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

Abstract

Artificial synapse is one of the potential electronics for constructing neural network hardware. In this work, Pt/LiSiO_x/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/LiSiO_x/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 LiSiO_x memristor in the neuromorphic computing.

Graphical abstract

Keywords

artificial synapse / lithium silicate / memristor / neuromorphic computing / resistive switching

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