Lingan Kong

3.4k citations
49 papers · 2.7k indexed · 2 hit papers · h-index 30
Topics
2D Materials and Applications (21 papers)Advanced Memory and Neural Computing (18 papers)Graphene research and applications (13 papers)

In The Last Decade

Lingan Kong

48 papers receiving 2.6k citations

Hit Papers

Efficient strain modulation of 2D materials via polymer e...202020262022202420202024100200300

Peers

Lingan Kong
Comparison fields: 5 of 61
  • Electrical and Electronic Engineering 1.9k
  • Materials Chemistry 1.3k
  • Biomedical Engineering 678
  • Cellular and Molecular Neuroscience 551
  • Polymers and Plastics 471
Replace Swapnadeep Poddar with:
Swapnadeep Poddar Hong Kong
Bobo Tian China
Jaewon Jang South Korea
Guoyun Gao China
Chuan Qian China
Jaewoo Shim South Korea
Mingde Du China
Qing Wan China
Sunghoon Song South Korea
David Wei Zhang China
Lingan Kong relative to Swapnadeep Poddar Hong Kong Swapnadeep Poddar's profile →
Citations per field
00.5×10×15×20×23.5×
Swapnadeep Poddar · 1×
Citations per year

Countries citing papers authored by Lingan Kong

Since Specialization
Citations

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

Fields of papers citing papers by Lingan Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingan Kong

This figure shows the co-authorship network connecting the top 25 collaborators of Lingan Kong. A scholar is included among the top collaborators of Lingan Kong 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 Lingan Kong. Lingan Kong 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
#WorkIndexed citations
1 2
2 0
3 11
4
Monolithic three-dimensional tier-by-tier integration via van der Waals laminationbreakdown →
71
5 4
6 36
7 1
8 14
9 8
10 83
11 111
12 37
13 12
14 8
15 31
16 46
17 214
18 215
19 39
20 58

About Lingan Kong

Lingan Kong is a scholar working on Polymers and Plastics, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering, having authored 49 papers that have together received 2.7k indexed citations. Recurring topics across this work include 2D Materials and Applications (21 papers), Advanced Memory and Neural Computing (18 papers) and Graphene research and applications (13 papers). The work is most often cited by research in Polymers and Plastics (471 citations), Electrical and Electronic Engineering (1.9k citations) and Cellular and Molecular Neuroscience (551 citations). Lingan Kong has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jia Sun, Yongli Gao, Chuan Qian, Junliang Yang, Yuan Liu, Lei Liao, Quanyang Tao, Xidong Duan, Guangyang Gou and Ying Fu. Their work appears in journals such as Nature, Nature Communications and Nano Letters.

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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