神经形态工程学
材料科学
电导
光电子学
堆栈(抽象数据类型)
振幅
记忆电阻器
硅
油藏计算
非易失性存储器
电子工程
计算机科学
人工神经网络
光学
人工智能
凝聚态物理
工程类
物理
循环神经网络
程序设计语言
作者
Jinwoong Yang,Hyojong Cho,Hojeong Ryu,Muhammad Ismail,Chandreswar Mahata,Sungjun Kim
标识
DOI:10.1021/acsami.1c06618
摘要
In this study, we fabricate and characterize a Ti/TiO2/Si device with different dopant concentrations on a silicon surface for neuromorphic systems. We verify the device stack using transmission electron microscopy (TEM). The Ti/TiO2/p++Si device exhibits interface-type bipolar resistive switching with long-term memory. The potentiation and depression by the pulses of various amplitudes are demonstrated using gradual resistive switching. Moreover, pattern-recognition accuracy (>85%) is obtained in the neuromorphic system simulation when conductance is used as the weight in the network. Next, we investigate the short-term memory characteristics of the Ti/TiO2/p+Si device. The dynamic range is well-controlled by the pulse amplitude, and the conductance decay depends on the interval between the pulses. Finally, we build a reservoir computing system using the short-term effect of the Ti/TiO2/p+Si device, in which 4 bits (16 states) are differentiated by various pulse streams through the device that can be used for pattern recognition.
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