记忆电阻器
材料科学
神经形态工程学
振荡(细胞信号)
氧化物
电阻随机存取存储器
光电子学
放松(心理学)
电极
切换时间
纳米技术
电子工程
人工神经网络
电压
计算机科学
电气工程
机器学习
工程类
物理化学
生物
社会心理学
遗传学
化学
冶金
心理学
作者
Shimul Kanti Nath,Xiao Sun,Sanjoy Kumar Nandi,Xi Chen,Zhongrui Wang,Sujan Kumar Das,Wen Lei,L. Faraone,William D.A. Rickard,R. G. Elliman
标识
DOI:10.1002/adfm.202306428
摘要
Abstract Devices with volatile memristive switching and self‐sustained relaxation oscillations have received significant attention for their use in neuromorphic computing and solving optimization problems. However, obtaining devices with stable response and reliable oscillation remains challenging. This work describes the utility of metal/oxide interlayers in achieving reliable device performance with tuneable characteristics using Nb‐Nb2O5‐Pt structures. Detailed physical characterization of the Nb/Nb2O5 interlayer region shows that it consists of a thin, near‐stoichiometric Nb2O5 and an NbOx layer with a graded oxygen content. The impact of these interlayers on device performance is assessed by investigating their switching characteristics and oscillation dynamics. It is shown that the presence of the interlayer has a direct impact on the memristive switching mode and parameters threshold switching characteristics parameters. These dependencies are explained with reference to a lumped‐element circuit model of the device and shown to be dominated by changes in device resistance caused by interlayer formation. Significantly, stable oscillation with tuneable frequency is obtained by increasing the thickness of the reactive Nb electrode. Then, by simulating an array of coupled oscillators, a unique Hamiltonian solver is demonstrated. These results provide pathways for optimizing volatile memristive switching characteristics and guidance on how such devices can be employed to solve combinatorial optimization problems.
科研通智能强力驱动
Strongly Powered by AbleSci AI