Ha-Kyung Kwon
Impact in
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- Machine Learning in Materials Science
- Block Copolymer Self-Assembly
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- Advanced Battery Technologies Research
Papers in
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- Machine Learning in Materials Science 9
- Block Copolymer Self-Assembly 4
- Material Dynamics and Properties 3
- Electronic and Structural Properties of Oxides 2
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- Fuel Cells and Related Materials 6
- Advanced Battery Materials and Technologies 3
- Advancements in Battery Materials 3
- Co-authors
- Mónica Olvera de la Cruz (5 shared papers)Kenneth R. Shull (4 shared papers)Tran Doan Huan (2 shared papers)Rampi Ramprasad (2 shared papers)Jos W. Zwanikken (3 shared papers)Ryan P. Lively (1 shared paper)Rishi Gurnani (1 shared paper)Ghanshyam Pilania (1 shared paper)
- Journals
- Macromolecules (4 papers)npj Computational Materials (1 paper)Matter (1 paper)ACS Central Science (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Ha-Kyung Kwon
19 papers receiving 462 citations
Ha-Kyung Kwon's Hit Papers
Peers
Comparison fields: 5 of 88
- Materials Chemistry 219
- Automotive Engineering 52
- Polymers and Plastics 55
- Information Systems and Management 22
- Biomaterials 41
Countries citing papers authored by Ha-Kyung Kwon
This map shows the geographic impact of Ha-Kyung Kwon'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 Ha-Kyung Kwon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ha-Kyung Kwon more than expected).
Fields of papers citing papers by Ha-Kyung Kwon
This network shows the impact of papers produced by Ha-Kyung Kwon. 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 Ha-Kyung Kwon. The network helps show where Ha-Kyung Kwon may publish in the future.
Co-authors
The 25 scholars most cited alongside Ha-Kyung Kwon, 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 | Design of functional and sustainable polymers assisted by artificial intelligence Hit paper breakdown → | 2024 | 87 |
| 2 | 2018 | 70 | |
| 3 | 2019 | 51 | |
| 4 | 2020 | 38 | |
| 5 | 2022 | 30 | |
| 6 | 2024 | 24 | |
| 7 | 2023 | 24 | |
| 8 | 2017 | 24 | |
| 9 | 2015 | 21 | |
| 10 | 2019 | 16 | |
| 11 | 2023 | 15 | |
| 12 | 2024 | 13 | |
| 13 | 2024 | 13 | |
| 14 | 2023 | 12 | |
| 15 | 2023 | 8 | |
| 16 | 2014 | 8 | |
| 17 | 2024 | 7 | |
| 18 | 2017 | 7 | |
| 19 | 2025 | 6 |
About Ha-Kyung Kwon
Ha-Kyung Kwon is a scholar working on Materials Chemistry, Electrical and Electronic Engineering, Organic Chemistry, Physical and Theoretical Chemistry and Biomaterials, having authored 19 papers that have together received 474 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (9 papers), Fuel Cells and Related Materials (6 papers), Block Copolymer Self-Assembly (4 papers), Electrostatics and Colloid Interactions (3 papers), Advanced Battery Materials and Technologies (3 papers), Material Dynamics and Properties (3 papers), Advancements in Battery Materials (3 papers) and Electronic and Structural Properties of Oxides (2 papers). The work is most often cited by research in Materials Chemistry (219 citations), Automotive Engineering (52 citations), Polymers and Plastics (55 citations), Information Systems and Management (22 citations) and Biomaterials (41 citations). Ha-Kyung Kwon has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Mónica Olvera de la Cruz, Kenneth R. Shull, Tran Doan Huan, Rampi Ramprasad, Jos W. Zwanikken, Ryan P. Lively, Rishi Gurnani, Ghanshyam Pilania, Linda Hung and Sharan Bobbala. Their work appears in journals such as Macromolecules, npj Computational Materials, Matter, ACS Central Science 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.