Perovskite-based optoelectronic artificial synaptic thin-film transistor

Y. X. Cao; C. Zhao; L. Yin; L. M. Shi; J. B. Zhou; Z. Y. Zhang; R. Wu; Q. Y. Yang; M. T. Yuan; M. Q. Gu

doi:10.1016/j.sse.2023.108713

Perovskite-based optoelectronic artificial synaptic thin-film transistor

Y. X. Cao, C. Zhao^*, L. Yin, L. M. Shi, J. B. Zhou, Z. Y. Zhang, R. Wu, Q. Y. Yang, M. T. Yuan, M. Q. Gu

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

Traditional computer processing requires a large amount of data transmission between the processor and the storage unit, which limits the metering efficiency and the scalability of the architecture. To solve the limit, the concept of a brain-like parallel computing system based on artificial synapses was proposed. This work presents an optoelectronic synapse based on perovskite. The energy band of the perovskite material matches that of the metal oxide semiconductor, allowing the device to possess synaptic plasticity and thus be used to simulate biological synapses. Finally, based on the proof of concept, the neural network classification process using artificial synaptic devices was simulated.

Original language	English
Article number	108713
Journal	Solid-State Electronics
Volume	208
DOIs	https://doi.org/10.1016/j.sse.2023.108713
Publication status	Published - Oct 2023

Keywords

Artificial synaptic
Neuromorphic computing
Optoelectronic devices
Perovskite

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10.1016/j.sse.2023.108713

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title = "Perovskite-based optoelectronic artificial synaptic thin-film transistor",

abstract = "Traditional computer processing requires a large amount of data transmission between the processor and the storage unit, which limits the metering efficiency and the scalability of the architecture. To solve the limit, the concept of a brain-like parallel computing system based on artificial synapses was proposed. This work presents an optoelectronic synapse based on perovskite. The energy band of the perovskite material matches that of the metal oxide semiconductor, allowing the device to possess synaptic plasticity and thus be used to simulate biological synapses. Finally, based on the proof of concept, the neural network classification process using artificial synaptic devices was simulated.",

keywords = "Artificial synaptic, Neuromorphic computing, Optoelectronic devices, Perovskite",

author = "Cao, {Y. X.} and C. Zhao and L. Yin and Shi, {L. M.} and Zhou, {J. B.} and Zhang, {Z. Y.} and R. Wu and Yang, {Q. Y.} and Yuan, {M. T.} and Gu, {M. Q.}",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

month = oct,

doi = "10.1016/j.sse.2023.108713",

language = "English",

volume = "208",

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T1 - Perovskite-based optoelectronic artificial synaptic thin-film transistor

AU - Cao, Y. X.

AU - Zhao, C.

AU - Yin, L.

AU - Shi, L. M.

AU - Zhou, J. B.

AU - Zhang, Z. Y.

AU - Wu, R.

AU - Yang, Q. Y.

AU - Yuan, M. T.

AU - Gu, M. Q.

PY - 2023/10

Y1 - 2023/10

N2 - Traditional computer processing requires a large amount of data transmission between the processor and the storage unit, which limits the metering efficiency and the scalability of the architecture. To solve the limit, the concept of a brain-like parallel computing system based on artificial synapses was proposed. This work presents an optoelectronic synapse based on perovskite. The energy band of the perovskite material matches that of the metal oxide semiconductor, allowing the device to possess synaptic plasticity and thus be used to simulate biological synapses. Finally, based on the proof of concept, the neural network classification process using artificial synaptic devices was simulated.

AB - Traditional computer processing requires a large amount of data transmission between the processor and the storage unit, which limits the metering efficiency and the scalability of the architecture. To solve the limit, the concept of a brain-like parallel computing system based on artificial synapses was proposed. This work presents an optoelectronic synapse based on perovskite. The energy band of the perovskite material matches that of the metal oxide semiconductor, allowing the device to possess synaptic plasticity and thus be used to simulate biological synapses. Finally, based on the proof of concept, the neural network classification process using artificial synaptic devices was simulated.

KW - Artificial synaptic

KW - Neuromorphic computing

KW - Optoelectronic devices

KW - Perovskite

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DO - 10.1016/j.sse.2023.108713

M3 - Article

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SN - 0038-1101

VL - 208

JO - Solid-State Electronics

JF - Solid-State Electronics

M1 - 108713

ER -

Perovskite-based optoelectronic artificial synaptic thin-film transistor

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Keywords

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