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

Jaafar, Ayoub H.; Shao, Li; Dai, Peng; Zhang, Tongjun; Han, Yisong; Beanland, Richard; Kemp, Neil T.; Bartlett, Philip N.; Hector, Andrew L.; Huang, Ruomeng

Authors

Li Shao

Peng Dai

Tongjun Zhang

Yisong Han

Richard Beanland

Philip N. Bartlett

Andrew L. Hector

Ruomeng Huang



Contributors

Abstract

Memristors are emerging as promising candidates for practical application in reservoir computing systems that are capable of temporal information processing. Here, we experimentally implement a physical reservoir computing system using resistive memristors based on three-dimensional (3D)-structured mesoporous silica (mSiO2) thin films fabricated by a low cost, fast and vacuum-free sol–gel technique. The in situ learning capability and a classification accuracy of 100% on a standard machine learning dataset are experimentally demonstrated. The volatile (temporal) resistive switching in diffusive memristors arises from the formation and subsequent spontaneous rupture of conductive filaments via diffusion of Ag species within the 3D-structured nanopores of the mSiO2 thin film. Besides volatile switching, the devices also exhibit a bipolar non-volatile resistive switching behavior when the devices are operated at a higher compliance current level. The implementation of mSiO2 thin films opens the route to fabricate a simple and low cost dynamic memristor with a temporal information process functionality, which is essential for neuromorphic computing applications.

Citation

Jaafar, A. H., Shao, L., Dai, P., Zhang, T., Han, Y., Beanland, R., …Huang, R. (2022). 3D-structured mesoporous silica memristors for neuromorphic switching and reservoir computing. Nanoscale, https://doi.org/10.1039/d2nr05012a

Journal Article Type Article
Acceptance Date Nov 10, 2022
Publication Date Nov 16, 2022
Deposit Date Nov 23, 2022
Publicly Available Date Nov 24, 2022
Journal Nanoscale
Print ISSN 2040-3364
Electronic ISSN 2040-3372
Publisher Royal Society of Chemistry
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1039/d2nr05012a
Keywords General Materials Science
Public URL https://nottingham-repository.worktribe.com/output/14034508

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