Jun Wei

404 citations
14 papers · 102 · h-index 6

Impact in

    • Supramolecular Chemistry and Complexes
    • Synthesis and Properties of Aromatic Compounds
    • Sulfur-Based Synthesis Techniques
    • Synthesis of Indole Derivatives
    • Neuroscience of respiration and sleep

Papers in

Jun Wei

12 papers receiving 100 citations

Peers

Jun Wei
Comparison fields: 5 of 51
  • Organic Chemistry 52
  • Endocrine and Autonomic Systems 12
  • Complementary and Manual Therapy 2
  • Spectroscopy 12
  • Cognitive Neuroscience 13
Replace Sainan Li with:
Sainan Li China
Yuanheng Li China
Shigeaki Masuda Japan
Tomoyuki Watanabe Japan
Elyse T. Williams Switzerland
Rhonda L. Pitsch United States
Andreas Klein Germany
Robin Lemmens Belgium
Robert B. Chevalier United States
Suhas Ballal India
Jun Wei relative to Sainan Li China Sainan Li's profile →
Citations per field
00.5×6.5×
Sainan Li · 1×
Citations per year

Countries citing papers authored by Jun Wei

Since Specialization
Citations

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

Fields of papers citing papers by Jun Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 201828
2 202224
3 201517
4 20237
5 20247
6 20157
7 20223
8 20133
9 20242
10 20132
11 20221
12 20241
13 20250
14 20250

About Jun Wei

Jun Wei is a scholar working on Organic Chemistry, Computational Mechanics, Spectroscopy, Surgery and Molecular Biology, having authored 14 papers that have together received 102 indexed citations. Recurring topics across this work include Fluid Dynamics Simulations and Interactions (3 papers), Luminescence and Fluorescent Materials (2 papers), Molecular Sensors and Ion Detection (2 papers), Robotic Path Planning Algorithms (2 papers), Supramolecular Chemistry and Complexes (2 papers), Synthesis and Properties of Aromatic Compounds (2 papers), Metabolism and Genetic Disorders (1 paper) and MicroRNA in disease regulation (1 paper). The work is most often cited by research in Organic Chemistry (52 citations), Endocrine and Autonomic Systems (12 citations), Complementary and Manual Therapy (2 citations), Spectroscopy (12 citations) and Cognitive Neuroscience (13 citations). Jun Wei has collaborated with scholars based in China, Germany and United Kingdom. Frequent co-authors include Dietmar Kuck, Xiao‐Ping Cao, Zhimin Li, Hak‐Fun Chow, Jianmin Liang, Jing Kang, Yanli Chen, Xiaojie Jin, Xiaojun Yao and Xinyu Hu. Their work appears in journals such as Drones, Chemistry - An Asian Journal, Chinese Journal of Chemistry, European Journal of Organic Chemistry and Brain and Behavior.

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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