Jaechang Lim
Impact in
-
- Computational Drug Discovery Methods
-
- Machine Learning in Materials Science
- Graphene research and applications
Papers in
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- Computational Drug Discovery Methods 7
- Petri Nets in System Modeling 4
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- Machine Learning in Materials Science 8
- Co-authors
- Woo Youn Kim (15 shared papers)Seongok Ryu (2 shared papers)Yo Joong Choe (1 shared paper)Jiyeon Ham (1 shared paper)Soojung Yang (1 shared paper)Jaewook Kim (6 shared papers)Sungwoo Kang (5 shared papers)Tae‐Yong Kim (1 shared paper)
- Journals
- The Journal of Chemical Physics (2 papers)Advanced Science (2 papers)Chemical Science (2 papers)Journal of Chemical Information and Modeling (2 papers)Computer Physics Communications (1 paper)
- Partner nations
- South Korea
In The Last Decade
Jaechang Lim
20 papers receiving 605 citations
Peers
Comparison fields: 5 of 78
- Computational Theory and Mathematics 396
- Materials Chemistry 238
- Molecular Biology 354
- Pharmacology 58
- Computational Mathematics 1
Countries citing papers authored by Jaechang Lim
This map shows the geographic impact of Jaechang Lim'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 Jaechang Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaechang Lim more than expected).
Fields of papers citing papers by Jaechang Lim
This network shows the impact of papers produced by Jaechang Lim. 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 Jaechang Lim. The network helps show where Jaechang Lim may publish in the future.
Co-authors
The 18 scholars most cited alongside Jaechang Lim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 269 | |
| 2 | 2022 | 119 | |
| 3 | 2018 | 39 | |
| 4 | 2021 | 34 | |
| 5 | 2023 | 27 | |
| 6 | 2009 | 26 | |
| 7 | 2023 | 22 | |
| 8 | 2020 | 13 | |
| 9 | 2020 | 9 | |
| 10 | 2004 | 8 | |
| 11 | 2023 | 8 | |
| 12 | 2016 | 8 | |
| 13 | 2016 | 7 | |
| 14 | 2017 | 6 | |
| 15 | Deeply learning molecular structure-property relationships using graph attention neural network. | 2018 | 5 |
| 16 | 2001 | 4 | |
| 17 | 2005 | 2 | |
| 18 | 2018 | 2 | |
| 19 | 2011 | 1 | |
| 20 | 2004 | 1 |
About Jaechang Lim
Jaechang Lim is a scholar working on Computational Theory and Mathematics, Materials Chemistry, Molecular Biology, Computer Networks and Communications and Atomic and Molecular Physics, and Optics, having authored 21 papers that have together received 610 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (8 papers), Computational Drug Discovery Methods (7 papers), Advanced Chemical Physics Studies (4 papers), Petri Nets in System Modeling (4 papers), Protein Structure and Dynamics (4 papers), Distributed systems and fault tolerance (3 papers), Advanced Wireless Network Optimization (2 papers) and Advanced NMR Techniques and Applications (2 papers). The work is most often cited by research in Computational Theory and Mathematics (396 citations), Materials Chemistry (238 citations), Molecular Biology (354 citations), Pharmacology (58 citations) and Computational Mathematics (1 citation). Jaechang Lim has collaborated with scholars based in South Korea. Frequent co-authors include Woo Youn Kim, Seongok Ryu, Yo Joong Choe, Jiyeon Ham, Soojung Yang, Jaewook Kim, Sungwoo Kang, Tae‐Yong Kim, Sang-Yeon Hwang and Soojin Park. Their work appears in journals such as The Journal of Chemical Physics, Advanced Science, Chemical Science, Journal of Chemical Information and Modeling and Computer Physics 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.