3D-structured mesoporous silica memristors for neuromorphic switching and reservoir computing-Reference-Cited by-同舟云学术

3D-structured mesoporous silica memristors for neuromorphic switching and reservoir computing

Published:2022 Issue:46 Volume:14 Page:17170-17181
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Jaafar Ayoub H.¹²,Shao Li³,Dai Peng¹,Zhang Tongjun¹,Han Yisong⁴,Beanland Richard⁴,Kemp Neil T.²,Bartlett Philip N.³^ORCID,Hector Andrew L.³^ORCID,Huang Ruomeng¹^ORCID

Affiliation:

1. School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK

2. School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK

3. School of Chemistry, University of Southampton, Southampton, SO17 1BJ, UK

4. Department of Physics, University of Warwick, Coventry, CV4 7AL, UK

Abstract

This work experimentally implements a physical reservoir computing system using a highly ordered, 3D-structured mesoporous silica (mSiO2) thin film based memristor to achieve pattern recognition with high accuracy.

Funder

Engineering and Physical Sciences Research Council

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2022/NR/D2NR05012A

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