Advanced Functional Materials, volume 32, issue 27, pages 2200959

Ultralow‐Power and Multisensory Artificial Synapse Based on Electrolyte‐Gated Vertical Organic Transistors

Guocai Liu ^{1, 2}

Qingyuan Li ^{1, 2}

Wei Shi ²

Yanwei Liu ^{1, 2}

Kai Liu ²

Xueli Yang ^{1, 2}

Mingchao Shao ^{1, 2}

Ankang Guo ^{1, 2}

Xin Huang ²

Fan Zhang ²

Zhiyuan Zhao ²

Yunlong Guo ²

Yunqi Liu ^{1, 2}

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University of Chinese Academy of Sciences Beijing 100049 P. R. China |

Beijing National Laboratory for Molecular Sciences CAS Key Laboratory of Organic Solids Institute of Chemistry Chinese Academy of Sciences Beijing 100190 P. R. China

Institute of Chemistry, Chinese Academy of Sciences

Beijing National Laboratory for Molecular Sciences

Publication type: Journal Article

Publication date: 2022-04-08

Wiley

Journal: Advanced Functional Materials

Quartile SCImago

Quartile WOS

Impact factor: 19

ISSN: 1616301X, 16163028

DOI: 10.1002/adfm.202200959

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Electronic, Optical and Magnetic Materials

Electrochemistry

Condensed Matter Physics

Biomaterials

Abstract

Bioinspired electronics have shown great potential in the field of artificial intelligence and brain-like science. Low energy consumption and multifunction are key factors for its application. Here, multisensory artificial synapse and neural networks based on electrolyte-gated vertical organic field-effect transistors (VOFETs) are first developed. The channel length of the organic transistor is scaled down to 30 nm through cross-linking strategy. Owing to the short channel length and extremely large capacitance of the electric double layer formed at the electrolyte–channel interface, the minimum power consumption of one synaptic event is 0.06 fJ, which is significantly lower than that required by biological synapses (1–10 fJ). Moreover, the artificial synapse can be trained to learn and memory images in a 5 × 5 synapse array and emulate the human brain's spatiotemporal information processing and sound azimuth detection. Finally, the artificial tongue is designed using the synaptic transistor that can discriminate acidity. Overall, this study provides new insights into realizing energy-efficient artificial synapses and mimicking biological sensory systems.

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	1 2 3 4 5
Advanced Functional Materials	Advanced Functional Materials, 5, 9.43% Advanced Functional Materials 5 publications, 9.43%
Advanced Materials	Advanced Materials, 5, 9.43% Advanced Materials 5 publications, 9.43%
ACS applied materials & interfaces	ACS applied materials & interfaces, 5, 9.43% ACS applied materials & interfaces 5 publications, 9.43%
Advanced Electronic Materials	Advanced Electronic Materials, 3, 5.66% Advanced Electronic Materials 3 publications, 5.66%
Nano Letters	Nano Letters, 3, 5.66% Nano Letters 3 publications, 5.66%
Advanced Science	Advanced Science, 3, 5.66% Advanced Science 3 publications, 5.66%
ACS Applied Electronic Materials	ACS Applied Electronic Materials, 2, 3.77% ACS Applied Electronic Materials 2 publications, 3.77%
Materials Horizons	Materials Horizons, 2, 3.77% Materials Horizons 2 publications, 3.77%
IEEE Electron Device Letters	IEEE Electron Device Letters, 2, 3.77% IEEE Electron Device Letters 2 publications, 3.77%
Sensors	Sensors, 2, 3.77% Sensors 2 publications, 3.77%
Nature	Nature, 1, 1.89% Nature 1 publication, 1.89%
Nature Communications	Nature Communications, 1, 1.89% Nature Communications 1 publication, 1.89%
Journal of Materials Chemistry C	Journal of Materials Chemistry C, 1, 1.89% Journal of Materials Chemistry C 1 publication, 1.89%
Chemistry of Materials	Chemistry of Materials, 1, 1.89% Chemistry of Materials 1 publication, 1.89%
Scientific Reports	Scientific Reports, 1, 1.89% Scientific Reports 1 publication, 1.89%
Small Methods	Small Methods, 1, 1.89% Small Methods 1 publication, 1.89%
Chemical Engineering Journal	Chemical Engineering Journal, 1, 1.89% Chemical Engineering Journal 1 publication, 1.89%
Nanotechnology	Nanotechnology, 1, 1.89% Nanotechnology 1 publication, 1.89%
International Journal of Extreme Manufacturing	International Journal of Extreme Manufacturing, 1, 1.89% International Journal of Extreme Manufacturing 1 publication, 1.89%
Science China Materials	Science China Materials, 1, 1.89% Science China Materials 1 publication, 1.89%
Materials Science and Engineering B: Solid-State Materials for Advanced Technology	Materials Science and Engineering B: Solid-State Materials for Advanced Technology, 1, 1.89% Materials Science and Engineering B: Solid-State Materials for Advanced Technology 1 publication, 1.89%
Applied Materials Today	Applied Materials Today, 1, 1.89% Applied Materials Today 1 publication, 1.89%
Journal of Applied Physics	Journal of Applied Physics, 1, 1.89% Journal of Applied Physics 1 publication, 1.89%
Nature Electronics	Nature Electronics, 1, 1.89% Nature Electronics 1 publication, 1.89%
Advanced Optical Materials	Advanced Optical Materials, 1, 1.89% Advanced Optical Materials 1 publication, 1.89%
Biosensors	Biosensors, 1, 1.89% Biosensors 1 publication, 1.89%
Russian Chemical Reviews	Russian Chemical Reviews, 1, 1.89% Russian Chemical Reviews 1 publication, 1.89%
ACS Materials Letters	ACS Materials Letters, 1, 1.89% ACS Materials Letters 1 publication, 1.89%
Organic Electronics	Organic Electronics, 1, 1.89% Organic Electronics 1 publication, 1.89%
	1 2 3 4 5

