L. Shang

594 citations
23 papers · 293 · h-index 7

Impact in

Papers in

L. Shang

22 papers receiving 289 citations

Peers

L. Shang
Comparison fields: 5 of 77
  • Renewable Energy, Sustainability and the Environment 45
  • Epidemiology 75
  • Ophthalmology 18
  • Insect Science 17
  • Radiology, Nuclear Medicine and Imaging 26
Replace Shuo Rong with:
Shuo Rong China
Yejun Wu China
Yan Wei China
Ge Gao China
Seung Hyun Shin South Korea
Yu‐Chang Liu Taiwan
Anastasia M. Moysenovich Russia
Yining Jiang China
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Citations per field
00.5×4.5×
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Citations per year

Countries citing papers authored by L. Shang

Since Specialization
Citations

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

Fields of papers citing papers by L. Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202188
2 202146
3 201631
4 201929
5 201822
6 202219
7 201611
8 20246
9 20166
10 20135
11 20225
12 20234
13 20224
14 20224
15
Optimization of Ultrasound-assisted Extraction of Total Flavonoids from Trollius chinensis by Response Surface Methodology
20112
16 20202
17 20192
18 20222
19 20132
20 20221

About L. Shang

L. Shang is a scholar working on Materials Chemistry, Polymers and Plastics, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Oncology, having authored 23 papers that have together received 293 indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (2 papers), Carbon Nanotubes in Composites (2 papers), Ophthalmology and Visual Impairment Studies (1 paper), Cyclopropane Reaction Mechanisms (1 paper), Click Chemistry and Applications (1 paper), Cerebrospinal fluid and hydrocephalus (1 paper), Insect Utilization and Effects (1 paper) and Silk-based biomaterials and applications (1 paper). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (45 citations), Epidemiology (75 citations), Ophthalmology (18 citations), Insect Science (17 citations) and Radiology, Nuclear Medicine and Imaging (26 citations). L. Shang has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Minjie Wei, Hu Shi, Hongxia Zhang, Ming Zhang, Hengquan Yang, Pengju Yang, Jinglin Yi, Liang Huang, Fen Xiong and Jianghong Zhao. Their work appears in journals such as Frontiers in Oncology, BioMed Research International, Computational Materials Science, International Journal of Electrical Power & Energy Systems and The Analyst.

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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