Brain-like synaptic memristor based on lithium-doped silicate for neuromorphic computing

被引:11
|
作者
Ke, Shanwu [1 ]
Jiang, Li [1 ]
Zhao, Yifan [1 ]
Xiao, Yongyue [1 ]
Jiang, Bei [1 ]
Cheng, Gong [1 ]
Wu, Facai [3 ]
Cao, Guangsen [1 ]
Peng, Zehui [1 ]
Zhu, Min [2 ]
Ye, Cong [1 ]
机构
[1] Hubei Univ, Fac Phys & Elect Sci, Wuhan 430062, Peoples R China
[2] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Shanghai 200050, Peoples R China
[3] Chiao Tung Univ, Inst Elect, Hsinchu 30010, Taiwan
基金
中国国家自然科学基金;
关键词
artificial synapse; lithium silicate; memristor; neuromorphic computing; resistive switching; ION BATTERIES; SHORT-TERM; NETWORK; MEMORY;
D O I
10.1007/s11467-022-1173-2
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Artificial synapse is one of the potential electronics for constructing neural network hardware. In this work, Pt/LiSiOx/TiN analog artificial synapse memristor is designed and investigated. With the increase of compliance current (C. C.) under 0.6 mA, 1 mA, and 3 mA, the current in the high resistance state (HRS) presents an increasing variation, which indicates lithium ions participates in the operation process for Pt/LiSiOx/TiN memristor. Moreover, depending on the movement of lithium ions in the functional layer, the memristor illustrates excellent conduction modulation property, so the long-term potentiation (LTP) or depression (LTD) and paired-pulse facilitation (PPF) synaptic functions are successfully achieved. The neural network simulation for pattern recognition is proposed with the recognition accuracy of 91.4%. These findings suggest the potential application of the LiSiOx memristor in the neuromorphic computing.
引用
收藏
页数:6
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