Yang Chai

28.3k total citations · 17 hit papers
339 papers, 22.6k citations indexed

About

Yang Chai is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Biomedical Engineering. According to data from OpenAlex, Yang Chai has authored 339 papers receiving a total of 22.6k indexed citations (citations by other indexed papers that have themselves been cited), including 184 papers in Electrical and Electronic Engineering, 180 papers in Materials Chemistry and 49 papers in Biomedical Engineering. Recurrent topics in Yang Chai's work include 2D Materials and Applications (93 papers), Advanced Memory and Neural Computing (75 papers) and Graphene research and applications (65 papers). Yang Chai is often cited by papers focused on 2D Materials and Applications (93 papers), Advanced Memory and Neural Computing (75 papers) and Graphene research and applications (65 papers). Yang Chai collaborates with scholars based in Hong Kong, China and United States. Yang Chai's co-authors include Feichi Zhou, Ning Zhang, Yuda Zhao, Lejuan Cai, Shu Ping Lau, Ziyuan Lin, Bocheng Qiu, Yuen Hong Tsang, Jiewei Chen and Jingli Wang and has published in prestigious journals such as Journal of the American Chemical Society, Physical Review Letters and Advanced Materials.

In The Last Decade

Yang Chai

323 papers receiving 22.2k citations

Hit Papers

Optoelectronic resistive random access memory for neuromo... 2016 2026 2019 2022 2019 2020 2020 2019 2021 250 500 750 1000

Peers

Yang Chai
Comparison fields: 5 of 170
  • Electrical and Electronic Engineering 12.9k
  • Materials Chemistry 9.9k
  • Renewable Energy, Sustainability and the Environment 4.7k
  • Biomedical Engineering 4.2k
  • Polymers and Plastics 2.6k
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Citations per field, relative to Yang Chai
Yang Chai · 1×
Citations per year, relative to Yang Chai
Yang Chai · 1×

Countries citing papers authored by Yang Chai

Since Specialization
Citations

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

Fields of papers citing papers by Yang Chai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yang Chai

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Chai. A scholar is included among the top collaborators of Yang Chai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yang Chai. Yang Chai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 3
2 5
3 0
4 0
5 1
6 12
7 10
8
Optoelectronic graded neurons for bioinspired in-sensor motion perception breakdown →
273
9 37
10 2
11 56
12 7
13 55
14 46
15 61
16 61
17 12
18 14
19 30
20 69

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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