基于ZnO忆阻器的神经突触仿生电子器件

本文采用ZnO忆阻器模拟了生物神经突触的记忆和学习功能。ZnO突触器件表现出典型的随时间指数衰减的突触后兴奋电流(EPSC),以及EPSC的双脉冲增强行为。在此基础上,实现了学习-遗忘-再学习的经验式学习行为,以及四种不同种类的电脉冲时刻依赖可塑性学习规则。ZnO突触器件实现了超低能耗操作,单次突触行为能耗最低为1.6pJ,表明其可以用来构筑未来的人工神经网络硬件系统,最终开发出与人脑结构类似的认知型计算机以及类人机器人。     

ZnO全光控忆阻器及其类突触行为

本研究基于ZnO制备了一种全光控忆阻器,短波光照射可增大器件电导,长波光则可降低电导,并且电导态可以长时间保持.因此,通过改变施加光信号的波长,可实现忆阻器电导的可逆调控.基于以上特性,该器件可以模拟突触基本功能,包括长程增强与长程抑制、光功率密度依赖可塑性、频率依赖可塑性以及学习-遗忘-再学习的经验学习行为.与电相比...     

CuS/ZnS/ITO透明忆阻器的制备及其突触性能

忆阻器突触可用于构建神经形态系统,进行类脑计算,而透明突触器件则有利于光电协同调控.本研究首次采用CuS薄膜作为电极,构筑了CuS/ZnS/ITO透明忆阻器,器件表现出稳定的忆阻性能与良好的均一性,在可见光范围内透过率高达82％.通过与Cu制电极的器件比较,采用CuS制电极可以抑制Cu离子向ZnS介质层中大量迁移,有利...     

石墨烯衍生材料在忆阻器中的应用

基于目前石墨烯在忆阻器中应用的最新研究进展,从石墨烯类忆阻器的基本结构出发,评述了石墨、氧化石墨烯、石墨烯在忆阻器中的应用方式,分析了石墨烯类阻变材料的阻变特性、阻变机理及界面势垒调节和电荷陷阱充放电两种模型,最后介绍了目前石墨烯衍生忆阻装置亟待解决的问题和发展方向。     

忆阻器材料的研究进展

忆阻器(RRAM)是一种新兴的非挥发性存储器,具有简单的器件结构、较快的操作速度和相对较小的功耗。简述了忆阻器的基本原理以及该领域材料方面的最新研究进展,其中重点介绍了HP忆阻器模型;综述了基于不同薄膜材料制备的忆阻器的特性,如有机材料、固态电解液材料、多元金属氧化物、二元金属氧化物等;阐述了忆阻器的重要意义及面临的巨大挑战,提出了未来该领域需要加强研究的若干问题。     

氧化铁忆阻器中缺陷态诱导的模拟型阻变及突触双脉冲易化特性

模拟型阻变突触特性能够为神经形态计算提供高的计算精度并避免计算过程中带来的电导卡滞、跃变以及失效等问题。模拟生物突触在刺激脉冲下的行为,能够更好地揭示电子器件的仿生特性机理并为高性能神经形态计算提供支撑。突触双脉冲易化是生物突触的重要特性,反映了在外界刺激作用下的易化和适应性过程,对揭示神经元的工作机制至关重要。为了构建突触双脉冲易化的模拟型忆阻器件,本研究通过器件的能带结构设计及氧空位缺陷态的调控,利用射频磁控溅射法制备了一种结构为Ag/FeOx/ITO的忆阻器。电学测试结果表明,该器件具有优异的渐进递增的非线性阻变特性,即模拟型阻变特性。在I-V循环扫描3000次范围内,这种器件均表现出模拟型阻变特性,可提供稳定的、可分离的16个电导状态,且在104 s内维持良好,说明这些电导状态是非易失性的,这主要归功于电子在氧空位缺陷态中的捕获与去捕获以及在势垒间隧穿行为。但是,在低电场强度情况下,捕获的热电子有可能会跃迁出浅陷阱能级,而呈现出易失性。根据这种器件的易失性和非易失性共存特性,通过调制电压脉冲宽度、幅度,器件能够表现出很好的突触双脉冲易化特性,显示出该类型器件在神经形态计算中的潜...     

