Yong Huang

Dr. Yong Huang

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

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

Representative Publications

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7 August 2014 in Discover Nano
Verified
Journal Article
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YHYong Huang
Yong Huang
YLYing Luo
Ying Luo
ZSZihan Shen
Zihan Shen
GYGuoliang Yuan
Guoliang Yuan
Haibo ZengHaibo Zeng
Haibo Zeng
Well unipolar resistive switching (RS) behaviors were observed from Ag/ZnO single-microwire/Ag memristors. The reset voltages were larger than the set voltages, and all of them were less than 1 V. The resistance ratios of high-resistance state (HRS) to low-resistance state (LRS) reached 103. The bistable RS behaviors were entirely reversible and steady within 100 cycles. It was found that the dominant conduction mechanisms in LRS and HRS were ohmic behavior and space-charge-limited current (SCLC), respectively.

28 July 2021 in Journal of Electronic Materials
Verified
Journal Article
Closed access
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WLWenqiang Liu
Wenqiang Liu
SGShiying Guo
Shiying Guo
GLGaoyu Liu
Gaoyu Liu
XXXinyan Xia
Xinyan Xia
YHYong Huang
Yong Huang
SZShengli Zhang
Shengli Zhang

10 October 2022 in Current Applied Physics
Verified
Journal Article
Closed access
YJYue Jiang
Yue Jiang
YHYong Huang
Yong Huang
SZShengli Zhang
Shengli Zhang

28 November 2022 in Journal of Electronic Materials
Verified
Journal Article
Closed access
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YTYuanyuan Tai
Yuanyuan Tai
XXXinyan Xia
Xinyan Xia
MXMin Xie
Min Xie
XGXinwei Guo
Xinwei Guo
LXLili Xu
Lili Xu
SZShengli Zhang
Shengli Zhang

22 November 2022 in RSC Advances
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Journal Article
Open access
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YHYong Huang
Yong Huang
JYJiahao Yu
Jiahao Yu
YKYu Kong
Yu Kong
XWXiaoqiu Wang
Xiaoqiu Wang
The advent of memristors and the continuing research and development in the field of brain-inspired computing could allow realization of a veritable “thinking machine”. In this study, ZnO-based memristors were fabricated using a radio frequency magnetron sputtering method. The ZnO oxide layer was prepared by incorporating silver nanocrystals (NCs). Several synaptic functions, i.e. nonlinear transmission characteristics, short-term potentiation, long-term potentiation/depression, and pair-pulse facilitation, were imitated in the memristor successfully. Furthermore, the transition from synaptic behaviors to bipolar resistive switching behaviors of the device was also observed under repeated stimulus. It is speculated that the switching mechanism is due to the formation and rupture of the conductive Ag filaments and the corresponding electrochemical metallization. The experimental results demonstrate that the Ag/Ag:ZnO/Pt memristor with resistive switching and several synaptic behaviors has a potential application in neuromorphic computing and data storage systems.

17 July 2020 in Semiconductor Science and Technology
Verified
Journal Article
Closed access
YHYong Huang
Yong Huang
JZJianjie Zhou
Jianjie Zhou
YHYu Huang
Yu Huang
RWRuixue Wang
Ruixue Wang
The rapid expansion of data information has necessitated higher requirements for the operational speed, low energy consumption and high density integration. Resistive random access memory (RRAM), which can realize all of the mentioned advantages, has the potential to be the next-generation nonvolatile memory device. However, it is not easy to design an RRAM device with both high performance and stability. Herein, we improve the performance of the RRAM devices by incorporating Cu nanocrystals (NCs) into the ZnO oxide layer. Afterwards, many resistive parameters of the NC-RRAM devices are markedly improved, such as longer retention time over 10 6 s, with consecutive 10 3 switching cycles. It is inferred that the switching mechanism is due to the migration of Cu cations and the corresponding electrochemical metallization, and the Cu NCs enhance the electric field intensity, which boosts the formation and rupture of the conductive filaments.