Jun Yao

2.6k citations
36 papers · 2.1k indexed · 1 hit paper · h-index 18

Impact in

Papers in

Jun Yao

34 papers receiving 2.0k citations

Hit Papers

Power generation from ambient humidity using protein nanowires 2020 · 628 citations
6282020202620222024200400600

Peers

Jun Yao
Comparison fields: 5 of 92
  • Renewable Energy, Sustainability and the Environment 439
  • Biomedical Engineering 1.0k
  • Electrical and Electronic Engineering 1.1k
  • Cellular and Molecular Neuroscience 308
  • Polymers and Plastics 215
Replace Tianda Fu with:
Tianda Fu United States
Bing Yin China
Soong Ju Oh South Korea
Samuele Porro Italy
Jaeyeong Heo South Korea
Arash Takshi United States
Junchen Liu China
Daozhi Shen China
Donghwi Cho South Korea
Malkeshkumar Patel South Korea
Jun Yao relative to Tianda Fu United States Tianda Fu's profile →
Citations per field
00.5×3.7×
Tianda Fu · 1×
Citations per year

Countries citing papers authored by Jun Yao

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20254
3 20250
4 202431
5 20244
6 202315
7 20236
8 2022128
9 202169
10 202157
11
Power generation from ambient humidity using protein nanowires
Hit paper breakdown →
2020628
12 2020200
13 202016
14 202055
15 201915
16 201918
17 201815
18 2013250
19 200019
20 19941

About Jun Yao

Jun Yao is a scholar working on Cellular and Molecular Neuroscience, Bioengineering, Electrical and Electronic Engineering, Biomedical Engineering and Renewable Energy, Sustainability and the Environment, having authored 36 papers that have together received 2.1k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (10 papers), Advanced Memory and Neural Computing (7 papers), Nanowire Synthesis and Applications (7 papers), Advanced Sensor and Energy Harvesting Materials (7 papers), Photonic and Optical Devices (6 papers), Semiconductor Lasers and Optical Devices (5 papers), Photoreceptor and optogenetics research (4 papers) and Microbial Fuel Cells and Bioremediation (4 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (439 citations), Biomedical Engineering (1.0k citations), Electrical and Electronic Engineering (1.1k citations), Cellular and Molecular Neuroscience (308 citations) and Polymers and Plastics (215 citations). Jun Yao has collaborated with scholars based in United States, France and China. Frequent co-authors include Xiaomeng Liu, Hongyan Gao, Tianda Fu, Derek R. Lovley, Bing Yin, Charles M. Lieber, Hao Yan, Joy E. Ward, Xiaorong Liu and Jianhan Chen. Their work appears in journals such as Nature Communications, Nano Letters, IEEE Photonics Technology Letters, Biosensors and Bioelectronics and Advanced Materials.

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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