Optoelectronic In‐Ga‐Zn‐O Memtransistors for Artificial Vision System

Qiu, Weijie; Huang, Yulong; Kong, Lingan; Yang, Cangjie; Liu, Wanrong; Wang, Zhen; Sun, Jia; Wan, Qing; Cho, Jeong Ho; Yang, Junliang; Gao, Yongli

doi:10.1002/adfm.202002325

Cited by 60 publications

(65 citation statements)

References 57 publications

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“…The response and recovery times of photoreceptors in the human retina ranges from 40 to 150 ms. 6 The presence of high light intensity prolongs the persistence of vision generally for more than 0.1 s. Inspired by the human vision system, combined with advanced articial intelligence technology, an articial vision system with perception, processing and memory has captured the wide attention of researchers. [7][8][9] Synaptic devices for color discrimination are expected to simulate human vision systems to achieve color-sensitive neural network systems. Here, we imitate the photoreceptor cell structure in the human retina by constructing a photonic synaptic sensor based on a halogenadjustable perovskite quantum dot embedded InGaZnO (IGZO) thin-lm transistor.…”

Section: Introductionmentioning

confidence: 99%

Visible-light-stimulated synaptic InGaZnO phototransistors enabled by wavelength-tunable perovskite quantum dots

et al. 2021

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Section: Introductionmentioning

confidence: 99%

Visible-light-stimulated synaptic InGaZnO phototransistors enabled by wavelength-tunable perovskite quantum dots

et al. 2021

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“…The SW duration of STP ranges from tens of milliseconds to a few min, while that of the LTP can last for a long time. [53][54][55][56] The two types of synaptic plasticity can be converted into each other by employing specific stimuli. The learning and memory processes follow the Hebb assumption.…”

Section: Synaptic Plasticitymentioning

confidence: 99%

Recent Advances in Flexible Organic Synaptic Transistors

Liu

Huang

et al. 2021

Adv Elect Materials

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organic electronic devices have attracted substantial attention. [18][19][20][21][22][23][24] However, many issues still exist. For instance, the flexible substrates can be easily bent and thus cause damage to the devices or affect their electrical performance. Moreover, the flexible substrates are sensitive to operating conditions and are unstable during longterm operation. [25][26][27][28][29] Therefore, many research groups have dedicated their efforts to study and improve the flexibility and stretchability of organic electronic devices. [30][31][32][33] In recent years, organic three-terminal synaptic transistors have evolved from two-terminal devices to avoid the problem of crosstalk between adjacent cells. [34] This is an evolutionary structural design to improve the function of organic synaptic devices. In addition, the organic three-terminal synaptic transistors can be designed to form a highly interconnected neural network system. [35] At the same time, the organic three-terminal synaptic transistors can concurrently receive and read stimuli, which is conducive to the design of multiple input devices. [36] Currently, the threeterminal artificial synapses devices based on flexible organic transistors are considered to be the representative structures of biomimetic devices, which can be used to simulate the plasticity of biological synapses. [37,38] Compared with the traditional inorganic synaptic devices, the flexible organic synaptic transistors (FOSTs) can be used to simulate the plasticity of the human brain with a simpler structure and lower manufacturing cost. Therefore, a FOST is a promising component of future organic neuromorphic systems. [39][40][41][42][43][44][45][46] To date, the FOSTs have been widely used in wearable electronic devices and intelligent e-skins. [47][48][49] In 2018, a flexible artificial afferent nerve was reported by Xu et al. [47] representing significant progress toward the development of intelligent e-skin and soft robotics. This paper reviews the recent progress in the development of FOSTs and their applications in neuromorphic systems. Generally, the FOSTs are divided into four categories: flexible organic floating-gate synaptic transistors (FO-FGSTs), flexible organic ferroelectric-gate synaptic transistors (FO-FeGSTs), flexible organic electrolyte-gate synaptic transistors (FO-EGSTs), and flexible organic optoelectronic synaptic transistors (FO-OSTs). First, a brief introduction of the device structure mostly used in the FOSTs is provided. Then, the selection of substrate materials, gate dielectric materials, organic channel materials, and electrode materials in the FOSTs is summarized. Next, the major advances of these FOSTs and their potential applications are reviewed and discussed. Lastly, the summary, outlook, and In recent years, flexible organic synaptic transistors have attracted considerable attention due to their flexibility, biocompatibility, easy processability, and reduced complexity. Flexible organic synaptic transistors have functions and structures sim...

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“…Recently, inspired by a biological vision system, various optoelectronic synaptic devices that can act as both a photodetector and a synapse used for an ANN by preprocessing of the data in a sensor have been demonstrated 9 – 11 . During the optical sensing, however, their synaptic weight is changed owing to an optically controllable synaptic weight.…”

Section: Introductionmentioning

confidence: 99%

Mnemonic-opto-synaptic transistor for in-sensor vision system

Han

Chung

Sim

et al. 2022

Sci Rep

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A mnemonic-opto-synaptic transistor (MOST) that has triple functions is demonstrated for an in-sensor vision system. It memorizes a photoresponsivity that corresponds to a synaptic weight as a memory cell, senses light as a photodetector, and performs weight updates as a synapse for machine vision with an artificial neural network (ANN). Herein the memory function added to a previous photodetecting device combined with a photodetector and a synapse provides a technical breakthrough for realizing in-sensor processing that is able to perform image sensing and signal processing in a sensor. A charge trap layer (CTL) was intercalated to gate dielectrics of a vertical pillar-shaped transistor for the memory function. Weight memorized in the CTL makes photoresponsivity tunable for real-time multiplication of the image with a memorized photoresponsivity matrix. Therefore, these multi-faceted features can allow in-sensor processing without external memory for the in-sensor vision system. In particular, the in-sensor vision system can enhance speed and energy efficiency compared to a conventional vision system due to the simultaneous preprocessing of massive data at sensor nodes prior to ANN nodes. Recognition of a simple pattern was demonstrated with full sets of the fabricated MOSTs. Furthermore, recognition of complex hand-written digits in the MNIST database was also demonstrated with software simulations.

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Optoelectronic In‐Ga‐Zn‐O Memtransistors for Artificial Vision System

Cited by 60 publications

References 57 publications

Visible-light-stimulated synaptic InGaZnO phototransistors enabled by wavelength-tunable perovskite quantum dots

Visible-light-stimulated synaptic InGaZnO phototransistors enabled by wavelength-tunable perovskite quantum dots

Recent Advances in Flexible Organic Synaptic Transistors

Mnemonic-opto-synaptic transistor for in-sensor vision system

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