Related Experiment Video
Updated: Jun 7, 2025

A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning
Published on: January 19, 2022
Orientation-Selective Memory Switching in Quasi-1D NbSe3 Neuromorphic Device for Omnibearing Motion Detection
Ruo-Yao Sun1,2, Ze-Yu Hou3, Qing Chen2
1School of Integrated Circuits, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China.
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 NbSe3 nanosheets is demonstrated. Benefitting from the highly aligned diffusive channel associated with a quasi-1D van der Waals structure, the memristor patterned along NbSe3 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 NbSe3 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 NbSe3 crystals to develop a neuromorphic computing system with intelligent application scenarios.

