Spintronics, utilizing both the charge and spin of electrons, benefits from the nonvolatility, low switching energy, and collective behavior of magnetization. These properties allow the development of magnetoresistive random access memories, with magnetic tunnel junctions (MTJs) playing a central role. Various spin logic concepts are also extensively explored. Among these, spin logic devices based on the motion of magnetic domain walls (DWs) enable the implementation of compact and energy-efficient logic circuits. In these devices, DW motion within a magnetic track enables spin information processing, while MTJs at the input and output serve as electrical writing and reading elements. DW logic holds promise for simplifying logic circuit complexity by performing multiple functions within a single device. Nevertheless, the demonstration of DW logic circuits with electrical writing and reading at the nanoscale is still needed to unveil their practical application potential. In this review, we discuss material advancements for high-speed DW motion, progress in DW logic devices, groundbreaking demonstrations of current-driven DW logic, and its potential for practical applications. Additionally, we discuss alternative approaches for current-free information propagation, along with challenges and prospects for the development of DW logic.
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http://dx.doi.org/10.3390/mi15060696 | DOI Listing |
Alzheimers Dement
December 2024
University of Southern California, Los Angeles, CA, USA.
Background: Optimal cerebral blood flow is crucial to maintaining cognitive function. Cerebrovascular reactivity (CVR) is a dynamic measure of cerebrovascular function which represents the ability of cerebral blood vessels to regulate blood flow in response to vasoactive stimuli. Prior studies have demonstrated an association between impaired CVR and cognitive function in cerebrovascular and neurodegenerative conditions, including cerebral amyloid angiopathy and Alzheimer disease.
View Article and Find Full Text PDFJ Neurol Sci
December 2024
Computational and Translational Neuroscience Laboratory, Institute of Cognitive Sciences and Technologies, National Research Council (CTNLab-ISTC-CNR), Via Gian Domenico Romagnosi 18A, Rome 00196, Italy; AI2Life s.r.l., Innovative Start-Up, ISTC-CNR Spin-Off, Via Sebino 32, Rome 00199, Italy. Electronic address:
Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasive, lacking consideration of sex-based differences. This study introduces an explainable machine learning (ML) system to predict and differentiate the progression of AD based on sex, using non-invasive, easily collectible predictors such as neuropsychological test scores and sociodemographic data, enabling its application in every day clinical settings.
View Article and Find Full Text PDFPhys Rev Lett
November 2024
Center for Quantum Matter, School of Physics, Zhejiang University, Hangzhou 310058, China.
J Phys Condens Matter
November 2024
Institute of Applied Physics, Vienna University of Technology, Wiedner Hauptstr. 8-10/134, Wien, 1040, AUSTRIA.
The transition from planar (2D) to three-dimensional (3D) magnetic nanostructures represents a significant advancement in both fundamental research and practical applications, offering vast potential for next-generation technologies like ultrahigh-density storage, memory, logic, and neuromorphic computing. Despite being a relatively new field, the emergence of 3D nanomagnetism presents numerous opportunities for innovation, prompting the creation of a comprehensive roadmap by leading international researchers. This roadmap aims to facilitate collaboration and interdisciplinary dialogue to address challenges in materials science, physics, engineering, and computing.
View Article and Find Full Text PDFNanoscale Adv
December 2024
Department of Electrical and Electronics Engineering, Koç University Sarıyer Istanbul 34450 Turkey
Nanoscale skyrmions are spin-based quasiparticles that are promising for nonvolatile logic applications. However, the presence of the skyrmion Hall effect (SkHE) in ferromagnetic skyrmions limits their performance in logic devices. Here, we present a detailed micromagnetic modeling study on low-energy skyrmion logic gate circuits based on skyrmions in synthetic antiferromagnetically coupled (SAF) metallic ferromagnetic layers to eliminate the SkHE while reducing current requirements.
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