Baekjun Kim
Impact in
- Inorganic Chemistry top 5%
- Metal-Organic Frameworks: Synthesis and Applications
- Zeolite Catalysis and Synthesis
- Materials Chemistry top 10%
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Covalent Organic Framework Applications
Papers in
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- Metal-Organic Frameworks: Synthesis and Applications 5
- Zeolite Catalysis and Synthesis 3
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- Machine Learning in Materials Science 4
- X-ray Diffraction in Crystallography 2
- Covalent Organic Framework Applications 1
- Co-authors
- Jihan Kim (6 shared papers)Sangwon Lee (4 shared papers)Sanggyu Chong (1 shared paper)Eun Seon Cho (1 shared paper)Sarah Yunmi Lee (1 shared paper)Hyun Min Cho (1 shared paper)Peter G. Boyd (1 shared paper)Berend Smit (1 shared paper)
- Journals
- Science Advances (1 paper)ACS Applied Materials & Interfaces (1 paper)Building and Environment (1 paper)IEEE Access (1 paper)Journal of Chemical Information and Modeling (1 paper)
- Partner nations
- South KoreaSwitzerlandUnited States
In The Last Decade
Baekjun Kim
8 papers receiving 745 citations
Peers
Comparison fields: 5 of 76
- Inorganic Chemistry 409
- Materials Chemistry 545
- Catalysis 50
- Process Chemistry and Technology 16
- Computational Theory and Mathematics 75
Countries citing papers authored by Baekjun Kim
This map shows the geographic impact of Baekjun 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 Baekjun Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Baekjun Kim more than expected).
Fields of papers citing papers by Baekjun Kim
This network shows the impact of papers produced by Baekjun 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 Baekjun Kim. The network helps show where Baekjun Kim may publish in the future.
Co-authors
The 12 scholars most cited alongside Baekjun 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 | 2020 | 278 | |
| 2 | 2020 | 184 | |
| 3 | 2021 | 172 | |
| 4 | 2017 | 57 | |
| 5 | 2019 | 34 | |
| 6 | 2024 | 19 | |
| 7 | 2020 | 8 | |
| 8 | 2026 | 1 |
About Baekjun Kim
Baekjun Kim is a scholar working on Inorganic Chemistry, Materials Chemistry, Process Chemistry and Technology, Artificial Intelligence and Mechanics of Materials, having authored 8 papers that have together received 753 indexed citations. Recurring topics across this work include Metal-Organic Frameworks: Synthesis and Applications (5 papers), Machine Learning in Materials Science (4 papers), Zeolite Catalysis and Synthesis (3 papers), X-ray Diffraction in Crystallography (2 papers), Internet Traffic Analysis and Secure E-voting (1 paper), Covalent Organic Framework Applications (1 paper), Authorship Attribution and Profiling (1 paper) and Hate Speech and Cyberbullying Detection (1 paper). The work is most often cited by research in Inorganic Chemistry (409 citations), Materials Chemistry (545 citations), Catalysis (50 citations), Process Chemistry and Technology (16 citations) and Computational Theory and Mathematics (75 citations). Baekjun Kim has collaborated with scholars based in South Korea, Switzerland and United States. Frequent co-authors include Jihan Kim, Sangwon Lee, Sanggyu Chong, Eun Seon Cho, Sarah Yunmi Lee, Hyun Min Cho, Peter G. Boyd, Berend Smit, Yunsung Lim and Myungchul Kim. Their work appears in journals such as Science Advances, ACS Applied Materials & Interfaces, Building and Environment, IEEE Access and Journal of Chemical Information and Modeling.
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.