RESEARCH ARTICLE

Direct laser writing of graphene oxide for ultra-low power consumption memristors in reservoir computing for digital recognition

¹ Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200090, China
² Centre for Artificial-Intelligence Nanophotonics, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200090, China

^* Corresponding authors (emails: qimingzhang@usst.edu.cn (Min Gu); gumin@usst.edu.cn (Qiming Zhang))

Received: 10 March 2022
Revised: 12 April 2022
Accepted: 12 May 2022

Abstract

A memristor is a promising candidate of new electronic synaptic devices for neuromorphic computing. However, conventional memristors often exhibit complex device structures, cumbersome manufacturing processes, and high energy consumption. Graphene-based materials show great potential as the building materials of memristors. With direct laser writing technology, this paper proposes a lateral memristor with reduced graphene oxide (rGO) and Pt as electrodes and graphene oxide (GO) as function material. This Pt/GO/rGO memristor with a facile lateral structure can be easily fabricated and demonstrates an ultra-low energy consumption of 200 nW. Typical synaptic behaviors are successfully emulated. Meanwhile, the Pt/GO/rGO memristor array is applied in the reservoir computing network, performing the digital recognition with a high accuracy of 95.74%. This work provides a simple and low-cost preparation method for the massive production of artificial synapses with low energy consumption, which will greatly facilitate the development of neural network computing hardware platforms.