Jun Gao

436 papers receiving 11.8k citations

Peers

Jun Gao
Comparison fields: 5 of 151
  • Filtration and Separation 1.6k
  • Catalysis 2.8k
  • Process Chemistry and Technology 670
  • Fluid Flow and Transfer Processes 1.1k
  • Molecular Medicine 660
Replace Wolfgang Arlt with:
Wolfgang Arlt Germany
Sohrab Rohani Canada
Inas Muen AlNashef United Arab Emirates
Huizhou Liu China
Edward L Cussler United States
Jianji Wang China
João G. Crespo Portugal
Farouq Sabri Mjalli Oman
Xiangping Zhang China
Irina V. Smirnova Germany
Jun Gao relative to Wolfgang Arlt Germany Wolfgang Arlt's profile →
Citations per field
00.5×5×10×16.5×
Wolfgang Arlt · 1×
Citations per year

Countries citing papers authored by Jun Gao

Since Specialization
Citations

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

Fields of papers citing papers by Jun Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 457 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019336
2 2018240
3 2004184
4 2003182
5 2002147
6 2018127
7 2009115
8 2001113
9 2001110
10 2020110
11 2019106
12 2017104
13 2003101
14 200099
15 201896
16 201895
17 201993
18 202092
19 201792
20 199789

About Jun Gao

Jun Gao is a scholar working on Catalysis, Filtration and Separation, Fluid Flow and Transfer Processes, Mechanical Engineering and Control and Systems Engineering, having authored 457 papers that have together received 12.0k indexed citations. Recurring topics across this work include Ionic liquids properties and applications (109 papers), Process Optimization and Integration (85 papers), Chemical and Physical Properties in Aqueous Solutions (84 papers), Phase Equilibria and Thermodynamics (73 papers), Thermodynamic properties of mixtures (66 papers), Extraction and Separation Processes (61 papers), Advanced Control Systems Optimization (39 papers) and Crystallization and Solubility Studies (27 papers). The work is most often cited by research in Filtration and Separation (1.6k citations), Catalysis (2.8k citations), Process Chemistry and Technology (670 citations), Fluid Flow and Transfer Processes (1.1k citations) and Molecular Medicine (660 citations). Jun Gao has collaborated with scholars based in China, United States and France. Frequent co-authors include Master. Y. Wang, Dongmei Xu, Lianzheng Zhang, Zhaoyou Zhu, Yixin Ma, Peizhe Cui, Barbara J. Frisken, Zhishan Zhang, Zhibing Hu and Mengshuai Liu. Their work appears in journals such as Journal of Chemical & Engineering Data, The Journal of Chemical Thermodynamics, Separation and Purification Technology, Journal of Molecular Liquids and Process Safety and Environmental Protection.

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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