神经形态工程学
记忆电阻器
材料科学
电阻随机存取存储器
方向(向量空间)
各向异性
非易失性存储器
计算机科学
电导
电压
光电子学
纳米技术
电气工程
人工智能
凝聚态物理
物理
人工神经网络
光学
几何学
数学
工程类
作者
Ruo‐Yao Sun,Zeyu Hou,Qing Chen,Bingxuan Zhu,Chengyi Zhu,Peiyu Huang,Zhen Hu,Liang Zhen,Feichi Zhou,Cheng‐Yan Xu,Jing‐Kai Qin
标识
DOI:10.1002/adma.202409017
摘要
Abstract Intelligent neuromorphic hardware holds considerable promise in addressing the growing demand for massive real‐time data processing in edge computing. Resistive switching materials with intrinsic anisotropy and a compact design of non‐volatile memory devices with the capability of handling spatiotemporally reconstructed data is crucial to perform sophisticated tasks in complex application scenarios. In this study, an anisotropic resistive switching cell with a planar configuration based on lithiated NbSe 3 nanosheets is demonstrated. Benefitting from the highly aligned diffusive channel associated with a quasi‐1D van der Waals structure, the memristor patterned along NbSe 3 atomic chains presents robust memory switching behavior with superior stability, particularly the low set/reset voltages (0.4 V/−0.36 V) and extremely small standard deviation (0.041 V/0.051 V), among the best compared to state‐of‐the‐art devices. More importantly, unlike traditional resistive switching materials, anisotropic ion migration in NbSe 3 crystals leads to a high orientation selectivity in the conductance update. Custom‐designed neuromorphic hardware contributes to the implementation of omnibearing motion recognition for automatic pilot applications, yielding a high accuracy of 95.9% considering variations. This article presents a new strategy based on NbSe 3 crystals to develop a neuromorphic computing system with intelligent application scenarios.
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