Yong-Hoon Kim

Prof. Yong-Hoon Kim


Research Focus & Metrics

Academic Career Length

29Years (1998-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 December 2017 in Small
Verified
Journal Article
Closed access
PDF file
JHJae Sang Heo
Jae Sang Heo
JEJimi Eom
Jimi Eom
YKYong-Hoon Kim
Yong-Hoon Kim
SPSung Kyu Park
Sung Kyu Park

17 May 2017 in Advanced Materials
Verified
Journal Article
Closed access
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MLMinkyung Lee
Minkyung Lee
WLWoobin Lee
Woobin Lee
SCSeungbeom Choi
Seungbeom Choi
JJJeong‐Wan Jo
Jeong‐Wan Jo
JKJaekyun Kim
Jaekyun Kim
YKYong-Hoon Kim
Yong-Hoon Kim

14 November 2019 in Advanced Materials
Verified
Journal Article
Closed access
PDF file
SKSung Min Kwon
Sung Min Kwon
SCSung Woon Cho
Sung Woon Cho
MKMinho Kim
Minho Kim
JHJae Sang Heo
Jae Sang Heo
YKYong-Hoon Kim
Yong-Hoon Kim
SPSung Kyu Park
Sung Kyu Park

5 February 2021 in Advanced Intelligent Systems
Verified
Journal Article
Open access
PDF file
SCSung Woon Cho
Sung Woon Cho
SKSung Min Kwon
Sung Min Kwon
YKYong-Hoon Kim
Yong-Hoon Kim
SPSung Kyu Park
Sung Kyu Park
Neuromorphic electronics draw attention as innovative approaches that facilitate hardware implementation of next‐generation artificial intelligent system including neuromorphic in‐memory computing, artificial sensory perception, and humanoid robotics. Among the various neuromorphic devices, optoelectronic synapses are promising neuromorphic devices that use optical means to mimic synaptic plasticity and related functions. Compared with classical neuromorphic chip based on electronic synapses using electrical means, photonic neuromorphic chip using light as input spike signal can be attractive alternative approach for next‐generation artificial intelligent system capable of high density, low power consumption, and low crosstalk. Thus, various optoelectronic synaptic electronics have been developed to overcome the drawback of conventional artificial intelligent system based on electrical synapses. Herein, the recent progresses in transistor‐based optoelectronic synapses for artificial intelligent system and review their device architecture, neuromorphic operational mechanisms, manufacturing methodologies, and advanced applications for artificial intelligent computing and visual perception systems are focused. Finally, the future challenges and research direction in the optoelectronic synaptic research are discussed.

9 March 2017 in ACS Applied Materials & Interfaces
Verified
Journal Article
Closed access
JEJimi Eom
Jimi Eom
RJRawat Jaisutti
Rawat Jaisutti
HLHyungseok Lee
Hyungseok Lee
WLWoobin Lee
Woobin Lee
JHJae-Sang Heo
Jae-Sang Heo
YKYong-Hoon Kim
Yong-Hoon Kim

1 November 2019 in Science Advances
Verified
Journal Article
Open access
PDF file
JKJaehyun Kim
Jaehyun Kim
SKSung-Min Kwon
Sung-Min Kwon
YKYeo Kyung Kang
Yeo Kyung Kang
YKYong-Hoon Kim
Yong-Hoon Kim
MLMyoung-Jae Lee
Myoung-Jae Lee
SPSung Kyu Park
Sung Kyu Park
Direct full-color photodetectors without sophisticated color filters and interferometric optics have attracted considerable attention for widespread applications. However, difficulties of combining various multispectral semiconductors and improving photon transfer efficiency for high-performance optoelectronic devices have impeded the translation of these platforms into practical realization. Here, we report a low-temperature (4.2 × 1017 Jones) and photoresponsivity (>8.3 × 103 A W−1) in a broad range of wavelengths (365 to 1310 nm). On the basis of these technologies, a wavelength discriminable phototransistor circuit array (>600 phototransistors) was implemented on a skin-like soft platform, which is expected to be a versatile and scalable approach for wide spectral image sensors and human-oriented biological devices.