Jun‐Jie Zhu

5.2k total citations · 4 hit papers
90 papers, 4.0k citations indexed

About

Jun‐Jie Zhu is a scholar working on Environmental Engineering, Materials Chemistry and Electrical and Electronic Engineering. According to data from OpenAlex, Jun‐Jie Zhu has authored 90 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Environmental Engineering, 19 papers in Materials Chemistry and 18 papers in Electrical and Electronic Engineering. Recurrent topics in Jun‐Jie Zhu's work include Electrochemical sensors and biosensors (7 papers), Air Quality Monitoring and Forecasting (7 papers) and Water resources management and optimization (7 papers). Jun‐Jie Zhu is often cited by papers focused on Electrochemical sensors and biosensors (7 papers), Air Quality Monitoring and Forecasting (7 papers) and Water resources management and optimization (7 papers). Jun‐Jie Zhu collaborates with scholars based in China, United States and Taiwan. Jun‐Jie Zhu's co-authors include Zhiyong Jason Ren, Meiqi Yang, Yuqing Miao, Nongyue He, Gang Yang, Wenhua Hou, Jingjing Zhang, Hao Zheng, Bowen Li and Lichun Ma and has published in prestigious journals such as Chemical Reviews, Environmental Science & Technology and PLoS ONE.

In The Last Decade

Jun‐Jie Zhu

87 papers receiving 3.9k citations

Hit Papers

Machine Learning: New Ideas and Tools in Environmental Sc... 2021 2026 2022 2024 2021 2022 2023 2023 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun‐Jie Zhu China 28 810 774 588 546 543 90 4.0k
Weifeng Liu China 32 752 0.9× 835 1.1× 894 1.5× 811 1.5× 592 1.1× 162 3.7k
Xuemei Wang China 40 1.1k 1.4× 558 0.7× 690 1.2× 429 0.8× 238 0.4× 309 5.9k
Xiaojing Zhang China 37 654 0.8× 622 0.8× 570 1.0× 280 0.5× 618 1.1× 206 4.1k
Xinyang Li China 35 1.4k 1.7× 1.4k 1.8× 759 1.3× 258 0.5× 346 0.6× 190 4.5k
Mengxue Li China 35 1.1k 1.4× 647 0.8× 745 1.3× 224 0.4× 177 0.3× 185 4.2k
Jue Wang China 41 1.7k 2.1× 1.9k 2.5× 399 0.7× 370 0.7× 400 0.7× 204 5.7k
Huan Chen China 36 619 0.8× 411 0.5× 736 1.3× 241 0.4× 217 0.4× 188 4.0k
Luyao Wang China 34 850 1.0× 636 0.8× 397 0.7× 229 0.4× 172 0.3× 255 4.0k
Venkataramana Gadhamshetty United States 31 675 0.8× 520 0.7× 324 0.6× 278 0.5× 642 1.2× 104 2.7k
Qiang Xue China 39 1.1k 1.3× 863 1.1× 860 1.5× 462 0.8× 502 0.9× 266 6.1k

