Magnetization Vector Rotation Reservoir Computing Operated by Redox Mechanism.
basic_science · Level V
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- Record sourced from PubMed, PMID 38513213.
- Also identified by DOI 10.1021/acs.nanolett.3c05029.
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Abstract
Physical reservoir computing is a promising way to develop 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 results 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 do 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 the previous physical reservoir. The normalized mean square error of the reservoir on a second-order nonlinear equation task was 1.69 × 10<sup>-3</sup>, which is lower than that of a memristor array (3.13 × 10<sup>-3</sup>) even though the number of reservoir nodes was fewer than half that of the memristor array.