K
Kwang S. Kim
Researcher at Ulsan National Institute of Science and Technology
Publications - 671
Citations - 71259
Kwang S. Kim is an academic researcher from Ulsan National Institute of Science and Technology. The author has contributed to research in topics: Graphene & Ab initio. The author has an hindex of 97, co-authored 642 publications receiving 62053 citations. Previous affiliations of Kwang S. Kim include Asia Pacific Center for Theoretical Physics & IBM.
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Origin of diastereoselectivity in the nitrile oxide cycloadditions with Oppolzer's chiral sultams: coulombic interaction as the key role in diastereofacial differentiation
TL;DR: In this paper, the authors used semi-empirical quantum mechanical calculations using the PM3 method to find the origin of diastereoselectivity in cycloadditions with Oppolzer's chiral sultams and found that activation barriers for the favored and disfavored transition states are strongly correlated with the Coulombic repulsions between the dipolar oxygen and the sultam oxygens.
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Covalent versus Charge Transfer Modification of Graphene/Carbon-Nanotubes with Vitamin B1: Co/N/S-C Catalyst toward Excellent Oxygen Reduction.
TL;DR: High catalytic efficiency and stability of ThG/CNT/Co-cov show a promising prospect of materialization of PEMFCs for clean energy production.
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Graphene Edges and Beyond: Temperature-Driven Structures and Electromagnetic Properties
Changbae Hyun,Jeonghun Yun,Woo Jong Cho,Chang Woo Myung,Jaesung Park,Geunsik Lee,Zonghoon Lee,Kwanpyo Kim,Kwang S. Kim +8 more
TL;DR: In this issue of ACS Nano, He et al. report an in situ heating experiment in aberration-corrected transmission electron microscopy to elucidate the temperature dependence of graphene edge termination at the atomic scale, and reveal that graphene edges predominantly have zigzag terminations below 400 °C, while above 600 ° C, the edges are dominated by armchair and reconstructedZigzag edges.
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Universal Machine Learning Interatomic Potentials: Surveying Solid Electrolytes.
Amir Hajibabaei,Kwang S. Kim +1 more
TL;DR: In this paper, the authors apply ab initio molecular dynamics (AIMD) with on-the-fly machine learning (ML) of interatomic potentials using the sparse Gaussian process regression (SGPR) algorithm for a survey of Li diffusivity in hundreds of ternary crystals as potential electrolytes for all-solid-state batteries.
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Hydrogenation-induced atomic stripes on the 2 H − MoS 2 surface
Sang Wook Han,Won Seok Yun,J. D. Lee,Younghun Hwang,Jeong Min Baik,Hoon-Kyu Shin,Wang G. Lee,Young S. Park,Kwang S. Kim +8 more
TL;DR: In this article, it was shown that the hydrogenation of a single crystal $2H\text{\ensuremath{-}}{\mathrm{MoS}}_{2}$ induces a novel intermediate phase between 2H and 1T phases on its surface, i.e., the large area, uniform, robust, and surface array of atomic stripes through the intralayer atomic-plane gliding.