Song Liu

6.6k citations
109 papers · 4.9k indexed · 4 hit papers · h-index 36

Song Liu

105 papers receiving 4.8k citations

Hit Papers

Zero-field superconducting diode effe...1782017202620202023200400600

Peers

Song Liu
Comparison fields: 5 of 125
  • Atomic and Molecular Physics, and Optics 1.7k
  • Materials Chemistry 2.3k
  • Electronic, Optical and Magnetic Materials 848
  • Civil and Structural Engineering 851
  • Condensed Matter Physics 383
Replace Martin Maldovan with:
Martin Maldovan United States
Roy H. Olsson United States
Yan Pennec France
Zhiwen Shi China
Christofer Hierold Switzerland
Jian Wu China
Clifton G. Fonstad United States
Oliver Paul Germany
Toshiro Higuchi Japan
Guangyu Zhang China
Song Liu relative to Martin Maldovan United States Martin Maldovan's profile →
Citations per field
00.5×4.9×
Martin Maldovan · 1×
Citations per year

Countries citing papers authored by Song Liu

Since Specialization
Citations

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

Fields of papers citing papers by Song Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20254
3 20234
4 202241
5 20225
6 20224
7 202124
8 20217
9 202120
10 202119
11 202125
12 20219
13 2021190
14 202033
15 20209
16
Simulation of Hubbard model physics in WSe2/WS2 moiré superlatticesbreakdown →
2020620
17
Pushing the polariton confinement limits with low losses using image polaritons in boron nitride
20202
18
Infrared hyperbolic metasurface based on nanostructured van der Waals materialsbreakdown →
2018376
19 20171
20
A Defect Detection Algorithm for Paper Currency Sorting System
20071

About Song Liu

Song Liu is a scholar working on Cognitive Neuroscience, Materials Chemistry and Civil and Structural Engineering, having authored 109 papers that have together received 4.9k indexed citations. Recurring topics across this work include Graphene research and applications (33 papers), Plasmonic and Surface Plasmon Research (19 papers), Thermal Radiation and Cooling Technologies (16 papers), 2D Materials and Applications (16 papers), Boron and Carbon Nanomaterials Research (10 papers), Neural dynamics and brain function (10 papers), Autism Spectrum Disorder Research (9 papers) and EEG and Brain-Computer Interfaces (8 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (1.7k citations), Materials Chemistry (2.3k citations) and Electronic, Optical and Magnetic Materials (848 citations). Song Liu has collaborated with scholars based in United States, China and Spain. Frequent co-authors include James H. Edgar, Takashi Taniguchi, Kenji Watanabe, Rainer Hillenbrand, Katayun Barmak, Fèlix Casanova, Peining Li, Luis E. Hueso, Alexey Y. Nikitin and Jiahan Li. Their work appears in journals such as Nature, Science and Physical Review 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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