Flexible memristors as electronic synapses for neuro- inspired computation based on scotch tape-exfoliated mica substrates

Flexible memristor devices based on plastic substrates have attracted considerable attention due to their applications in wearable computers and integrated circuits. However, most plastic-substrate memristors cannot function or be grown in high-temperature environments. In this study, scotch-tape-exfoliated mica was used as the flexible memristor substrate in order to resolve these high-temperature issues. Our TiN/ZHO/IGZO memristor, which was constructed using a thin （10 μm） mica substrate, has superior flexibility and thermostability. After bending it 103 times, the device continues to exhibit exceptional electrical characteristics. It can also be implemented for transitions between high and low resistance states, even in temperatures of up to 300 ℃. More importantly, the biological synaptic characteristics of paired-pulse facilitation/depression （PPF/PPD） and spike- timing-dependent plasticity （STDP） were observed through applying different pulse measurement modes. This work demonstrates that flexible memristor devices on mica substrates may potentially allow for the realization of high-temperature memristor applications for biologically-inspired computing systems.

A robust graphene oxide memristor enabled by organic pyridinium intercalation for artificial biosynapse application

Graphene oxide(GO)-based memristors offer the promise of low cost,eco-friendliness,and mechanical flexibility,making them attractive candidates for outstanding flexible electronic devices.However,their resistive transitions often display abrupt change rather than bidirectional progressive tuning,which largely limits their applications for biological synapse emulation and neuromorphic computing.Here,a memristor with a novel layered structure of GO/pyridinium/GO is presented with tunable bidirectional feature.The inserted organic pyridinium intercalation succeeds in serving as a satisfactory buffer layer to intrinsically control the formation of conductive filaments during device operation,leading to progressive conductance regulation.Thus,the essential synaptic behaviors including analog memory characteristics,excitatory postsynaptic current,paired pulse facilitation,prepulse inhibition,spike-timing-dependent plasticity,and spike-rate-dependent plasticity are replicated.The emulation of brain-like“learning-forgetting-relearning”process is also implemented.Additionally,the instant responses of the memristor can be stimulated by low operational voltages and short pulse widths.This study paves one way for GO-based memristors to actuate appealing features such as bidirectional tuning and fast speed switching that are desirable for the development of bio-inspired neuromorphic systems.

Flexible artificial synapse based on single-crystalline BiFeO_(3) thin film

Realization of functional flexible artificial synapse is a significant step toward neuromorphic computing.Herein,a flexible artificial synapse based on ferroelectric tunnel junctions(FTJs)is demonstrated,using BiFeO_(3)(BFO)thin film as the functional layer.The inorganic single crystalline FTJs grown on rigid perovskite substrates at high temperatures are integrated with the flexible plastic substrates,by using the water-soluble Sr_(3)Al_(2)O_(6)(SAO)as the sacrificial layer and the following transfer.The transferred freestanding BFO thin film exhibits excellent ferroelectric properties.Moreover,the memristive properties and the brain-like synaptic learning performance of the flexible FTJs are investigated.The results show that multilevel resistance states were maintained well of the flexible artificial synapse,together with their stable synaptic learning properties.Our work indicates the promising opportunity of ferroelectric thin film based flexible synapse used in the future neuromorphic computing system.

A flexible BiFeO_(3)-based ferroelectric tunnel junction memristor for neuromorphic computing

Ferroelectric tunnel junctions(FTJs)as the artificial synaptic devices have been considered promising for constructing brain-inspired neuromorphic computing systems.However,the memristive synapses based on the flexible FTJs have been rarely studied.Here,we report a flexible FTJ memristor grown on a mica substrate,which consists of an ultrathin ferroelectric barrier of BiFeO_(3),a semiconducting layer of ZnO,and an electrode of SrRuO_(3).The obtained flexible FTJ memristor exhibits stable voltage-tuned multistates,and the resistive switchings are robust after 10^(3) bending cycles.The capability of the FTJ as a flexible synaptic device is demonstrated by the functionality of the spike-timing-dependent plasticity with bending,and the accurate conductance manipulation with small nonlinearity(-0.24)and low cycle-to-cycle variation(1.77%)is also realized.Especially,artificial neural network simulations based on experimental device behaviors reveal that the high recognition accuracies up to 92.8%and 86.2%are obtained for handwritten digits and images,respectively,which are close to the performances for ideal memristors.This work highlights the potential applications of FTJ as flexible electronics for data storage and processing.

柔性人工突触:面向智能人机交互界面和高效率神经网络计算的基础器件

人工智能技术的发展为人机交互、感知系统、机器人及假肢的控制等带来了革命性变化,同时对复杂数据的处理和人机交互界面提出了新的要求。不同于目前基于软件系统和冯·诺依曼构架实现的神经网络,人脑运算方式具有高效率和低功耗的特点。因此,在硬件层面上模拟人脑的神经拟态器件,对构建新的运算系统具有重要意义。此外,神经拟态器件能够将传感器数字信号转变成类神经模拟信号,有望实现与生物神经信号的兼容,构建智能、高效的人机交互界面。因此,神经形态器件受到了广泛研究,其相关材料、制备工艺和器件结构不断得到优化,例如基于晶体管和忆阻器的柔性仿生人工突触器件均实现了视觉信息处理、运动识别、类脑神经记忆等功能。目前,虽然随着研究的不断深入,仿生人工突触器件的工作原理得到了一定解释,但深入的机理仍有待挖掘:(1)针对生物个体间的差异,以及同一个体不同感知系统的差异,需要对人工突触器件突触后信号进行调控,以获得与生物神经信号更好的兼容性;(2)生物突触的树突结构,能够搜集、整合和调制时间和空间的信号,模拟树突的信号整合机制,将有助于改善多栅极人工突触晶体管的设计方案,实现对人工突触器件信号整合功能的调控;(3)目前多数研究是基于硬质衬底上的器件设计,对于在柔性衬底上的形变-异质界面-器件电子学性能的规律还有待研究,需要对应力应变下柔性人工突触器件的稳定性与失效机制进行探究。本文归纳了柔性仿生人工突触器件的最新研究进展,分别从器件结构、材料选择、工作机理等角度进行介绍,分析了人工突触器件面临的问题和潜在应用领域。本综述期望为柔性人工突触的设计、制备和应用提供一定参考。