Kyoungmin Min

3.3k total citations
107 papers, 2.7k citations indexed

About

Kyoungmin Min is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Automotive Engineering. According to data from OpenAlex, Kyoungmin Min has authored 107 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Electrical and Electronic Engineering, 58 papers in Materials Chemistry and 17 papers in Automotive Engineering. Recurrent topics in Kyoungmin Min's work include Advancements in Battery Materials (43 papers), Machine Learning in Materials Science (39 papers) and Advanced Battery Materials and Technologies (30 papers). Kyoungmin Min is often cited by papers focused on Advancements in Battery Materials (43 papers), Machine Learning in Materials Science (39 papers) and Advanced Battery Materials and Technologies (30 papers). Kyoungmin Min collaborates with scholars based in South Korea, United States and France. Kyoungmin Min's co-authors include Eunseog Cho, N. R. Aluru, Seung-Woo Seo, Kwangjin Park, Amir Barati Farimani, Hyo Sug Lee, Byung‐Jin Choi, You Young Song, Minseon Kim and Changhoon Jung and has published in prestigious journals such as Advanced Materials, The Journal of Chemical Physics and ACS Nano.

In The Last Decade

Kyoungmin Min

101 papers receiving 2.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Kyoungmin Min South Korea	30	1.7k	978	591	418	415	107	2.7k
Shuai Chang China	31	1.1k 0.6×	904 0.9×	576 1.0×	1.1k 2.6×	233 0.6×	145	3.7k
Yarong Wang China	30	2.5k 1.5×	988 1.0×	537 0.9×	272 0.7×	908 2.2×	109	3.6k
Hu Chen China	32	1.6k 0.9×	1.0k 1.0×	203 0.3×	784 1.9×	155 0.4×	116	3.2k
Man‐Fai Ng Singapore	34	2.9k 1.7×	1.7k 1.7×	760 1.3×	340 0.8×	514 1.2×	98	4.0k
Weiling Luan China	31	1.4k 0.8×	1.5k 1.5×	318 0.5×	468 1.1×	278 0.7×	125	2.5k
Christoph Ziegler Germany	29	1.9k 1.1×	1.6k 1.6×	247 0.4×	700 1.7×	648 1.6×	67	3.4k
Jingyang Wang China	26	3.2k 1.9×	1.1k 1.1×	1.0k 1.7×	443 1.1×	770 1.9×	59	5.4k
Jingmin Zhang China	25	1.5k 0.9×	1.1k 1.1×	208 0.4×	330 0.8×	621 1.5×	78	2.3k
Wonjoon Choi South Korea	33	1.0k 0.6×	1.4k 1.4×	171 0.3×	1.3k 3.0×	782 1.9×	132	3.4k
Ziqian Wang China	24	1.7k 1.0×	2.0k 2.0×	217 0.4×	643 1.5×	437 1.1×	94	3.4k

Countries citing papers authored by Kyoungmin Min

Since Specialization

Citations

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

Fields of papers citing papers by Kyoungmin Min

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyoungmin Min. 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 Kyoungmin Min. The network helps show where Kyoungmin Min may publish in the future.

Co-authorship network of co-authors of Kyoungmin Min

This figure shows the co-authorship network connecting the top 25 collaborators of Kyoungmin Min. A scholar is included among the top collaborators of Kyoungmin Min 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 Kyoungmin Min. Kyoungmin Min is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kang, Byung‐Ho, et al.. (2025). Unveiling unexpected mechanical softening/stiffening in carbon nanotube composites under cyclic deformation: experiments and predictive modeling. Advanced Composites and Hybrid Materials. 8(2). 2 indexed citations

Ahn, Ji‐Hoon, John J. Bang, Ji Young Kim, et al.. (2025). Role of carbon nanotube film interlayer for Li-free all-solid-state battery. Electrochimica Acta. 528. 146284–146284. 1 indexed citations

Kim, Hodam, et al.. (2025). Face-wearable integrated bioelectronics for quantitative, automated diagnosis of blepharospasm. Biosensors and Bioelectronics X. 26. 100677–100677.

