K
Kyung-min Kim
Researcher at KAIST
Publications - 143
Citations - 6986
Kyung-min Kim is an academic researcher from KAIST. The author has contributed to research in topics: Memristor & Resistive random-access memory. The author has an hindex of 32, co-authored 138 publications receiving 6082 citations. Previous affiliations of Kyung-min Kim include Hewlett-Packard & Samsung.
Papers
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Journal ArticleDOI
Atomic structure of conducting nanofilaments in TiO2 resistive switching memory
Deok-Hwang Kwon,Kyung-min Kim,Jae Hyuck Jang,Jong Myeong Jeon,Min Hwan Lee,Gun Hwan Kim,Xiang-Shu Li,Gyeong-Su Park,Bora Lee,Seungwu Han,Miyoung Kim,Cheol Seong Hwang +11 more
TL;DR: In situ current-voltage and low-temperature conductivity measurements confirm that switching occurs by the formation and disruption of Ti(n)O(2n-1) (or so-called Magnéli phase) filaments, which will provide a foundation for unravelling the full mechanism of resistance switching in oxide thin films.
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Nanofilamentary resistive switching in binary oxide system; a review on the present status and outlook
TL;DR: TiO(2) and NiO thin films in unipolar thermo-chemical switching mode are primarily dealt with and appear to offer a basis for the understanding of other RS mechanisms which were originally considered to be irrelevant to the localized events.
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High dielectric constant TiO2 thin films on a Ru electrode grown at 250 °C by atomic-layer deposition
TL;DR: In this article, the leakage current density of a TiO2 film with an equivalent oxide thickness of 1.0-1.5 nm was 10−6−10−8A∕cm2 at ± 1V.
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An artificial nociceptor based on a diffusive memristor.
Jung Ho Yoon,Zhongrui Wang,Kyung-min Kim,Huaqiang Wu,Vignesh Ravichandran,Qiangfei Xia,Cheol Seong Hwang,Jianhua Yang +7 more
TL;DR: This study proposes and experimentally demonstrates an artificial nociceptor based on a diffusive memristor with critical dynamics for the first time, and builds an artificial sensory alarm system to experimentally demonstrate the feasibility and simplicity of integrating such novel artificial nOCICEptor devices in artificial intelligence systems, such as humanoid robots.
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Memristors for Energy-Efficient New Computing Paradigms
TL;DR: In this Review, memristors are examined from the frameworks of both von Neumann and neuromorphic computing architectures and a new logic computational process based on the material implication is discussed, which will substantially decrease the energy consumption for futuristic information technology.