Da Won Kim
Impact in
- Cognitive Neuroscience top 5%
- Tactile and Sensory Interactions
- Polymers and Plastics top 10%
- Conducting polymers and applications
Papers in
-
- Advanced Sensor and Energy Harvesting Materials 4
-
- Membrane Separation and Gas Transport 2
- Advanced Materials and Mechanics 1
- Co-authors
- Steve Park (4 shared papers)Jun Chang Yang (3 shared papers)Jinwon Oh (1 shared paper)Jin‐Oh Kim (1 shared paper)Joo Yong Sim (1 shared paper)Se Young Kwon (1 shared paper)Chan Beum Park (1 shared paper)Kayoung Kim (1 shared paper)
- Journals
- ACS Applied Materials & Interfaces (2 papers)Science Advances (1 paper)Polymer (1 paper)Fibers and Polymers (1 paper)Nature Communications (1 paper)
- Partner nations
- South KoreaJapan
In The Last Decade
Da Won Kim
7 papers receiving 845 citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Cognitive Neuroscience 295
- Polymers and Plastics 212
- Biomedical Engineering 660
- Bioengineering 47
- Electrical and Electronic Engineering 355
Countries citing papers authored by Da Won Kim
This map shows the geographic impact of Da Won 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 Da Won Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da Won Kim more than expected).
Fields of papers citing papers by Da Won Kim
This network shows the impact of papers produced by Da Won 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 Da Won Kim. The network helps show where Da Won Kim may publish in the future.
Co-authors
The 14 scholars most cited alongside Da Won Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Microstructured Porous Pyramid-Based Ultrahigh Sensitive Pressure Sensor Insensitive to Strain and Temperature Hit paper breakdown → | 2019 | 497 |
| 2 | 2020 | 199 | |
| 3 | 2022 | 93 | |
| 4 | 2020 | 59 | |
| 5 | 2024 | 4 | |
| 6 | 2023 | 2 | |
| 7 | 2022 | 2 |
About Da Won Kim
Da Won Kim is a scholar working on Biomedical Engineering, Mechanical Engineering, Cognitive Neuroscience, Water Science and Technology and Electrical and Electronic Engineering, having authored 7 papers that have together received 856 indexed citations. Recurring topics across this work include Advanced Sensor and Energy Harvesting Materials (4 papers), Membrane Separation Technologies (2 papers), Membrane Separation and Gas Transport (2 papers), Tactile and Sensory Interactions (2 papers), Electrochemical sensors and biosensors (1 paper), Advanced Materials and Mechanics (1 paper), Neuroscience and Neural Engineering (1 paper) and Alzheimer's disease research and treatments (1 paper). The work is most often cited by research in Cognitive Neuroscience (295 citations), Polymers and Plastics (212 citations), Biomedical Engineering (660 citations), Bioengineering (47 citations) and Electrical and Electronic Engineering (355 citations). Da Won Kim has collaborated with scholars based in South Korea and Japan. Frequent co-authors include Steve Park, Jun Chang Yang, Jinwon Oh, Jin‐Oh Kim, Joo Yong Sim, Se Young Kwon, Chan Beum Park, Kayoung Kim, Su Yeong Kim and Seungkyu Lee. Their work appears in journals such as ACS Applied Materials & Interfaces, Science Advances, Polymer, Fibers and Polymers and Nature Communications.
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.