Lin Lv

77 papers receiving 626 citations

Peers

Lin Lv
Comparison fields: 5 of 141
  • Catalysis 31
  • Modeling and Simulation 20
  • Renewable Energy, Sustainability and the Environment 61
  • Computer Science Applications 18
  • Industrial and Manufacturing Engineering 23
Replace Hongbo Chen with:
Hongbo Chen China
Yao Ge China
Kyung-Hwa Kim South Korea
Leijie Zhang China
Abir Mouldi Saudi Arabia
Zeeshan Haq United States
Francisco Sales Ávila Cavalcante Brazil
Jiao Sun China
Habiba Abdelhalim United States
Lin Lv relative to Hongbo Chen China Hongbo Chen's profile →
Citations per field
00.5×3.6×
Hongbo Chen · 1×
Citations per year

Countries citing papers authored by Lin Lv

Since Specialization
Citations

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

Fields of papers citing papers by Lin Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202368
2 202045
3 202134
4 202333
5 201733
6 202229
7 202225
8 201518
9 202117
10 202415
11 202314
12 202313
13 202013
14 202212
15 200611
16 201810
17 201410
18 20229
19 20169
20 20079

About Lin Lv

Lin Lv is a scholar working on Occupational Therapy, Computer Science Applications, Cancer Research, Catalysis and Renewable Energy, Sustainability and the Environment, having authored 89 papers that have together received 639 indexed citations. Recurring topics across this work include Catalytic Processes in Materials Science (10 papers), Diabetic Foot Ulcer Assessment and Management (5 papers), Advanced battery technologies research (5 papers), Toxic Organic Pollutants Impact (5 papers), Pressure Ulcer Prevention and Management (5 papers), Electrocatalysts for Energy Conversion (5 papers), Effects and risks of endocrine disrupting chemicals (4 papers) and MXene and MAX Phase Materials (4 papers). The work is most often cited by research in Catalysis (31 citations), Modeling and Simulation (20 citations), Renewable Energy, Sustainability and the Environment (61 citations), Computer Science Applications (18 citations) and Industrial and Manufacturing Engineering (23 citations). Lin Lv has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Guobao Song, Jingwen Chen, Xinyue Zhao, Yue Chen, Baichang Zhong, Xinpei Lu, Houzhao Wan, Xiaofan Liu, Li Qiu and Mingchu Li. Their work appears in journals such as Environmental Science & Technology, Journal of Tissue Viability, Intensive and Critical Care Nursing, The Science of The Total Environment and Journal of Cleaner Production.

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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