Habituation/Fatigue behavior of a synapse memristor based on IGZO–HfO2 thin film

Jiang, Runqing; Ma, Pengfei; Han, Zhewen; Du, Xuesen

doi:10.1038/s41598-017-09762-5

Cited by 44 publications

(37 citation statements)

References 40 publications

(35 reference statements)

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“…Under relatively positive V bg (0 V relative to −20 V), the process of returning electrons from MoS 2 to PTCDA is suppressed, resulting in a longer recovery relaxation time and finally LTP formation. Besides, we have demonstrated the transition from short‐term to long‐term plasticity by increasing the number of laser pulses (duration: 100 ms, interval between pulses: 25 ms, V bg 0 V, V ds 1 V) . When applying a single laser pulse, it appears as STP.…”

mentioning

confidence: 85%

A MoS₂/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

et al. 2018

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Just as biological synapses provide basic functions for the nervous system, artificial synaptic devices serve as the fundamental building blocks of neuromorphic networks; thus, developing novel artificial synapses is essential for neuromorphic computing. By exploiting the band alignment between 2D inorganic and organic semiconductors, the first multi-functional synaptic transistor based on a molybdenum disulfide (MoS 2 )/perylene-3,4,9,10-tetracarboxylic dianhydride (PTCDA) hybrid heterojunction, with remarkable short-term plasticity (STP) and longterm plasticity (LTP), is reported. Owing to the elaborate design of the energy band structure, both robust electrical and optical modulation are achieved through carriers transfer at the interface of the heterostructure, which is still a challenging task to this day. In electrical modulation, synaptic inhibition and excitation can be achieved simultaneously in the same device by gate voltage tuning. Notably, a minimum inhibition of 3% and maximum facilitation of 500% can be obtained by increasing the electrical number, and the response to different frequency signals indicates a dynamic filtering characteristic. It exhibits flexible tunability of both STP and LTP and synaptic weight changes of up to 60, far superior to previous work in optical modulation. The fully 2D MoS 2 /PTCDA hybrid heterojunction artificial synapse opens up a whole new path for the urgent need for neuromorphic computation devices.

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mentioning

confidence: 85%

A MoS₂/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

et al. 2018

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“…e) The current decay curves according to the different number of input pulses. Reproduced under the terms of the CC‐BY Creative Commons Attribution 4.0 International License . Copyright 2017, Springer Nature.…”

Section: Metal Oxidesmentioning

confidence: 99%

“…The heterojunction structure with IGZO as the oxygen‐rich layer and HfO 2 as the oxygen‐deficient film is also fabricated as a synaptic memristor by Jiang et al in 2017 . They generated the Al/HfO 2 /IGZO/Au structure as shown in Figure c.…”

Section: Metal Oxidesmentioning

confidence: 99%

Recent Advances in Memristive Materials for Artificial Synapses

Kim

Han

Kim

et al. 2018

Adv Materials Technologies

193

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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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“…There are key functions that the synaptic devices should emulate, such as a spike-timing-dependent plasticity (STDP), short-term memory (STM) to long-term memory (LTM) transition, and facilitation (Figure 6a-d). Indeed, there are other possible types for synaptic devices (e.g., resistive switching devices [48,49], atomic-switching devices [50], and transistor-based devices [51][52][53]), which use an electrical signal, as the biological synapse does. Compared to these electrical-stimulus types, TCO-based synaptic devices, which use an optical stimulus, may offer much wider bandwidth, ultrafast signal transmission, low crosstalk, and being avoided from electrical shortcoming induced by a parasitic effect like the Miller effect [26,54].…”

Section: Optical Synaptic Devices With An Optical Memory-actionmentioning

confidence: 99%

Thin-Film Optical Devices Based on Transparent Conducting Oxides: Physical Mechanisms and Applications

et al. 2019

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This paper provides a review of optical devices based on a wide band-gap transparent conducting oxide (TCO) while discussing related physical mechanisms and potential applications. Intentionally using a light-induced metastability mechanism of oxygen defects in TCOs, it is allowed to detect even visible lights, eluding to a persistent photoconductivity (PPC) as an optical memory action. So, this PPC phenomenon is naturally useful for TCO-based optical memory applications, e.g., optical synaptic transistors, as well as photo-sensors along with an electrical controllability of a recovery speed with gate pulse or bias. Besides the role of TCO channel layer in thin-film transistor structure, a defective gate insulator can be another approach for a memory operation with assistance for gate bias and illuminations. In this respect, TCOs can be promising materials for a low-cost transparent optoelectronic application.

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Habituation/Fatigue behavior of a synapse memristor based on IGZO–HfO2 thin film

Cited by 44 publications

References 40 publications

A MoS₂/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

A MoS₂/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

Recent Advances in Memristive Materials for Artificial Synapses

Thin-Film Optical Devices Based on Transparent Conducting Oxides: Physical Mechanisms and Applications

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Habituation/Fatigue behavior of a synapse memristor based on IGZO–HfO2 thin film

Cited by 44 publications

References 40 publications

A MoS2/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

A MoS2/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

Recent Advances in Memristive Materials for Artificial Synapses

Thin-Film Optical Devices Based on Transparent Conducting Oxides: Physical Mechanisms and Applications

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A MoS₂/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility

A MoS₂/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility