Aqueous solution processed mesoporous silica-gated photo-perception neuromorphic transistor
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Aqueous solution processed mesoporous silica-gated photo-perception neuromorphic transistor Zheng Yu Ren1,2,3,4, Li Qiang Zhu1,2,* Zhi Yuan Li2,4, and Hui Xiao2,4
, Ling Ai2,4,5,*, Xue Qin Lou2,4, Jia Cheng Cai2,4,
1
School of Physical Science and Technology, Ningbo University, Ningbo 315211, Zhejiang, People’s Republic of China Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, Zhejiang, People’s Republic of China 3 School of Physical Science and Technology, Shanghai Tech University, Shanghai 201210, People’s Republic of China 4 University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China 5 Jiangsu Province Cultivation Base for State Key Laboratory of Photovoltaic Science and Technology, Changzhou University, Changzhou 213164, Jiangsu, People’s Republic of China 2
Received: 15 September 2020
ABSTRACT
Accepted: 9 November 2020
Our body is a multiple perception learning system. Bionic application of perception cognitive functions based on neuromorphic electronics would endow artificial intelligence new intension. In particular, electrolyte-gated transistors have been suggested for neuromorphic platform applications. Due to the fundamental limitations for ionic liquid and ionic gel-based electrolyte, it would be interesting to obtain solid-state electrolytes through a vacuum free system. Thus, in the present work, a simple aqueous solution-processed mesoporous silica coating-gated oxide photo-perception neuromorphic transistors have been proposed. The neuromorphic transistors exhibit good electrical performances. A resistor-loaded inverter is built, exhibiting typical inverter operation at low working voltage. ‘Selective potentiation and depression’ behaviors have been mimicked on the neuromorphic transistor. In addition, the proposed neuromorphic transistor shows optical and electrical synergic response behaviors. Neurological behavior of conditioned taste aversion learning has been mimicked. Thus, the single photo-perception neuromorphic transistor could integrate the functions of perception and neuromorphic algorithm. The proposed photo-perception neuromorphic transistors could have potentials in artificial perception learning systems.
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Springer Science+Business
Media, LLC, part of Springer Nature 2020
Handling Editor: Kevin Jones.
Address correspondence to E-mail: [email protected]; [email protected]; [email protected]
https://doi.org/10.1007/s10853-020-05560-z
J Mater Sci
GRAPHICAL ABSTRACT
Introduction Nowadays, brain-inspired neuromorphic computing raises more and more attentions with the coming of big data era. Compared with traditional computation based on Von Neumann architectures, it has the priorities including but not limited to characteristics of parallel processing, high efficiency, low power consumption and autonomous learning [1–3]. Thus, neuromorphic computing provides a new strategy for future computation that can process high throughput data flows in an energy efficient way. Up to date, several kinds
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