Countries citing papers authored by Jun‐Jie Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Jun‐Jie Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun‐Jie Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Jun‐Jie Zhu. A scholar is included among the top collaborators of Jun‐Jie Zhu 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‐Jie Zhu. Jun‐Jie Zhu 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.
Song, Cuihong, Jun‐Jie Zhu, Hongming Yi, et al.. (2025). Comprehensive assessment of the contribution of wastewater treatment to urban greenhouse gas and ammonia emissions. Nature Water. 3(10). 1114–1124. 1 indexed citations
2.
Zhang, Jianrong, et al.. (2025). Bioapplications of Cell Membrane Engineering with DNA Nanotechnology. ChemBioChem. 26(10). e202500066–e202500066.
3.
Yan, Yuqing, et al.. (2025). Methodology Discrepancy and Data Comparability of Greenhouse Gas Monitoring from Water Resource Recovery Facilities. Environmental Science & Technology. 59(25). 12567–12583.
4.
Wu, Chih‐Da, Jun‐Jie Zhu, Chin-Yu Hsu, & Ruei‐Hao Shie. (2024). Quantifying source contributions to ambient NH3 using Geo-AI with time lag and parcel tracking functions. Environment International. 185. 108520–108520. 8 indexed citations
5.
Song, Cuihong, et al.. (2024). Oversimplification and misestimation of nitrous oxide emissions from wastewater treatment plants. Nature Sustainability. 7(10). 1348–1358. 42 indexed citations
6.
Falinski, Mark M., et al.. (2023). Underestimation of Sector-Wide Methane Emissions from United States Wastewater Treatment. Environmental Science & Technology. 57(10). 4082–4090. 45 indexed citations
9.
Zhu, Jun‐Jie & Zhiyong Jason Ren. (2023). The evolution of research in resources, conservation & recycling revealed by Word2vec-enhanced data mining. Resources Conservation and Recycling. 190. 106876–106876. 21 indexed citations
10.
Schneider, Mariane Yvonne, Sina Borzooei, Andreas Froemelt, et al.. (2022). Hybrid modelling of water resource recovery facilities: status and opportunities. Water Science & Technology. 85(9). 2503–2524. 47 indexed citations
11.
Zhu, Jun‐Jie, et al.. (2022). Adaptive soft sensing of river flow prediction for wastewater treatment operation and risk management. Water Research. 220. 118714–118714. 11 indexed citations
12.
13.
Anderson, Paul, et al.. (2020). Margin of Safety in TMDLs: Natural Language Processing-Aided Review of the State of Practice. Journal of Hydrologic Engineering. 25(4). 10 indexed citations
14.
Zhu, Jun‐Jie, Linbo Wu, Zhiyang Bu, Suyun Jie, & Bo‐Geng Li. (2019). Polyethylenimine-Grafted HKUST-Type MOF/PolyHIPE Porous Composites (PEI@PGD-H) as Highly Efficient CO2 Adsorbents. Industrial & Engineering Chemistry Research. 58(10). 4257–4266. 55 indexed citations
15.
Zhu, Jun‐Jie, Lulu Kang, & Paul Anderson. (2017). Predicting influent biochemical oxygen demand: Balancing energy demand and risk management. Water Research. 128. 304–313. 52 indexed citations
16.
Zhou, Shiwei, Yingying Wang, Ming Zhao, Liping Jiang, & Jun‐Jie Zhu. (2015). CdSeTe@CdS@ZnS Quantum‐Dot‐Sensitized Macroporous Tio2 Film: A Multisignal‐Amplified Photoelectrochemical Platform. ChemPhysChem. 16(13). 2826–2835. 15 indexed citations
17.
Bian, Mingming, Jun‐Jie Zhu, Cheng Hu, & Teng Long. (2014). The analysis of the ionospheric scintillation effects on the GEO SAR imaging. 1–4. 2 indexed citations
18.
Du, Xiaoping, et al.. (2013). Vertical Accuracy Assessment of SRTM and ASTER GDEM over Typical Regions of China Using ICESat/GLAS. Earth Science(Journal of China University of Geosciences). 38(4). 12 indexed citations
19.
Abulizi, Abulikemu, Kenji Okitsu, & Jun‐Jie Zhu. (2013). Ultrasound assisted reduction of graphene oxide to graphene in l-ascorbic acid aqueous solutions: Kinetics and effects of various factors on the rate of graphene formation. Ultrasonics Sonochemistry. 21(3). 1174–1181. 64 indexed citations
20.
Liu, Yuge, Jingjing Zhang, Wenhua Hou, & Jun‐Jie Zhu. (2008). A Pd/SBA-15 composite: synthesis, characterization and protein biosensing. Nanotechnology. 19(13). 135707–135707. 36 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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