记忆电阻器
神经形态工程学
电阻随机存取存储器
计算机科学
遗忘
强化学习
光电子学
材料科学
人工神经网络
纳米技术
电子工程
电气工程
人工智能
工程类
电压
哲学
语言学
作者
Liu Yang,Dong Lin,Qi Meng,Xiao‐Ming Xiu,Haikuan Dong,Heng Wang
标识
DOI:10.1002/pssr.202100255
摘要
Bipolar resistive switching (RS) and synaptic behaviors of resistive random access memory (RRAM) based on TiO x are demonstrated. RS uniformity is improved by introducing nitrogen into the RS layer using radio frequency sputtering in the reactive Ar/N 2 ambient. The conductive mechanism is in good agreement with the space−charge‐limited conduction model. The activation energy fit by the Arrhenius equation and conductive atomic force microscopy results indicate that the conductive filaments are formed by oxygen vacancies. More importantly, reliable multilevel RRAM can be achieved by tuning the compliance current, which enables the achievement of distinguishable resistance states. Furthermore, multilevel RRAM enables the simulation of synaptic functions, such as learning−forgetting−relearning, habituation, and spike‐timing‐dependent plasticity (STDP). Image pattern recognition based on STDP learning rules using a digital memristor is demonstrated. The findings may offer a route to the development of future storage and neuromorphic computing.
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