Geng Da

466 citations
9 papers · 394 · h-index 7

Impact in

  • Catalysis top 10%
    • Catalysts for Methane Reforming
    • Advanced Sensor and Energy Harvesting Materials
    • Soft Robotics and Applications

Papers in

Geng Da

8 papers receiving 385 citations

Peers

Geng Da
Comparison fields: 5 of 38
  • Catalysis 38
  • Biomedical Engineering 253
  • Electrical and Electronic Engineering 63
  • Materials Chemistry 45
  • Automotive Engineering 10
Replace Shigeki Tsuchitani with:
Shigeki Tsuchitani Japan
Heiki Kasemägi Estonia
Ashish V. Pattekar United States
Dawoon Lee South Korea
Ruifen Wu Singapore
Da Peng Yu China
Mike Renn United States
Guan-Wei Wu Taiwan
Tiechuan Li China
Patricio Espinoza-Vallejos United States
Geng Da relative to Shigeki Tsuchitani Japan Shigeki Tsuchitani's profile →
Citations per field
00.5×2×4×6×8.8×
Shigeki Tsuchitani · 1×
Citations per year

Countries citing papers authored by Geng Da

Since Specialization
Citations

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

Fields of papers citing papers by Geng Da

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Geng Da, 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 Geng Da Line = papers co-authored together Geng Da links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2021106
2 202169
3 202058
4 202154
5 202143
6 202137
7 202221
8 20206
9
Research Progress and Theories of He-Mu Group in Resent Years
20140

About Geng Da

Geng Da is a scholar working on Biomedical Engineering, Catalysis, Complementary and alternative medicine, Condensed Matter Physics and Electrical and Electronic Engineering, having authored 9 papers that have together received 394 indexed citations. Recurring topics across this work include Advanced Sensor and Energy Harvesting Materials (6 papers), Acupuncture Treatment Research Studies (1 paper), Advanced Materials and Mechanics (1 paper), Catalysts for Methane Reforming (1 paper), Micro and Nano Robotics (1 paper), Nanomaterials and Printing Technologies (1 paper), Advanced MEMS and NEMS Technologies (1 paper) and Electrochemical sensors and biosensors (1 paper). The work is most often cited by research in Catalysis (38 citations), Biomedical Engineering (253 citations), Electrical and Electronic Engineering (63 citations), Materials Chemistry (45 citations) and Automotive Engineering (10 citations). Geng Da has collaborated with scholars based in China. Frequent co-authors include Wei Dong Zhou, Rui Chen, Chenying Zhang, Songyue Chen, Zheng Shen, Yu Xie, Cheng Gang Bai, Yangxu Liu, Tianqing Zheng and Yaoyao Li. Their work appears in journals such as Sensors and Actuators A Physical, ACS Applied Materials & Interfaces, International Journal of Hydrogen Energy, Carbon and Advanced Materials Technologies.

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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