In-plane magnetic anisotropy and the corresponding morphology of Fe epitaxial layers have been investigated with respect to underlying MgO growth temperature when epitaxial Fe/MgO layers are grown on InAs (001) substrates. Coexistence of three-dimensional Fe islands with strong in-plane textures along <110> and (100) is observed on 4 nm thick MgO layers grown on 200 degrees C, leading to the absence of magnetic anisotropy. Meanwhile, the partially relaxed MgO layers grown above 300 degrees C give rise to two-dimensional Fe layers with cubic magnetic anisotropy. The higher MgO growth temperature accelerates the two-dimensional layer formation of the subsequent Fe as well as the advent of cubic anisotropy by reducing underlying strain within the MgO layer.
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http://dx.doi.org/10.1166/jnn.2012.4673 | DOI Listing |
Adv Sci (Weinh)
January 2025
Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai, Maharashtra, 400076, India.
Stabilizing large easy-axis type magnetic anisotropy in molecular complexes is a challenging task, yet it is crucial for the development of information storage devices and applications in molecular spintronics. Achieving this requires a deep understanding of electronic structure and the relationships between structure and properties to develop magneto-structural correlations that are currently unexplored in the literature. Herein, a series of five-coordinate distorted square pyramidal Co complexes [Co(L)(X)].
View Article and Find Full Text PDFACS Nano
January 2025
Department of Physics and Astronomy, University of Manitoba, Winnipeg R3T 2N2, Canada.
Theory and simulations are used to demonstrate implementation of a variational Bayes algorithm called "active inference" in interacting arrays of nanomagnetic elements. The algorithm requires stochastic elements, and a simplified model based on a magnetic artificial spin ice geometry is used to illustrate how nanomagnets can generate the required random dynamics. Examples of tracking and PID control are demonstrated and shown to be consistent with the original stochastic differential equation formulation of active inference.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Department of Physics, University of Ulsan, Ulsan, 44610, Republic of Korea.
The anisotropic properties of materials profoundly influence their electronic, magnetic, optical, and mechanical behaviors and are critical for a wide range of applications. In this study, the anisotropic characteristics of Ni-based van der Waals materials, specifically NiTe and its alloy NiTeSe, utilizing a combination of comprehensive scanning tunneling microscopy (STM), angle-resolved photoemission spectroscopy (ARPES), and density functional theory (DFT) calculations, are explored. Unlike 1T-NiTe, which exhibits trigonal in-plane symmetry, the substitution of Te with Se in NiTe (resulting in the NiTeSe alloy) induces a pronounced in-plane anisotropy.
View Article and Find Full Text PDFEur Spine J
January 2025
Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China.
Background: Intervertebral disc (IVD) degeneration is the main cause of neck pain. Although conventional magnetic resonance imaging can detect morphological changes in intervertebral disc degeneration, it cannot provide accurate and objective evaluations. Magnetic resonance diffusion tensor imaging (DTI) reflects the microstructural changes in tissues by describing the diffusion of water molecules.
View Article and Find Full Text PDFBrain Imaging Behav
January 2025
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Physical exercise is a promising intervention to improve brain white matter integrity. In the PAM study, exercise intervention effects on white matter integrity were investigated in breast cancer patients. Chemotherapy-treated breast cancer patients with cognitive problems were randomized 2-4 years post-diagnosis to an exercise (n = 91) or control group (n = 90).
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