阻变行为可调控的物理瞬态异质结构忆阻器及安全神经网络构建

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中文摘要：作为生物体的重要指挥中心,大脑能够通过神经网络执行多种智能交互,包括记忆、学习和认知.近年来,基于忆阻器实现的人工突触和人工神经元构建神经网络作为一种极具前景的技术,已经得到了广泛的研究.然而,人工智能设备中的多重信息交互对信息安全构成潜在威胁.本文提出了物理瞬态形式的异质结构Ag/MgO/SiNx/W忆阻器,通过调整SiNx层的厚度分别实现了可重构阻变特性和易失性阈值开关特性,并从导电细丝的形成及其界面迁移特点出发阐述了该忆阻器的阻变机制.代表性的神经功能包括短时可塑性、短时可塑性向长期可塑性的转化以及神经元的整合-放电等神经拟态功能均可基于该忆阻器进行形象模拟.此外,我们还探索了与器件瞬态行为相关的溶解动力学,并利用水辅助转移法在可溶于水的聚乙烯醇衬底上构建了瞬态形式的神经形态器件阵列,其在室温下的去离子水中浸泡10 s后就可完成物理形态的完全消失.该物理瞬态忆阻式神经形态器件对于人工神经网络应用中的信息安全加固具有重要意义.

外文标题：Security enhancement of artificial neural network using physically transient form of heterogeneous memristors with tunable resistive switching behaviors

外文摘要：As a critical command center in organisms,the brain can execute multiple intelligent interactions through neural networks,including memory,learning and cognition.Recently,memristive-based neuromorphic devices have been widely developed as promising technologies to build artificial synapses and neurons for neural networks.However,multiple information interactions in artificial intelligence devices po-tentially pose threats to information security.Herein,a tran-sient form of heterogeneous memristor with a stacked structure of Ag/MgO/SiNx/W is proposed,in which both the reconfigurable resistive switching behavior and volatile threshold switching characteristics could be realized by ad-justing the thickness of the SiNx layer.The underlying resistive switching mechanism of the device was elucidated in terms of filamentary and interfacial effects.Representative neural functions,including short-term plasticity(STP),the trans-formation from STP to long-term plasticity,and integrate-and-fire neuron functions,have been successfully emulated in memristive devices.Moreover,the dissolution kinetics asso-ciated with underlying transient behaviors were explored,and the water-assisted transfer printing technique was exploited to build transient neuromorphic device arrays on the water-dis-solvable poly(vinyl alcohol)substrate,which were able to formless disappear in deionized water after 10-s dissolution at room temperature.This transient form of memristive-based neuromorphic device provides an important step toward in-formation security reinforcement for artificial neural network applications.

外文关键词：

memristorphysically transientcontrolled resistive switching behaviorinformation security

作者：

孙静、王湛、王欣媛、周颖、王晏婷、何云龙、雷毅敏、王宏、马晓华

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作者单位：

School of Advanced Materials and Nanotechnology,Xidian University,Xi'an 710126,China

National Engineering Research Center of Wide Band-gap Semiconductor,Xidian University,Xi'an 710126,China

School of Electronic Engineering,Xi'an University of Posts & Telecommunications,Xi'an 710121,China

关键词：

memristor physically transient controlled resistive switching behavior information security

基金：

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNatural Science Basic Research Program of ShaanxiNatural Science Basic Research Program of ShaanxiGuangdong Basic and Applied Basic Research FoundationFundamental Research Funds for the Central UniversitiesScientific Research Program Foundation of Shaanxi Provincial Education Department

项目编号：

6230417262188102622741302022JQ-5822022JQ-6842021A1515110020ZYTS2411922JK0564

出版年：

2024

DOI：

10.1007/s40843-024-2951-2

中国科学:材料科学(英文)

CSTPCD

ISSN：

年,卷(期)：2024.67(9)