Chang‐Hyun Kim

5.8k total citations · 1 hit paper
230 papers, 4.6k citations indexed

About

Chang‐Hyun Kim is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Biomedical Engineering. According to data from OpenAlex, Chang‐Hyun Kim has authored 230 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 141 papers in Electrical and Electronic Engineering, 37 papers in Materials Chemistry and 36 papers in Biomedical Engineering. Recurrent topics in Chang‐Hyun Kim's work include Organic Electronics and Photovoltaics (65 papers), Advanced Memory and Neural Computing (54 papers) and Semiconductor materials and devices (37 papers). Chang‐Hyun Kim is often cited by papers focused on Organic Electronics and Photovoltaics (65 papers), Advanced Memory and Neural Computing (54 papers) and Semiconductor materials and devices (37 papers). Chang‐Hyun Kim collaborates with scholars based in South Korea, France and United States. Chang‐Hyun Kim's co-authors include Yvan Bonnassieux, Gilles Horowitz, C. Daniel Frisbie, Myung‐Han Yoon, Sungjun Park, Won‐June Lee, Ioannis Kymissis, Sujin Sung, Hocheon Yoo and Hong Chul Moon and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Advanced Materials.

In The Last Decade

Chang‐Hyun Kim

215 papers receiving 4.5k citations

Hit Papers

Influence of PEDOT:PSS crystallinity and composition on e... 2018 2026 2020 2023 2018 100 200 300 400

Peers

Chang‐Hyun Kim
Comparison fields: 5 of 138
  • Electrical and Electronic Engineering 2.9k
  • Polymers and Plastics 1.3k
  • Materials Chemistry 1.2k
  • Biomedical Engineering 1.1k
  • Electronic, Optical and Magnetic Materials 379
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Jin‐Woo Choi United States
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Yawen Li China View profile →
Citations per field, relative to Chang‐Hyun Kim
Chang‐Hyun Kim · 1×
Citations per year, relative to Chang‐Hyun Kim
Chang‐Hyun Kim · 1×

Countries citing papers authored by Chang‐Hyun Kim

Since Specialization
Citations

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

Fields of papers citing papers by Chang‐Hyun Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chang‐Hyun Kim. 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 Chang‐Hyun Kim. The network helps show where Chang‐Hyun Kim may publish in the future.

Co-authorship network of co-authors of Chang‐Hyun Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Chang‐Hyun Kim. A scholar is included among the top collaborators of Chang‐Hyun Kim 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 Chang‐Hyun Kim. Chang‐Hyun Kim 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
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2 1
3 1
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10 4
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12 4
13 2
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15 13
16 1
17 8
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What is Needed the Most in MT-Supported Paper Writing
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20 1

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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