Min, Kyoungmin, et al.. (2025). Design strategies for fast-charging multiphase Na-ion layered cathodes: Dopant selection via computational high-throughput screening. Journal of Energy Chemistry. 107. 103–113. 3 indexed citations

Kim, Jonghyuk, et al.. (2025). Revealing the role of dopants to suppress phase transition in biphasic layered transition metal oxide cathodes for sodium-ion batteries. Journal of Power Sources. 640. 236718–236718.

Jeong, Jinyoung, Deok‐Hye Park, Jae‐Sung Jang, et al.. (2025). Machine learning-driven discovery of innovative hybrid solid electrolytes for high-performance all-solid-state batteries. Chemical Engineering Journal. 511. 161926–161926. 6 indexed citations

Kim, Minseon, et al.. (2024). Next-generation cathodes for calcium-ion batteries: Leveraging NASICON structures for enhanced stability and energy density. Energy storage materials. 73. 103827–103827. 4 indexed citations

Won, Joonghee, et al.. (2024). Toward fast and accurate machine learning interatomic potentials for atomic layer deposition precursors. Materials Today Advances. 21. 100474–100474. 9 indexed citations

Kim, Minseon, et al.. (2024). Exploring the large chemical space in search of thermodynamically stable and mechanically robust MXenes via machine learning. Physical Chemistry Chemical Physics. 26(14). 10769–10783. 6 indexed citations

10.

Ko, Tae‐Sung, et al.. (2024). Enhancing predictions of experimental band gap using machine learning and knowledge transfer. Materials Today Communications. 41. 110717–110717. 1 indexed citations

11.

Song, Junho, et al.. (2024). Molecular dynamics and machine learning insights into the mechanical behavior of zeolites under large deformation. Materials Today Communications. 41. 110922–110922. 1 indexed citations

12.

Min, Kyoungmin, et al.. (2024). Active Learning Framework for Expediting the Search of Thermodynamically Stable MXenes in the Extensive Chemical Space. ACS Nano. 18(43). 29678–29688. 5 indexed citations

13.

Song, Junho, et al.. (2024). Integrating Data Mining and Natural Language Processing to Construct a Melting Point Database for Organometallic Compounds. Journal of Chemical Information and Modeling. 64(19). 7432–7446.

14.

Kim, Jihwan, et al.. (2023). Heterogeneous double-layered hybrid solid electrolyte with a concentration-gradient structure for high-performance all-solid-state lithium batteries. Energy storage materials. 64. 103080–103080. 23 indexed citations

15.

Min, Kyoungmin, et al.. (2023). Natural Language Processing Techniques for Advancing Materials Discovery: A Short Review. International Journal of Precision Engineering and Manufacturing-Green Technology. 10(5). 1337–1349. 13 indexed citations

16.

Park, Junghwan, et al.. (2023). Impact of Data Partitioning to Improve Prediction Accuracy for Remaining Useful Life of Li-Ion Batteries. International Journal of Energy Research. 2023. 1–13. 2 indexed citations

17.

Kim, Minseon, et al.. (2023). Rapid discovery of promising materials via active learning with multi-objective optimization. Materials Today Communications. 37. 107245–107245. 10 indexed citations

18.

Min, Kyoungmin, Byung‐Jin Choi, Kwangjin Park, & Eunseog Cho. (2018). Machine learning assisted optimization of electrochemical properties for Ni-rich cathode materials. Scientific Reports. 8(1). 15778–15778. 57 indexed citations

19.

Park, Kwangjin, Jun‐Ho Park, Suk-Gi Hong, et al.. (2017). Re-construction layer effect of LiNi0.8Co0.15Mn0.05O2 with solvent evaporation process. Scientific Reports. 7(1). 44557–44557. 39 indexed citations

20.

McKenzie, Matthew E., Sushmit Goyal, Sung Hoon Lee, et al.. (2016). Adhesion of Organic Molecules on Silica Surfaces: A Density Functional Theory Study. The Journal of Physical Chemistry C. 121(1). 392–401. 20 indexed citations

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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