JOURNAL ARTICLE

A Fully Printed ZnO Memristor Synaptic Array for Neuromorphic Computing Application

Jiewen ChenQian XuYang LiJie CaoXusheng LiuJie QiuYan ChenMeng-Yang LiuJie YuXumeng ZhangZhi-Wei ZhengMing Wang

Year: 2024 Journal:   IEEE Electron Device Letters Vol: 45 (6)Pages: 1076-1079   Publisher: Institute of Electrical and Electronics Engineers

Abstract

In this letter, we report a fully printed metal-oxide memristor crossbar array based on the Ag/ZnO/Ag structure, and extend its neuromorphic computing application as artificial synapses. The wurtzite-type ZnO is printed as an active layer, which is sandwiched between two printed Ag electrodes, forming a memristor unit. The printed memristor exhibits volatile resistive switching behaviors under a low compliance current of 1 μA, and can emulate the short-term synaptic plasticity and biological "learning-relearning" processes. More importantly, the image learning and forgetting function is successfully demonstrated in a 3 × 3 printable memristor array. These results show that the printing technique offers a promising path towards large-scale and low-cost neuromorphic computing electronics.

Keywords:
Neuromorphic engineering Memristor Crossbar switch Materials science Computer science Resistive random-access memory Nanotechnology Optoelectronics Resistive touchscreen Electronic engineering Electrical engineering Voltage Artificial neural network Artificial intelligence Engineering Telecommunications

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12
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4.43
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28
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0.91
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Citation History

Topics

Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Photoreceptor and optogenetics research
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
Neuroscience and Neural Engineering
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
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