Jun Li

8.5k citations
285 papers · 7.2k · 1 hit paper · h-index 47

Impact in

Papers in

Jun Li

272 papers receiving 7.1k citations

Jun Li's Hit Papers

Potential energy surfaces from high fidelity fitting ofab initiopoints: the permutation invariant polynomial - neural network approach 2016 · 352 citations
3520+3+6Years since publication100200300

Peers

Jun Li
Comparison fields: 5 of 169
  • Atomic and Molecular Physics, and Optics 3.5k
  • Spectroscopy 1.6k
  • Atmospheric Science 1.0k
  • Catalysis 298
  • Materials Chemistry 1.7k
Replace Bryan M. Wong with:
Bryan M. Wong United States
Eric J. Bylaska United States
Bin Jiang China
Jadran Vrabec Germany
Hans Hasse Germany
Baron Peters United States
Pál Jedlovszky Hungary
Bernhard Lendl Austria
Ze‐Sheng Li China
Bin Yang China
Jun Li relative to Bryan M. Wong United States Bryan M. Wong's profile →
Citations per field
00.5×2.7×
Bryan M. Wong · 1×
Citations per year

Countries citing papers authored by Jun Li

Since Specialization
Citations

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

Fields of papers citing papers by Jun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 285 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Potential energy surfaces from high fidelity fitting ofab initiopoints: the permutation invariant polynomial - neural network approach
Hit paper breakdown →
2016352
2 2017306
3 2013284
4 2020164
5 2020144
6 2014141
7 2013116
8 2010111
9 2012102
10 201495
11 201290
12 201490
13 202089
14 201589
15 201381
16 201679
17 201572
18 201471
19 201771
20 201871

About Jun Li

Jun Li is a scholar working on Atomic and Molecular Physics, and Optics, Spectroscopy, Atmospheric Science, Materials Chemistry and Biomedical Engineering, having authored 285 papers that have together received 7.2k indexed citations. Recurring topics across this work include Advanced Chemical Physics Studies (123 papers), Spectroscopy and Quantum Chemical Studies (61 papers), Spectroscopy and Laser Applications (45 papers), Quantum, superfluid, helium dynamics (41 papers), Atmospheric Ozone and Climate (37 papers), Atmospheric chemistry and aerosols (31 papers), Molecular Spectroscopy and Structure (18 papers) and Machine Learning in Materials Science (16 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (3.5k citations), Spectroscopy (1.6k citations), Atmospheric Science (1.0k citations), Catalysis (298 citations) and Materials Chemistry (1.7k citations). Jun Li has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Hua Guo, Bin Jiang, Daiqian Xie, Richard Dawes, Shanyong Wang, Dingtao Zhao, Yang Liu, Dandan Lü, T. B. Brill and Jianyi Ma. Their work appears in journals such as The Journal of Chemical Physics, The Journal of Physical Chemistry A, Physical Chemistry Chemical Physics, The Journal of Physical Chemistry Letters and Journal of the American Chemical Society.

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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