Shengping Dai

1.1k citations
59 papers · 874 indexed · h-index 20

Impact in

Papers in

Shengping Dai

56 papers receiving 861 citations

Peers

Shengping Dai
Comparison fields: 5 of 85
  • Polymers and Plastics 335
  • Molecular Medicine 73
  • Biomedical Engineering 624
  • Cognitive Neuroscience 142
  • Electronic, Optical and Magnetic Materials 117
Replace Jiahe Liao with:
Jiahe Liao United States
Mingkun Li China
Jeonghee Yeom South Korea
Xuewen Shi China
Kaixi Huang China
Chuan Liu China
Huizhen Yan China
Ruonan Liu China
Jian Zou China
Mohammad Shamsi Iran
Shengping Dai relative to Jiahe Liao United States Jiahe Liao's profile →
Citations per field
00.5×10×15×
Jiahe Liao · 1×
Citations per year

Countries citing papers authored by Shengping Dai

Since Specialization
Citations

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

Fields of papers citing papers by Shengping Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20253
2 20253
3 20252
4 20250
5 20250
6 20250
7 20252
8 20241
9 20246
10 202318
11 202313
12 202318
13 202210
14 202210
15 202031
16 201910
17 20194
18 201930
19 201847
20 201116

About Shengping Dai

Shengping Dai is a scholar working on Polymers and Plastics, Biomedical Engineering, Molecular Medicine, Cognitive Neuroscience and Mechanical Engineering, having authored 59 papers that have together received 874 indexed citations. Recurring topics across this work include Advanced Sensor and Energy Harvesting Materials (40 papers), Conducting polymers and applications (19 papers), Advanced Materials and Mechanics (14 papers), Polymer composites and self-healing (11 papers), Tactile and Sensory Interactions (11 papers), Dielectric materials and actuators (7 papers), Gas Sensing Nanomaterials and Sensors (5 papers) and Hydrogels: synthesis, properties, applications (4 papers). The work is most often cited by research in Polymers and Plastics (335 citations), Molecular Medicine (73 citations), Biomedical Engineering (624 citations), Cognitive Neuroscience (142 citations) and Electronic, Optical and Magnetic Materials (117 citations). Shengping Dai has collaborated with scholars based in China, France and South Korea. Frequent co-authors include Jianning Ding, Guanggui Cheng, Xiaoshuang Zhou, Ningyi Yuan, Hao Zhu, Xu Dong, Ningyi Yuan, Yuewen Chen, Jiaqi Wang and Shuai Wang. Their work appears in journals such as Colloids and Surfaces A Physicochemical and Engineering Aspects, Measurement, Sensors and Actuators A Physical, New Journal of Chemistry and Langmuir.

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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