Short-Term Synaptic Plasticity Regulation in Solution-Gated Indium–Gallium–Zinc-Oxide Electric-Double-Layer Transistors

Wan, Chunru; Liu, Yanghui; Zhu, Li; Feng, Ping; Shi, Yi; Wan, Qing

doi:10.1021/acsami.5b12726

Cited by 88 publications

(67 citation statements)

References 31 publications

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“…It means that the second learning rule is easier than the first, which is similar to the human memory. Furthermore, two terminal IGZO‐based synaptic transistors are highly researched by fabricating an electric‐double‐layer (EDL) unit . In 2015, Zhou et al fabricated three‐terminal transistors with IGZO channel on ITO substrate and InZnO (IZO) source and drain.…”

Section: Metal Oxidesmentioning

confidence: 99%

Recent Advances in Memristive Materials for Artificial Synapses

Kim

Han

Kim

et al. 2018

Adv Materials Technologies

200

126

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required. Several types of emerging mem ories have been researched in the past few decades such as magnetic memory, phase change memory, ferroelectric tunnel junc tions, and resistive switching memory. Among these emerging devices, resistive switching memory called memristors, introduced by Chua in 1971, [1] have strong points of small cell size, nonvolatile and random data access possibility, easy fabri cation process, and simple structure. [2,3] Because of these advantages, various mate rials are examined for achieving memris tive properties.In addition, different from the past sev eral decades, information is being made depending on experiences or repeated stimuli similar to that in the human brain. The human brain contains ≈10 11 neurons and 10 15 synapses, occupies a small space, and consumes less than 20 W, which is lower than the power required to run a household light bulb. [4][5][6] Moreover, the human brain is currently considered as the most intelligent and fastest operation system. Therefore, neuromorphic computing, which emu lates the human brain, has been regarded as a promising nextgeneration computing system. Studies on neuromorphic computing have been rapidly growing and highlighted for various applications such as artificial intelligence, sensors, robotic devices, and memory devices.Existing neural networks are implemented by the combination of machine learning as software and the von Neumann archi tecture as hardware based on the complementary metaloxide semiconductor (CMOS) technology. However, CMOSbased cir cuits require 6-12 transistors and the design is not flexible. [7] The present computing system with the von Neumann architecture is implemented by a serial operation through a central processing unit (CPU). Because of the von Neumann bottleneck, memory devices have limitations in data processing speed between memory and CPU and require high power and large space. [8][9][10] Therefore, a new neuromorphic computing system that is exe cuted by parallel operation with a high operation speed, low energy consumption, and small volume is critically required.To achieve such requirement, memristive materials have been actively examined as emulating several functions of human brain. A memristor could act as a single unit of synapse without software programming supports. Memristorbased neu romorphic architecture is implemented by parallel operation with efficient power, small volume, and high data processing Neuromorphic architectures are in the spotlight as promising candidates for substituting current computing systems owing to their high operation speed, scale-down ability, and, especially, low energy consumption. Among candidate materials, memristors have shown excellent synaptic behaviors such as spike time-dependent plasticity and spike rate-dependent plasticity by gradually changing their resistance state according to electrical input stimuli. Memristor can work as a single synapse without programming support, which remarkably satisfies the requirements of neuromorphic computing. Here, the mo...

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Section: Metal Oxidesmentioning

confidence: 99%

Recent Advances in Memristive Materials for Artificial Synapses

Kim

Han

Kim

et al. 2018

Adv Materials Technologies

200

126

View full text Add to dashboard Cite

show abstract

“…33,34 Short term synaptic plasticity is demonstrated with aqueous gated Indium Gallium Zinc oxide (IGZO) synaptic devices using water and salt as gate electrolyte. 35 However, dissolution of the IGZO films in water and irreversible electrochemical reactions at interface are a major concern in these types of devices. 36 TCO devices employing a ferroelectric gate insulator have also been reported to show EPSC behaviour.…”

Section: Introductionmentioning

confidence: 99%

Nanoionics-Based Three-Terminal Synaptic Device Using Zinc Oxide

Pillai

Souza

2017

ACS Appl. Mater. Interfaces

145

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“…[26,[52][53][54] IGZO-based synaptic devices are expected to emulate basic synaptic behaviors. [55][56][57][58][59] Critically, IGZO shows strong persistent photoconduction (PPC) behavior with continuous high photoconductivity after taking away the light illumination, which is beneficial to realize photonic synaptic devices. [60][61][62] Lee et al reported an IGZO-based synaptic device to emulate major synaptic functions, such as short-term and long-term memory, neural facilitation and symmetric STDP.…”

Section: Oxide Semiconductorsmentioning

confidence: 99%

Recent Progress in Photonic Synapses for Neuromorphic Systems

Zhang

Dai

Zhao

et al. 2020

Advanced Intelligent Systems

165

118

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Implementing synaptic functions with electronic devices is critical to achieve neuromorphic systems on the hardware platform, as synapses play important roles in brain computing and memory. Synapses modulated by light signals, which are also referred as photonic synapses, can not only make effective use of the outstanding properties of light to provide devices with ultrahigh propagation speed, high bandwidth and low crosstalk but also provide a noncontact writing method, which can facilitate the evolution of optical wireless communication and operation. More importantly, real‐time image processing can also be performed by photonic synapses which possess temporary memory. Thus far, tremendous efforts have been taken to design and fabricate photonic synapses. Herein, a summary of the development of different kinds of emerging materials utilized in photonic synaptic devices including memristors, field‐effect transistors, and phase change memory is presented, followed by the innovative applications of photonic synapses for neuromorphic systems. Finally, some current challenges and future study directions are discussed.

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Short-Term Synaptic Plasticity Regulation in Solution-Gated Indium–Gallium–Zinc-Oxide Electric-Double-Layer Transistors

Cited by 88 publications

References 31 publications

Recent Advances in Memristive Materials for Artificial Synapses

Recent Advances in Memristive Materials for Artificial Synapses

Nanoionics-Based Three-Terminal Synaptic Device Using Zinc Oxide

Recent Progress in Photonic Synapses for Neuromorphic Systems

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