Investigation of Synaptic Response on Memristive Devices using Two Dimentional Transition Metal Carbide for Neuromorphic Applications

被引：1

作者：

Gao, Fei ^{[1
,2
]}

Chen, Yihao ^{[1
,2
]}

Li, Yuefeng ^{[1
,2
]}

Zhang, Miaocheng ^{[1
,2
]}

Wang, Yu ^{[1
,2
]}

He, Nan ^{[1
,2
]}

Shen, Xinyi ^{[1
,2
]}

Lian, Xiaojuan ^{[1
,2
]}

Wan, Xiang ^{[1
,2
]}

Gong, Xiao ^{[3
]}

Guo, Yufeng ^{[1
,2
]}

Tong, Yi ^{[1
,2
,4
]}

机构：

[1] Nanjing Univ Posts & Telecommun, Coll Elect & Opt Engn, Nanjing, Jiangsu, Peoples R China

[2] Nanjing Univ Posts & Telecommun, Coll Microelect, Natl & Local Joint Engn Lab RF Integrat & Microas, Nanjing, Jiangsu, Peoples R China

[3] Natl Univ Singapore, Singapore, Singapore

[4] Univ Calif Santa Barbara, Santa Barbara, CA 93106 USA

来源：

2019 IEEE INTERNATIONAL CONFERENCE ON ELECTRON DEVICES AND SOLID-STATE CIRCUITS (EDSSC) | 2019年

基金：

中国国家自然科学基金;

关键词：

component; finmatting; style; styling; insert;

D O I：

10.1109/edssc.2019.8754057

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recently, physical realization of biological synapses with electronic devices aroused great interest. Meanwhile, a new family of two-dimensional transition metal carbides (TMC) has expanded rapidly. However, there are very few progresses for performing synaptic devices using transition metal carbides. In addition, biological plasticity and reliability are crucial fur achieving controllable synaptic behavior. In this work, synaptic devices were fabricated with transition metal carbide, and the value of memristive resistance is able to be carefully tuned and enhanced by 107 times, which is critical in building artificial neural networks with accurate and efficient learning capability.

引用

页数：3

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