We present results concerning the fabrication of a new magnetorheological fluid with FeCo magnetic nanoparticles (NPs) as magnetic fillers. These NPs have been fabricated by using the chemical reduction technique and show a pure crystalline phase with size ranging among 30-50 nm and high magnetization, 212 ± 2 A m kg. They agglomerate due to the strong magnetic dipolar interaction among them. These FeCo nanoparticles were used to synthesize a magnetorheological fluid by using oleic acid as surfactant, mineral oil as carrier liquid and Aerosil 300 as additive to control the viscosity of the fluid. The synthesized fluid showed a strong magnetorheological response with increasing shear stress values as the magnetic field intensity increases. Thus, we have measured a superior performance up to 616.7 kA m, with a yield stress value of 2729 Pa, and good reversibility after demagnetization process. This value competes with the best ones reported in the most recent literature. We have compared the obtained results with our previous reported ones by using high magnetization Fe NPs fabricated by the electrical explosion of wire method (Fe-EEW).
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Phys Rev Lett
December 2024
Institute of Molecular Science, University of Valencia, Catedratico Jose Beltrán 2, 46980 Paterna, Spain.
The role of self-intercalation in 2D van der Waals materials is key to the understanding of many of their properties. Here we show that the magnetic ordering temperature of thin films of the 2D ferromagnet Fe_{5}GeTe_{2} is substantially increased by self-intercalated Fe that resides in the van der Waals gaps. The epitaxial films were prepared by molecular beam epitaxy and their magnetic properties explored by element-specific x-ray magnetic circular dichroism that showed ferromagnetic ordering up to 375 K.
View Article and Find Full Text PDFPLoS One
January 2025
NCCA, Bournemouth University, Poole, United Kingdom.
Medical volume data are rapidly increasing, growing from gigabytes to petabytes, which presents significant challenges in organisation, storage, transmission, manipulation, and rendering. To address the challenges, we propose an end-to-end architecture for data compression, leveraging advanced deep learning technologies. This architecture consists of three key modules: downsampling, implicit neural representation (INR), and super-resolution (SR).
View Article and Find Full Text PDFNeurosurg Rev
January 2025
Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
Glioma is characterized by high heterogeneity and poor prognosis. Attempts have been made to understand its diversity in both genetic expressions and radiomic characteristics, while few integrated the two omics in predicting survival of glioma. This study was intended to investigate the connection between glioma imaging and genome, and examine its predictive value in glioma mortality risk and tumor immune microenvironment (TIME).
View Article and Find Full Text PDFAlzheimers Dement
December 2024
The Second Affiliated Hospital of Chongqing Medical University, Chongqing, Chong Qing, China.
Background: Alzheimer's disease (AD) frequently coexists with cerebral small vessel disease (CSVD) is common in the aging population, yet the underlying mechanisms are not yet fully understood. Both long-term blood pressure variability (BPV) and plasma neurofilament light (PNFL) were identified as potential biomarkers for AD and CSVD. This study aims to understand the mechanisms of comorbidity between AD and CSVD by investigating the associations among BPV, PNFL, and comorbidity.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Korea University, Sejong, Sejong, Korea, Republic of (South).
Background: Amyloid-β accumulation is a pivotal factor in Alzheimer's disease (AD) progression. As treatment for AD has not been successful yet, the most effective approach lies in early diagnosis and the subsequent delay of disease progression. Hence, this study introduces a deep learning model to predict amyloid-β accumulation in the brain.
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