忆阻器与神经元突触联系的分析

忆阻器作为"丢失的原件"被华裔科学家蔡少棠提出,是连接磁通和电荷的电学器件。忆阻器的可操控性和记忆功能,类似神经元细胞的性能。应用忆阻器代替现有晶体管的开关功能,是解决信号的通断智能控制的最理想办法,进而实现神经形态计算系统的智能控制。     

面向类脑计算的氧化物忆阻器

类脑神经形态计算通过电子或光子器件集成来模拟人脑结构和功能。人工突触是类脑系统中数量最多的计算单元。忆阻器可模拟突触功能,并具有优异的尺寸缩放性和低能耗,是实现人工突触的理想元器件。利用欧姆定律和基尔霍夫定律,忆阻器交叉阵列可执行并行的原位乘累加运算,从而大幅提升类脑系统处理模拟信号的速度。氧化物制备容易,和CMOS工艺兼容性强,是使用最广泛的忆阻器材料。本文梳理了氧化物忆阻器的研究进展,分别讨论了电控、光电混合调控和全光控忆阻器,主要聚焦阻变机理、器件结构和性能。电控忆阻器工作一般会产生微结构变化和焦耳热,将严重影响器件稳定性,改进器件结构和材料成分可有效改善器件性能。利用光信号调控忆阻器电导,不仅能降低能耗,而且可避免产生微结构变化和焦耳热,从而有望解决稳定性难题。此外,光控忆阻器能直接感受光刺激,单器件即可实现感/存/算功能,可用于研发新型视觉传感器。因此,全光控忆阻器的实现为忆阻器的研究和应用打开了一扇新窗口。     

氧化物双介质层忆阻器的设计及应用

忆阻器可以在单一器件上实现存储和计算功能,成为打破冯·诺依曼瓶颈的核心电子元器件之一。它凭借独特的易失性/非易失性电阻特性,可以很好地模拟大脑活动中的突触/神经元的功能。此外,基于金属氧化物的忆阻器与传统的互补金属氧化物半导体(CMOS)工艺兼容,受到了广泛关注。近年来,研究提出了多种基于单介质层结构的金属氧化物忆阻器,但仍然存在高低阻态不稳定、开关电压波动大和循环耐久性差等问题。在此基础上,研究人员通过在金属氧化物忆阻器中引入双介质层成功优化了忆阻器的性能。本文首先详细介绍了氧化物双介质层忆阻器的优势,阐述了氧化物双介质层忆阻器的阻变机理和设计思路,并进一步介绍了氧化物双介质层忆阻器在神经形态计算中的应用。本文将为设计更高性能的氧化物双介质层忆阻器起到一定的启示作用。     

具有高度连续传导调制的记忆器件及其在电子突触应用中的基本物理机制

新兴的忆阻器可以用作模拟记忆和计算功能的人工突触.在这项工作中,受钽氧化物记忆特性的启发,我们设计了一种结构为TiN/Ta2O5-x/HfxZr1-xO2(x=0.5)/Pt(TTHZOP)的忆阻器.通过调整电压扫描的电压脉冲参数(即振幅、脉宽和数量),可以连续调节器件的电导.此外,对于正负两部分,扫描周期的电流-电压...     

Mimicking Synaptic Plasticity and Neural Network Using Memtranstors

Artificial synaptic devices that mimic the functions of biological synapses have drawn enormous interest because of their potential in developing brain‐inspired computing. Current studies are focusing on memristive devices in which the change of the conductance state is used to emulate synaptic behaviors. Here, a new type of artificial synaptic devices based on the memtranstor is demonstrated, which is a fundamental circuit memelement in addition to the memristor, memcapacitor, and meminductor. The state of transtance (presented by the magnetoelectric voltage) in memtranstors acting as the synaptic weight can be tuned continuously with a large number of nonvolatile levels by engineering the applied voltage pulses. Synaptic behaviors including the long‐term potentiation, long‐term depression, and spiking‐time‐dependent plasticity are implemented in memtranstors made of Ni/0.7Pb(Mg_1/3Nb_2/3)O₃‐0.3PbTiO₃/Ni multiferroic heterostructures. Simulations reveal the capability of pattern learning in a memtranstor network. The work elucidates the promise of memtranstors as artificial synaptic devices with low energy consumption.     

