Jun Cai

4.1k citations
170 papers · 3.4k indexed · h-index 31

Jun Cai

164 papers receiving 3.3k citations

Peers

Jun Cai
Comparison fields: 5 of 138
  • Computational Mechanics 821
  • Fluid Flow and Transfer Processes 234
  • Biomaterials 409
  • Materials Chemistry 1.2k
  • Mechanical Engineering 777
Replace Matthias Kind with:
Matthias Kind Germany
Heike P. Schuchmann Germany
Antonello Barresi Italy
Hermann Nirschl Germany
Mark Simmons United Kingdom
Hua Wu Switzerland
Souvik Bhattacharyya India
B. Florence Scarlett Netherlands
Georgios D. Stefanidis Belgium
Quan Yuan China
Jun Cai relative to Matthias Kind Germany Matthias Kind's profile →
Citations per field
00.5×2.9×
Matthias Kind · 1×
Citations per year

Countries citing papers authored by Jun Cai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20250
4 20243
5 20239
6 202317
7 202250
8 201811
9 201715
10 201757
11 201619
12
Analysis of simulation results for cavitating flows in micro-channels using different turbulence models
20162
13 201419
14 201286
15
Numerical study of convective heat transfer of aviation kerosene flows in pipe at supercritical pressure
20103
16
AERODYNAMICS OF LEAN DIRECT INJECTION COMBUSTOR WITH MULTI-SWIRLER ARRAYS
20068
17 200540
18
S^p _2 \subseteq ZPP^{NP}
200111
19 19993
20
ON ABELIAN AUTOMORPHISM GROUPS OF SURFACES OF GENERAL TYPE
19961

About Jun Cai

Jun Cai is a scholar working on Computational Mechanics, Fluid Flow and Transfer Processes, Materials Chemistry, Catalysis and Aerospace Engineering, having authored 170 papers that have together received 3.4k indexed citations. Recurring topics across this work include Combustion and flame dynamics (16 papers), Ultrasound and Cavitation Phenomena (16 papers), Catalytic Processes in Materials Science (12 papers), Nanocomposite Films for Food Packaging (10 papers), Fluid Dynamics and Heat Transfer (9 papers), Microstructure and mechanical properties (8 papers), Heat transfer and supercritical fluids (8 papers) and Aerosol Filtration and Electrostatic Precipitation (8 papers). The work is most often cited by research in Computational Mechanics (821 citations), Fluid Flow and Transfer Processes (234 citations), Biomaterials (409 citations), Materials Chemistry (1.2k citations) and Mechanical Engineering (777 citations). Jun Cai has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Xiulan Huai, Xunfeng Li, San‐Mou Jeng, Jianhong Yang, Zhixiong Guo, Lian Zhong, Jinping Zhou, Yanping Zhang, Lina Zhang and Lianjie Liu. Their work appears in journals such as International Journal of Biological Macromolecules, Applied Thermal Engineering, Energy, Physical review. B, Condensed matter and Journal of Applied Polymer Science.

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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