Magnetic information storage relies on external magnetic fields to encode logical bits through magnetization reversal. But because the magnetic fields needed to operate ultradense storage devices are too high to generate, magnetization reversal by electrical currents is attracting much interest as a promising alternative encoding method. Indeed, spin-polarized currents can reverse the magnetization direction of nanometre-sized metallic structures through torque; however, the high current densities of 10(7)-10(8) A cm(-2) that are at present required exceed the threshold values tolerated by the metal interconnects of integrated circuits. Encoding magnetic information in metallic systems has also been achieved by manipulating the domain walls at the boundary between regions with different magnetization directions, but the approach again requires high current densities of about 10(7) A cm(-2). Here we demonstrate that, in a ferromagnetic semiconductor structure, magnetization reversal through domain-wall switching can be induced in the absence of a magnetic field using current pulses with densities below 10(5) A cm(-2). The slow switching speed and low ferromagnetic transition temperature of our current system are impractical. But provided these problems can be addressed, magnetic reversal through electric pulses with reduced current densities could provide a route to magnetic information storage applications.
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http://dx.doi.org/10.1038/nature02441 | DOI Listing |
Mol Psychiatry
January 2025
Department of Psychiatry, University of Oxford, Oxford, UK.
Cognitive and neural mechanisms underlying bipolar disorder (BD) and its treatment are still poorly understood. Here we examined the role of adaptations in risk-taking using a reward-guided decision-making task. We recruited volunteers with high (n = 40) scores on the Mood Disorder Questionnaire, MDQ, suspected of high risk for bipolar disorder and those with low-risk scores (n = 37).
View Article and Find Full Text PDFNucleic Acids Res
January 2025
Department of Pharmaceutical Sciences, University of California, Irvine, CA 92697-3958, United States.
Growth in the development of engineered polymerases for synthetic biology has led to renewed interest in assays that can measure the fidelity of polymerases that are capable of synthesizing artificial genetic polymers (XNAs). Conventional approaches require purifying the XNA intermediate of a replication cycle (DNA → XNA → DNA) by denaturing polyacrylamide gel electrophoresis, which is a slow, costly, and inefficient process that requires a large-scale transcription reaction and careful extraction of the XNA strand from the gel slice. In an effort to streamline the assay, we developed a purification-free approach in which the XNA transcription and reverse transcription steps occur inside the matrix of a hydrogel-coated magnetic particle.
View Article and Find Full Text PDFInorg Chem
January 2025
School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, Singapore 63798, Singapore.
The corrugated <110> oriented layered metal halide perovskites (MHP) are gaining increased attention for a variety of properties including intrinsic white light emission. One prototypical candidate is 1-(3-aminopropyl)imidazole lead bromide, which was reported to crystallize as the <110> oriented perovskite (API)PbBr [API = 1-(3-aminopropyl)imidazole]. This work shows that under similar reaction conditions, the same components can instead form (API)PbBr, which has a "perovskitoid" structure.
View Article and Find Full Text PDFWe analyze the single-photon band structure and the transport of a single photon in a one-dimensional coupled-spinning-resonator chain. The time-reversal symmetry of the resonators chain is broken by the spinning of the resonators, instead of external or synthetic magnetic field. Two nonreciprocal single-photon band gaps can be obtained in the coupled-spinning-resonator chain, whose width depends on the angular velocity of the spinning resonator.
View Article and Find Full Text PDFDesigning invisibility devices for required frequency bands is important in anti-detection methods in various fields such as communications, construction, and others. However, traditional design methods are time-consuming, with manual adjustment of parameters and continuous trial and error. Fortunately, the data-driven approach based on deep learning has revolutionized the field.
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