 papers in Electrical and Electronic Engineering. Recurrent topics in Jun Zhou's work include Gold and Silver Nanoparticles Synthesis and Applications (81 papers), Advanced biosensing and bioanalysis techniques (51 papers) and Photonic and Optical Devices (40 papers). Jun Zhou is often cited by papers focused on Gold and Silver Nanoparticles Synthesis and Applications (81 papers), Advanced biosensing and bioanalysis techniques (51 papers) and Photonic and Optical Devices (40 papers). Jun Zhou collaborates with scholars based in China, United States and Italy. Jun Zhou's co-authors include Tao Jiang, Xiurong Su, Chenjie Gu, Chenyang Lu, Lucia Petti, Ye Li, Jiaojiao Han, Ying Chen, Ming-Yang Chen and Guodong Wei and has published in prestigious journals such as Journal of the American Chemical Society, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Jun Zhou

331 papers receiving 6.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Zhou China 43 2.3k 2.3k 2.3k 1.7k 1.4k 339 6.6k
Yang Luo China 46 3.2k 1.4× 2.4k 1.1× 298 0.1× 1.5k 0.9× 879 0.6× 238 7.5k
Junichi Kato Japan 59 6.1k 2.7× 1.5k 0.7× 456 0.2× 1.1k 0.6× 578 0.4× 326 11.8k
Xiaojuan Wang China 44 1.6k 0.7× 1.0k 0.5× 579 0.3× 2.0k 1.2× 711 0.5× 262 7.0k
Yutaka Takagi Japan 40 1.1k 0.5× 779 0.3× 1.1k 0.5× 2.3k 1.4× 401 0.3× 223 5.7k
Chang Chen China 44 1.6k 0.7× 1.9k 0.8× 1.1k 0.5× 2.2k 1.3× 2.1k 1.4× 240 7.9k
Fei Chen China 38 1.4k 0.6× 1.7k 0.7× 397 0.2× 1.3k 0.8× 654 0.5× 274 5.3k
Chii‐Wann Lin Taiwan 38 2.2k 1.0× 2.3k 1.0× 452 0.2× 608 0.4× 1.0k 0.7× 231 5.4k
K.I. Arai Japan 41 1.6k 0.7× 792 0.4× 1.5k 0.7× 823 0.5× 1.8k 1.3× 464 7.5k
Thomas Henkel Germany 38 4.2k 1.8× 1.8k 0.8× 555 0.2× 232 0.1× 652 0.5× 129 10.6k
David J. Meyer United States 52 4.9k 2.2× 623 0.3× 768 0.3× 800 0.5× 1.2k 0.8× 225 9.6k

Countries citing papers authored by Jun Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Jun Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Zhou. A scholar is included among the top collaborators of Jun Zhou 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 Jun Zhou. Jun Zhou 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.
Zhou, Jun, Guangming Zhao, Xiangrui Meng, et al.. (2025). Dynamic characteristics and fracture morphology of two rocks with different length to diameter ratios. 44(9). 2379–2390. 1 indexed citations
2.
Jiang, Yu, et al.. (2025). The Role of Gut Microbiome in Temporomandibular Joint Disorder Pathogenesis. Journal of Dental Research. 104(11). 1257–1266.
3.
Zhang, Zhikang, Haojun Yuan, Min Li, et al.. (2024). Minute level ultra-rapid and thousand copies level high-sensitive pathogen nucleic acid identification based on contactless impedance detection microsensor. Talanta. 278. 126487–126487. 1 indexed citations
4.
Li, Guang, Liang Zhao, Lili Qiu, et al.. (2024). Decreased Amino Acid Transporter LAT2 Is the Main Determinant of Impaired Protein Utilization During Aging. Engineering. 42. 88–98. 4 indexed citations
5.
Cui, Yanan, et al.. (2024). Bonded Interface Shear Performance of a Double-Layer Asphalt Mixture Based on DIC Technology. Journal of Testing and Evaluation. 52(2). 853–872. 1 indexed citations
7.
Zhou, Lu, Ambra Vestri, Valentina Marchesano, et al.. (2023). The Label-Free Detection and Identification of SARS-CoV-2 Using Surface-Enhanced Raman Spectroscopy and Principal Component Analysis. Biosensors. 13(12). 1014–1014. 10 indexed citations
9.
Zhang, Jing, Jiaojiao Han, Tinghong Ming, et al.. (2022). Gut microbiome and metabolome analyses reveal the protective effect of special high‐docosahexaenoic acid tuna oil on d‐galactose‐induced aging in mice. Food Science & Nutrition. 10(11). 3814–3827. 8 indexed citations
10.
11.
Zhang, Jing, Jiaojiao Han, Tinghong Ming, et al.. (2020). Novel high‐docosahexaenoic‐acid tuna oil supplementation modulates gut microbiota and alleviates obesity in high‐fat diet mice. Food Science & Nutrition. 8(12). 6513–6527. 50 indexed citations
12.
Zhou, Jun, Chundan Zhang, Xuan Zhang, et al.. (2020). Immunomagnetic separation-based nanogold enhanced surface plasmon resonance and colloidal gold test strips for rapid detection of Vibrio parahaemolyticus. Archives of Microbiology. 202(5). 1025–1033. 9 indexed citations
13.
Han, Jiaojiao, Shasha Tang, Chenyang Lu, et al.. (2020). The novel peptides ICRD and LCGEC screened from tuna roe show antioxidative activity via Keap1/Nrf2-ARE pathway regulation and gut microbiota modulation. Food Chemistry. 327. 127094–127094. 66 indexed citations
14.
Jiang, Qinqin, Yan Wu, Xiaoting Qiu, et al.. (2020). Structure determination of ferritin from Dendrorhynchus zhejiangensis. Biochemical and Biophysical Research Communications. 531(2). 195–202. 8 indexed citations
15.
Han, Jiaojiao, Shasha Tang, Wei Bao, et al.. (2019). Comparisons of protective effects between two sea cucumber hydrolysates against diet induced hyperuricemia and renal inflammation in mice. Food & Function. 11(1). 1074–1086. 83 indexed citations
16.
Zhou, Jun, Jianshuo Zhang, Haitao Yang, et al.. (2019). Plasmon-induced hot electron transfer in Au–ZnO heterogeneous nanorods for enhanced SERS. Nanoscale. 11(24). 11782–11788. 41 indexed citations
17.
Jiang, Qinqin, Chenyang Lu, Tingting Sun, et al.. (2019). Alterations of the Brain Proteome and Gut Microbiota in d-Galactose-Induced Brain-Aging Mice with Krill Oil Supplementation. Journal of Agricultural and Food Chemistry. 67(35). 9820–9830. 18 indexed citations
18.
Zhang, Y., Yang Zhong, Jing Liu, et al.. (2019). Polydopamine-modified dual-ligand nanoparticles as highly effective and targeted magnetic resonance/photoacoustic dual-modality thrombus imaging agents. SHILAP Revista de lepidopterología. 1 indexed citations
19.
Zhang, Dijun, Jiaojiao Han, Yanyan Li, et al.. (2018). Tuna Oil Alleviates d-Galactose Induced Aging in Mice Accompanied by Modulating Gut Microbiota and Brain Protein Expression. Journal of Agricultural and Food Chemistry. 66(22). 5510–5520. 26 indexed citations
20.
Han, Jiaojiao, Shasha Tang, Yanyan Li, et al.. (2018). In silicoanalysis andin vivotests of the tuna dark muscle hydrolysate anti-oxidation effect. RSC Advances. 8(25). 14109–14119. 24 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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