Brain-like synaptic memristor based on lithium-doped silicate for neuromorphic computing
Shanwu Ke1, Li Jiang1, Yifan Zhao1, Yongyue Xiao1, Bei Jiang1(), Gong Cheng1, Facai Wu3, Guangsen Cao1, Zehui Peng1, Min Zhu2(), Cong Ye1
1. Faculty of Physics and Electronic Science, Hubei University, Wuhan 430062, China 2. Shanghai Institute of Micro-system and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China 3. Institute of Electronics, Chiao Tung University, Hsinchu 30010, Taiwan, China
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.
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