Bin Cheng

528 citations
15 papers · 420 · h-index 8

Impact in

Papers in

Bin Cheng

13 papers receiving 413 citations

Peers

Bin Cheng
Comparison fields: 5 of 91
  • Health, Toxicology and Mutagenesis 82
  • Materials Chemistry 206
  • Developmental Neuroscience 15
  • Pollution 35
  • Automotive Engineering 36
Replace Kavitha Subbiah with:
Kavitha Subbiah India
Kyoung‐Min Kim South Korea
Shou-Chieh Huang Taiwan
Verónica Freyre‐Fonseca Mexico
Mira Das India
Robert Guest Belgium
Johannes G. Keller Germany
F. Pflücker Germany
Martyna Pajewska-Szmyt Poland
Bin Cheng relative to Kavitha Subbiah India Kavitha Subbiah's profile →
Citations per field
00.5×10×20×32×
Kavitha Subbiah · 1×
Citations per year

Countries citing papers authored by Bin Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Bin Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2012208
2 201371
3 202146
4 201929
5 202414
6 202413
7 20109
8 20208
9 20236
10 20196
11 20104
12 20244
13
Minimal parallel binary adders with and/or gates and a scheme for a compact parallel multiplier
19822
14 20090
15 20090

About Bin Cheng

Bin Cheng is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Health, Toxicology and Mutagenesis, Electronic, Optical and Magnetic Materials and Health, having authored 15 papers that have together received 420 indexed citations. Recurring topics across this work include Advancements in Battery Materials (4 papers), Urban Green Space and Health (3 papers), Supercapacitor Materials and Fabrication (3 papers), Advanced Battery Materials and Technologies (2 papers), Electromagnetic Scattering and Analysis (2 papers), Nanoparticles: synthesis and applications (2 papers), Urban Transport and Accessibility (2 papers) and Health disparities and outcomes (2 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (82 citations), Materials Chemistry (206 citations), Developmental Neuroscience (15 citations), Pollution (35 citations) and Automotive Engineering (36 citations). Bin Cheng has collaborated with scholars based in China, Macao and Australia. Frequent co-authors include Aoneng Cao, Yuanfang Liu, Jiahui Liu, Yixin Yang, Haifang Wang, Yuliang Zhao, Li‐Jing Du, Zheng‐Mei Song, Yanli Wang and Kun Xiang. Their work appears in journals such as Journal of Alloys and Compounds, Microporous and Mesoporous Materials, Frontiers in Public Health, Chinese Chemical Letters and Journal of Translational Medicine.

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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