Controllable resistive switching of STO:Ag/SiO2-based memristor synapse for neuromorphic computing

记忆电阻器 神经形态工程学 长时程增强 电阻随机存取存储器 材料科学 光电子学 电导 突触重量 突触可塑性 计算机科学 人工神经网络 突触 纳米技术 非易失性存储器 电压 神经科学 电子工程 电气工程 人工智能 物理 化学 工程类 受体 生物 凝聚态物理 生物化学
作者
Nasir Ilyas,Jinyong Wang,Chunmei Li,Hao Fu,Dongyang Li,Xiangdong Jiang,Deen Gu,Yadong Jiang,Wei Li
出处
期刊:Journal of Materials Science & Technology [Elsevier]
卷期号:97: 254-263 被引量:50
标识
DOI:10.1016/j.jmst.2021.04.071
摘要

Resistive random-access memory (RRAM) is a promising technology to develop nonvolatile memory and artificial synaptic devices for brain-inspired neuromorphic computing. Here, we have developed a STO:Ag/SiO2 bilayer based memristor that has exhibited a filamentary resistive switching with stable endurance and long-term data retention ability. The memristor also exhibits a tunable resistance modulation under positive and negative pulse trains, which could fully mimic the potentiation and depression behavior like a bio-synapse. Several synaptic plasticity functions, including long-term potentiation (LTP) and long-term depression (LTD), paired-pulsed facilitation (PPF), spike-rate-dependent-plasticity (SRDP), and post-tetanic potentiation (PTP), are faithfully implemented with the fabricated memristor. Moreover, to demonstrate the feasibility of our memristor synapse for neuromorphic applications, spike-time-dependent plasticity (STDP) is also investigated. Based on conductive atomic force microscopy observations and electrical transport model analyses, it can be concluded that it is the controlled formation and rupture of Ag filaments that are responsible for the resistive switching while exhibiting a switching ratio of ~103 along with a good endurance and stability suitable for nonvolatile memory applications. Before fully electroforming, the gradual conductance modulation of Ag/STO:Ag/SiO2/p++-Si memristor can be realized, and the working mechanism could be explained by the succeeding growth and contraction of Ag filaments promoted by a redox reaction. This newly fabricated memristor may enable the development of nonvolatile memory and realize controllable resistance/weight modulation when applied as an artificial synapse for neuromorphic computing.
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