Citations by publishers

	2 4 6 8 10 12 14 16 18
Wiley	Wiley, 18, 33.96% Wiley 18 publications, 33.96%
American Chemical Society (ACS)	American Chemical Society (ACS), 12, 22.64% American Chemical Society (ACS) 12 publications, 22.64%
Springer Nature	Springer Nature, 5, 9.43% Springer Nature 5 publications, 9.43%
Elsevier	Elsevier, 4, 7.55% Elsevier 4 publications, 7.55%
Royal Society of Chemistry (RSC)	Royal Society of Chemistry (RSC), 3, 5.66% Royal Society of Chemistry (RSC) 3 publications, 5.66%
Multidisciplinary Digital Publishing Institute (MDPI)	Multidisciplinary Digital Publishing Institute (MDPI), 3, 5.66% Multidisciplinary Digital Publishing Institute (MDPI) 3 publications, 5.66%
IOP Publishing	IOP Publishing, 2, 3.77% IOP Publishing 2 publications, 3.77%
IEEE	IEEE, 2, 3.77% IEEE 2 publications, 3.77%
American Institute of Physics (AIP)	American Institute of Physics (AIP), 2, 3.77% American Institute of Physics (AIP) 2 publications, 3.77%
Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii	Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii, 1, 1.89% Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii 1 publication, 1.89%
	2 4 6 8 10 12 14 16 18

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Liu G. et al. Ultralow‐Power and Multisensory Artificial Synapse Based on Electrolyte‐Gated Vertical Organic Transistors // Advanced Functional Materials. 2022. Vol. 32. No. 27. p. 2200959.

GOST all authors (up to 50) Copy

Liu G., Li Q., Shi W., Liu Y., Liu K., Yang X., Shao M., Guo A., Huang X., Zhang F., Zhao Z., Guo Y., Liu Y. Ultralow‐Power and Multisensory Artificial Synapse Based on Electrolyte‐Gated Vertical Organic Transistors // Advanced Functional Materials. 2022. Vol. 32. No. 27. p. 2200959.

RIS |

Cite this

RIS Copy

TY - JOUR

DO - 10.1002/adfm.202200959

UR - https://doi.org/10.1002/adfm.202200959

TI - Ultralow‐Power and Multisensory Artificial Synapse Based on Electrolyte‐Gated Vertical Organic Transistors

T2 - Advanced Functional Materials

AU - Liu, Guocai

AU - Li, Qingyuan

AU - Liu, Yanwei

AU - Yang, Xueli

AU - Shao, Mingchao

AU - Guo, Ankang

AU - Zhao, Zhiyuan

AU - Guo, Yunlong

AU - Liu, Yunqi

AU - Shi, Wei

AU - Liu, Kai

AU - Huang, Xin

AU - Zhang, Fan

PY - 2022

DA - 2022/04/08 00:00:00

PB - Wiley

SP - 2200959

IS - 27

VL - 32

SN - 1616-301X

SN - 1616-3028

ER -

BibTex |

Cite this

BibTex Copy

@article{2022_Liu,

author = {Guocai Liu and Qingyuan Li and Yanwei Liu and Xueli Yang and Mingchao Shao and Ankang Guo and Zhiyuan Zhao and Yunlong Guo and Yunqi Liu and Wei Shi and Kai Liu and Xin Huang and Fan Zhang},

title = {Ultralow‐Power and Multisensory Artificial Synapse Based on Electrolyte‐Gated Vertical Organic Transistors},

journal = {Advanced Functional Materials},

year = {2022},

volume = {32},

publisher = {Wiley},

month = {apr},

url = {https://doi.org/10.1002/adfm.202200959},

number = {27},

pages = {2200959},

doi = {10.1002/adfm.202200959}

}

MLA

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MLA Copy

Liu, Guocai, et al. “Ultralow‐Power and Multisensory Artificial Synapse Based on Electrolyte‐Gated Vertical Organic Transistors.” Advanced Functional Materials, vol. 32, no. 27, Apr. 2022, p. 2200959. https://doi.org/10.1002/adfm.202200959.

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Publisher

Wiley

Journal

Advanced Functional Materials

Quartile SCImago

Quartile WOS

Impact factor

ISSN

1616301X (Print)
16163028 (Electronic)