神经形态工程学
记忆电阻器
非阻塞I/O
材料科学
人工神经网络
计算机科学
可重组计算
纳米技术
计算机体系结构
电子工程
工程类
嵌入式系统
化学
人工智能
现场可编程门阵列
生物化学
催化作用
作者
Jiaqi Chen,Xingqiang Liu,Chang Liu,Lin Tang,Tong Bu,Bei Jiang,Yinxia Qing,Yulu Xie,Yong Wang,Y. Shan,Ruxin Li,Cong Ye,Lei Liao
出处
期刊:Nano Letters
[American Chemical Society]
日期:2024-04-22
标识
DOI:10.1021/acs.nanolett.4c01319
摘要
Artificial synapses and bionic neurons offer great potential in highly efficient computing paradigms. However, complex requirements for specific electronic devices in neuromorphic computing have made memristors face the challenge of process simplification and universality. Herein, reconfigurable Ag/HfO2/NiO/Pt memristors are designed for feasible switching between volatile and nonvolatile modes by compliance current controlled Ag filaments, which enables stable and reconfigurable synaptic and neuronal functions. A neuromorphic computing system effectively replicates the biological synaptic weight alteration and continuously accomplishes excitation and reset of artificial neurons, which consist of bionic synapses and artificial neurons based on isotype Ag/HfO2/NiO/Pt memristors. This reconfigurable electrical performance of the Ag/HfO2/NiO/Pt memristors takes advantage of simplified hardware design and delivers integrated circuits with high density, which exhibits great potency for future neural networks.
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