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

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.

More information

Identifiers

ORCID for Ayoub Hassan Jaafar Hamdiyah: orcid.org/0000-0001-7305-4542

ORCID for Li Shao: orcid.org/0000-0001-6029-5574

ORCID for Peng Dai: orcid.org/0000-0002-5973-9155

ORCID for Philip N. Bartlett: orcid.org/0000-0002-7300-6900

ORCID for Andrew L. Hector: orcid.org/0000-0002-9964-2163

ORCID for Ruomeng Huang: orcid.org/0000-0003-1185-635X

Catalogue record

Export record

Altmetrics