Brain-like synaptic memristor based on lithium-doped silicate for neuromorphic computing |
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| Authors: | Shanwu Ke Li Jiang Yifan Zhao Yongyue Xiao Bei Jiang Gong Cheng Facai Wu Guangsen Cao Zehui Peng Min Zhu Cong Ye |
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| Institution: | 1. Faculty of Physics and Electronic Science, Hubei University, Wuhan 430062, China2. Shanghai Institute of Micro-system and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China3. Institute of Electronics, Chiao Tung University, Hsinchu 30010, Taiwan, China |
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| Abstract: | 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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| Keywords: | artificial synapse lithium silicate memristor neuromorphic computing resistive switching |
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