Song Qi

2.3k citations
53 papers · 1.9k indexed · 1 hit paper · h-index 20

Impact in

Papers in

Song Qi

52 papers receiving 1.8k citations

Hit Papers

A highly sensitive, self-powered triboelectric auditory sensor for social robotics and hearing aids 2018 · 713 citations
7132018202620202023200400600

Peers

Song Qi
Comparison fields: 5 of 94
  • Polymers and Plastics 607
  • Civil and Structural Engineering 689
  • Biomedical Engineering 1.1k
  • Cognitive Neuroscience 333
  • Electronic, Optical and Magnetic Materials 261
Replace Li Ding with:
Li Ding China
Choon Chiang Foo Singapore
Haiwen Luan United States
Fengxin Sun China
Yong Shi United States
Inho Ha South Korea
Joonhwa Choi South Korea
Guoyong Mao China
Yun Ling United States
Aaron Lamoureux United States
Song Qi relative to Li Ding China Li Ding's profile →
Citations per field
00.5×6.4×
Li Ding · 1×
Citations per year

Countries citing papers authored by Song Qi

Since Specialization
Citations

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

Fields of papers citing papers by Song Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20251
3 20257
4 20242
5 20244
6 20245
7 20241
8 20234
9 20239
10 20239
11 202317
12 20232
13 20212
14 202014
15 202016
16 20207
17 201914
18 201918
19
A highly sensitive, self-powered triboelectric auditory sensor for social robotics and hearing aids
Hit paper breakdown →
2018713
20 201882

About Song Qi

Song Qi is a scholar working on Civil and Structural Engineering, Polymers and Plastics, Biomedical Engineering, Electronic, Optical and Magnetic Materials and Mechanical Engineering, having authored 53 papers that have together received 1.9k indexed citations. Recurring topics across this work include Vibration Control and Rheological Fluids (40 papers), Structural Engineering and Vibration Analysis (25 papers), Seismic Performance and Analysis (20 papers), Advanced Sensor and Energy Harvesting Materials (8 papers), Advanced Materials and Mechanics (7 papers), Dielectric materials and actuators (7 papers), Electromagnetic wave absorption materials (6 papers) and Advanced Antenna and Metasurface Technologies (4 papers). The work is most often cited by research in Polymers and Plastics (607 citations), Civil and Structural Engineering (689 citations), Biomedical Engineering (1.1k citations), Cognitive Neuroscience (333 citations) and Electronic, Optical and Magnetic Materials (261 citations). Song Qi has collaborated with scholars based in China, Norway and United States. Frequent co-authors include Miao Yu, Jie Fu, Mi Zhu, Hengyu Guo, Jie Chen, Zhong Lin Wang, Chenguo Hu, Xianjie Pu, Jie Wang and Di Liu. Their work appears in journals such as Smart Materials and Structures, Composites Science and Technology, Applied Physics Letters, Physics of Fluids and Mechanical Systems and Signal Processing.

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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