Neuromorphic Computing with Emerging Antiferromagnetic Ordering in Spin-Orbit Torque Devices.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 38869369.
- Also identified by DOI 10.1021/acs.nanolett.4c01712 and PMC identifier 11212055.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Field-free switching (FFS) and spin-orbit torque (SOT)-based neuromorphic characteristics were realized in a W/Pt/Co/NiO/Pt heterostructure with a perpendicular exchange bias (<i>H</i><sub>EB</sub>) for brain-inspired neuromorphic computing (NC). Experimental results using NiO-based SOT devices guided the development of fully spin-based artificial synapses and sigmoidal neurons for implementation in a three-layer artificial neural network. This system achieved impressive accuracies of 91-96% when applied to the Modified National Institute of Standards and Technology (MNIST) image data set and 78.85-81.25% when applied to Fashion MNIST images, due presumably to the emergence of robust NiO antiferromagnetic (AFM) ordering. The emergence of AFM ordering favored the FFS with an enhanced <i>H</i><sub>EB</sub>, which suppressed the memristivity and reduced the recognition accuracy. This indicates a trade-off between the requirements for solid-state memory and those required for brain-inspired NC devices. Nonetheless, our findings revealed opportunities by which the two technologies could be aligned via controllable exchange coupling.