A Synaptic Transistor based on Quasi‐2D Molybdenum Oxide

Biological synapses store and process information simultaneously by tuning the connection between two neighboring neurons. Such functionality inspires the task of hardware implementation of neuromorphic computing systems. Ionic/electronic hybrid three‐terminal memristive devices, in which the channel conductance can be modulated according to the history of applied voltage and current, provide a more promising way of emulating synapses by a substantial reduction in complexity and energy consumption. 2D van der Waals materials with single or few layers of crystal unit cells have been a widespread innovation in three‐terminal electronic devices. However, less attention has been paid to 2D transition‐metal oxides, which have good stability and technique compatibility. Here, nanoscale three‐terminal memristive transistors based on quasi‐2D α‐phase molybdenum oxide (α‐MoO₃) to emulate biological synapses are presented. The essential synaptic behaviors, such as excitatory postsynaptic current, depression and potentiation of synaptic weight, and paired‐pulse facilitation, as well as the transition of short‐term plasticity to long‐term potentiation, are demonstrated in the three‐terminal devices. These results provide an insight into the potential application of 2D transition‐metal oxides for synaptic devices with high scaling ability, low energy consumption, and high processing efficiency.     

Synaptic Barristor Based on Phase‐Engineered 2D Heterostructures

The development of energy‐efficient artificial synapses capable of manifoldly tuning synaptic activities can provide a significant breakthrough toward novel neuromorphic computing technology. Here, a new class of artificial synaptic architecture, a three‐terminal device consisting of a vertically integrated monolithic tungsten oxide memristor, and a variable‐barrier tungsten selenide/graphene Schottky diode, termed as a ‘synaptic barrister,’ are reported. The device can implement essential synaptic characteristics, such as short‐term plasticity, long‐term plasticity, and paired‐pulse facilitation. Owing to the electrostatically controlled barrier height in the ultrathin van der Waals heterostructure, the device exhibits gate‐controlled memristive switching characteristics with tunable programming voltages of 0.2?0.5 V. Notably, by electrostatic tuning with a gate terminal, it can additionally regulate the degree and tuning rate of the synaptic weight independent of the programming impulses from source and drain terminals. Such gate tunability cannot be accomplished by previously reported synaptic devices such as memristors and synaptic transistors only mimicking the two‐neuronal‐based synapse. These capabilities eventually enable the accelerated consolidation and conversion of synaptic plasticity, functionally analogous to the synapse with an additional neuromodulator in biological neural networks.     

Short-Term Synaptic Plasticity Mimicked on Ionic/Electronic Hybrid Oxide Synaptic Transistor Gated by Nanogranular SiO_2 Films

An indium-zinc-oxide （IZO） based ionic/electronic hybrid synaptic transistor gated by field-configurable nanogranular SiO2 films was reported. The devices exhibited a high current ON/OFF ratio of above 107, a high electron mobility of ～14 cm2 V^-1 s^-1 and a low subthreshold swing of ～80 mV/decade. The gate bias would modulate the interplay between protons and electrons at the channel/dielectric interface. Due to the dynamic modulation of the transient protons flux within the nanogranular SiO2 films, the channel current would be modified dynamically. Short-term synaptic plasticities, such as short-term potentiation and short- term depression, were mimicked on the proposed IZO synaptic transistor. The results indicate that the synaptic transistor proposed here has potential applications in future neuromorphic devices.     

