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Magnetization Vector Rotation Reservoir Computing Operated by Redox Mechanism

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Physical reservoir computing is a promising way to develop an efficient artificial intelligence using physical devices exhibiting nonlinear dynamics. Although magnetic materials have advantages in miniaturization, the need for a magnetic field and large electric current result in high electric power consumption and a complex device structure. To resolve these issues, we propose a redox-based physical reservoir utilizing the planar Hall effect and anisotropic magnetoresistance, which are phenomena described by different nonlinear functions of the magnetization vector, that does not need a magnetic field to be applied. The expressive power of this reservoir based on a compact all-solid-state redox transistor is higher than previous physical reservoir. The normalized mean square error of the reservoir on a second-order nonlinear equation task was 1.69×10-3, which is lower than that of a memristor array (3.13×10-3) even though the number of reservoir nodes was fewer than half that of the memristor array.

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  • 17/04/2024
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  • This document is the unedited Author’s version of a Submitted Work that was subsequently accepted for publication in Nano Letters, copyright © 2024 American Chemical Society after peer review. To access the final edited and published work see https://doi.org/10.1021/acs.nanolett.3c05029
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