Ming Lv

31 papers receiving 798 citations

Peers

Ming Lv
Comparison fields: 5 of 112
  • Filtration and Separation 34
  • Pollution 151
  • Electronic, Optical and Magnetic Materials 135
  • Environmental Engineering 102
  • Catalysis 47
Replace Junwei Qian with:
Junwei Qian China
Lixiong Li United States
Ruiling Wang China
Mohamed E. El‐Hefnawy Saudi Arabia
Swati Mohanty India
Yann Le Brech France
Fahim Uddin Pakistan
Sourav Mondal India
Chye‐Eng Seng Malaysia
Kozo Koide Japan
Ming Lv relative to Junwei Qian China Junwei Qian's profile →
Citations per field
00.5×6.4×
Junwei Qian · 1×
Citations per year

Countries citing papers authored by Ming Lv

Since Specialization
Citations

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

Fields of papers citing papers by Ming Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012150
2 201368
3 201565
4 201458
5 202157
6 201354
7 200744
8 202136
9 201634
10 201533
11 201629
12 201625
13 202123
14 201520
15 201518
16
Efficacy and side effect of curcumin for the treatment of osteoarthritis: A meta-analysis of randomized controlled trials.
201918
17 202015
18 201314
19 200514
20 20158

About Ming Lv

Ming Lv is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Pollution, Biomedical Engineering and Aerospace Engineering, having authored 33 papers that have together received 813 indexed citations. Recurring topics across this work include Gold and Silver Nanoparticles Synthesis and Applications (4 papers), Process Optimization and Integration (3 papers), Thermodynamic properties of mixtures (3 papers), Pharmaceutical and Antibiotic Environmental Impacts (3 papers), Robotic Path Planning Algorithms (3 papers), Robotics and Sensor-Based Localization (3 papers), Phase Equilibria and Thermodynamics (2 papers) and Image and Object Detection Techniques (2 papers). The work is most often cited by research in Filtration and Separation (34 citations), Pollution (151 citations), Electronic, Optical and Magnetic Materials (135 citations), Environmental Engineering (102 citations) and Catalysis (47 citations). Ming Lv has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Wenxiu Li, Hai Xu, Luo Liu, Changqiu Wang, Anhuai Lu, Muhammad Junaid, Nan Xu, Yong Zhao, Hongrui Ding and Riffat Naseem Malik. Their work appears in journals such as Scientific Reports, The Science of The Total Environment, Journal of Chemical & Engineering Data, Organic & Biomolecular Chemistry and Applied Physics Letters.

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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