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Universal Core–Shell Nanowire Memristor Platform with Quasi‐2D Filament Confinement for Scalable Neuromorphic Applications

Enxiu Wu, Yue Wang, Shida Huo, Jing‐Bo Xu, Ming Sheng, Hongsheng Liu, Li Zhong, Gao Junfeng, Yuan Xie, Caofeng Pan

2025Advanced Functional Materials32 citationsDOI

Abstract

Abstract Memristors are central to the advancement of nano‐electronic and neuromorphic systems due to their fast‐switching speed, low power consumption, and compatibility with CMOS technology. However, the stochastic formation of conductive filaments (CFs) in filament‐based memristors remains a major obstacle, leading to significant variability in switching performance. Here, a novel memristor architecture that combines spatial confinement precision with fabrication simplicity is proposed; a core–shell silver nanowire structure, consisting of a highly conductive Ag core wrapped in a polyvinylpyrrolidone (PVP) shell. This 1D nanowire serves both as the active electrode and as a geometric scaffold that constrains CF growth within a quasi‐2D plane. The resulting device demonstrates excellent electrical performance, including a low threshold voltage (0.22 V), high switching uniformity (coefficient of variation <15%), and ultra‐low power consumption (≈400 pW). Molecular dynamics simulations reveal the spontaneous rupture behavior of CF and establish a correlation between filament dimensions and their temporal stability. Furthermore, the system emulates key nociceptor‐like functionalities—such as threshold triggering, relaxation recovery, and sensitization—highlighting its neuromorphic potential. This work establishes a versatile structural platform for precise nanoscale CF control using a structurally simple core–shell nanowire architecture, offering broad applicability across device formats for energy‐efficient, neuromorphic‐compatible memristive electronics.

Topics & Concepts

Neuromorphic engineeringMaterials scienceMemristorNanowireCore (optical fiber)NanotechnologyScalabilityShell (structure)Protein filamentOptoelectronicsArtificial neural networkElectronic engineeringComputer scienceComposite materialArtificial intelligenceEngineeringDatabaseAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeuroscience and Neural Engineering
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