ZnO基电阻存储材料的研究与进展

在电阻存储技术的快速发展中,电阻存储材料是其发展的关键基础。因此探索新型、高效、环保的电阻存储材料是推进电阻存储技术发展的研究热点。ZnO自身具备优异的光学特性,结合可调控的电学、磁学特性,被誉为最有应用潜力的电阻存储材料。扼要介绍了ZnO基电阻存储材料的研究概况,结合大数据时代信息存储的背景回顾了ZnO基存储材料的研究进展、物理机制,对以往的研究工作进行了归纳与总结,并阐述了未来的发展趋势。     

The Design of 3D‐Interface Architecture in an Ultralow‐Power,Electrospun Single‐Fiber Synaptic Transistor for Neuromorphic Computing

Synaptic electronics is a new technology for developing functional electronic devices that can mimic the structure and functions of biological counterparts. It has broad application prospects in wearable computing chips, human–machine interfaces, and neuron prostheses. These types of applications require synaptic devices with ultralow energy consumption as the effective energy supply for wearable electronics, which is still very difficult. Here, artificial synapse emulation is demonstrated by solid‐ion gated organic field‐effect transistors (OFETs) with a 3D‐interface conducting channel for ultralow‐power synaptic simulation. The basic features of the artificial synapse, excitatory postsynaptic current (EPSC), paired‐pulse facilitation (PPF), and high‐pass filtering, are successfully realized. Furthermore, the single‐fiber based artificial synapse can be operated by an ultralow presynaptic spike down to ?0.5 mV with an ultralow reading voltage at ?0.1 mV due to the large contact surface between the ionic electrolyte and fiber‐like semiconducting channel. Therefore, the ultralow energy consumption at one spike of the artificial synapse can be realized as low as ≈3.9 fJ, which provides great potential in a low‐power integrated synaptic circuit.     

Synergistic Gating of Electro‐Iono‐Photoactive 2D Chalcogenide Neuristors: Coexistence of Hebbian and Homeostatic Synaptic Metaplasticity

Emulation of brain‐like signal processing with thin‐film devices can lay the foundation for building artificially intelligent learning circuitry in future. Encompassing higher functionalities into single artificial neural elements will allow the development of robust neuromorphic circuitry emulating biological adaptation mechanisms with drastically lesser neural elements, mitigating strict process challenges and high circuit density requirements necessary to match the computational complexity of the human brain. Here, 2D transition metal di‐chalcogenide (MoS₂) neuristors are designed to mimic intracellular ion endocytosis–exocytosis dynamics/neurotransmitter‐release in chemical synapses using three approaches: (i) electronic‐mode: a defect modulation approach where the traps at the semiconductor–dielectric interface are perturbed; (ii) ionotronic‐mode: where electronic responses are modulated via ionic gating; and (iii) photoactive‐mode: harnessing persistent photoconductivity or trap‐assisted slow recombination mechanisms. Exploiting a novel multigated architecture incorporating electrical and optical biases, this incarnation not only addresses different charge‐trapping probabilities to finely modulate the synaptic weights, but also amalgamates neuromodulation schemes to achieve “plasticity of plasticity–metaplasticity” via dynamic control of Hebbian spike‐time dependent plasticity and homeostatic regulation. Coexistence of such multiple forms of synaptic plasticity increases the efficacy of memory storage and processing capacity of artificial neuristors, enabling design of highly efficient novel neural architectures.     

Ion Gated Synaptic Transistors Based on 2D van der Waals Crystals with Tunable Diffusive Dynamics

Neuromorphic computing represents an innovative technology that can perform intelligent and energy‐efficient computation, whereas construction of neuromorphic systems requires biorealistic synaptic elements with rich dynamics that can be tuned based on a robust mechanism. Here, an ionic‐gating‐modulated synaptic transistor based on layered crystals of transitional metal dichalcogenides and phosphorus trichalcogenides is demonstrated, which produce a diversity of short‐term and long‐term plasticity including excitatory postsynaptic current, paired pulse facilitation, spiking‐rate‐dependent plasticity, dynamic filtering, etc., with remarkable linearity and ultralow energy consumption of ≈30 fJ per spike. Detailed transmission electron microscopy characterization and ab initio calculation reveal two‐stage ionic gating effects, namely, surface adsorption and internal intercalation in the channel medium, causing different poststimulation diffusive dynamics and thus accounting for the observed short‐term and long‐term plasticity, respectively. The synaptic activity can therefore be effectively manipulated by tailoring the ionic gating and consequent diffusion dynamics with varied thickness and structure of the van der Waals material as well as the number, duration, rate, and polarity of gate stimulations, making the present synaptic transistors intriguing candidates for low‐power neuromorphic systems.