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Spintronics use the electron spin as a state variable for information processing and storage. This requires manipulation of spin ensembles for data encoding, and spin transport for information transfer. Because of the central importance of lifetime for understanding and controlling spins, mechanisms that determine this lifetime in bulk systems have been extensively studied. However, a clear understanding of few-spin systems remains challenging. Here, we report spatially resolved magnetic resonance studies of electron spin ensembles confined to a 'spin nanowire' formed by nitrogen ion implantation in diamond. We measure the spin lifetime of the ensemble--that is, its spin autocorrelation time--by monitoring the statistical fluctuations of its net moment, which is in thermal equilibrium and has no imposed polarization gradient. We find that the lifetime of the ensemble is dominated by spin transport from the ensemble into the adjacent spin reservoir that is provided by the remainder of the nanowire. This is in striking contrast to conventional spin-lattice relaxation measurements of isolated spin ensembles. Electron spin resonance spectroscopy performed on nanoscale spin ensembles by means of a novel spin manipulation protocol corroborates spin transport in strong field gradients. Our experiments, supported by microscopic Monte Carlo modelling, provide a unique insight into the intrinsic dynamics of pure spin currents needed for nanoscale devices that seek to control spins.
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http://dx.doi.org/10.1038/nnano.2014.39 | DOI Listing |
J Comput Chem
January 2025
Department of Chemistry, Birla Institute of Technology Mesra, Ranchi, India.
Accurate prediction of physicochemical properties, such as electronic energy, enthalpy, free energy, and average vibrational frequencies, is critical for optimizing lithium-ion battery (LIB) performance. Traditional methods like density functional theory (DFT) are computationally expensive and inefficient for large-scale screening. In this study, we apply active learning on top of graph neural networks (GNNs) to efficiently predict these properties.
View Article and Find Full Text PDFFront Chem
December 2024
Department of Chemistry and Biochemistry, Auburn University, Auburn, AL, United States.
High-level quantum chemical calculations are performed for the (NH)MO and (NH)MO species (M = Ti-Cu), extending our previous work on the bare MO ions. The potential energy curves along the M-O distance are constructed for the ground and multiple excited electronic states of (NH)MO and are compared to those of MO. We see that ammonia stabilizes the oxo states (MO) over the oxyl (MO) ones.
View Article and Find Full Text PDFNano Lett
December 2024
Intel Corporation, Technology Research Group, Hillsboro, Oregon 97124, United States.
Intel's efforts to build a practical quantum computer are focused on developing a scalable spin-qubit platform leveraging industrial high-volume semiconductor manufacturing expertise and 300 mm fabrication infrastructure. Here, we provide an overview of the design, fabrication, and demonstration of a new customized quantum test chip, which contains 12-quantum-dot spin-qubit linear arrays, code named Tunnel Falls. These devices are fabricated using immersion and extreme ultraviolet lithography (EUV), along with other standard high-volume manufacturing (HVM) processes as well as production-level process control.
View Article and Find Full Text PDFJ Magn Reson
December 2024
Univ. Lille, CNRS, Centrale Lille, Univ. Artois, UMR 8181, UCCS - Unité de Catalyse et Chimie du Solide, F-59000 Lille, France. Electronic address:
The two-dimensional (2D) refocused INADEQUATE NMR experiment, which correlates double-quantum (DQ) and single-quantum (SQ) coherences, is widely used to probe the chemical connectivities in solids. Nevertheless, the multiplets along the F dimension reduce the resolution and sensitivity of this experiment. The Composite-Refocusing (CR) technique with two excitation pulses has been proposed to suppress these multiplets in 2D INADEQUATE spectra of liquids.
View Article and Find Full Text PDFEur J Radiol
December 2024
Division of Endocrinology and Metabolism, Department of Medicine III, Medical University of Vienna, Austria.
Objectives: To explore texture analysis' ability on T and T relaxation maps to classify liver fibrosis into no-to-mild liver fibrosis (nmF) versus severe fibrosis (sF) group using machine learning algorithms and histology as reference standard.
Materials And Methods: In this single-center study, patients undergoing 3 T MRI who also had histology examination were retrospectively enrolled. SNAPSHOT-FLASH sequence for T1 mapping, radial turbo-spin-echo sequence for T2 mapping and spin-echo echo-planar-imaging magnetic resonance elastography (MRE) sequences were analyzed.
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