Signal amplification by reversible exchange (SABRE) is a promising hyperpolarization technique, which makes use of spin-order transfer from parahydrogen (the H molecule in its singlet spin state) to a to-be-polarized substrate in a transient organometallic complex, termed the SABRE complex. In this work, we present an experimental method for measuring the magnetic field dependence of the SABRE effect over an ultrawide field range, namely, from 10 nT to 10 T. This approach gives a way to determine the complete magnetic field dependence of SABRE-derived polarization. Here, we focus on SABRE polarization of spin-1/2 hetero-nuclei, such as C and N and measure their polarization in the entire accessible field range; experimental studies are supported by calculations of polarization. Features of the field dependence of polarization can be attributed to level anticrossings in the spin system of the SABRE complex. Features at magnetic fields of the order of 100 nT-1 μT correspond to "strong coupling" of protons and hetero-nuclei, whereas features found in the mT field range stem from "strong coupling" of the proton system. Our approach gives a way to measuring and analyzing the complete SABRE field dependence, to probing NMR parameters of SABRE complexes and to optimizing the polarization value.
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http://dx.doi.org/10.1002/mrc.4694 | DOI Listing |
PLoS One
January 2025
Nanjing University of Science and Technology, Jiangsu, China.
Student performance is crucial for addressing learning process problems and is also an important factor in measuring learning outcomes. The ability to improve educational systems using data knowledge has driven the development of the field of educational data mining research. Here, this paper proposes a machine learning method for the prediction of student performance based on online learning.
View Article and Find Full Text PDFChem Commun (Camb)
January 2025
Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB21EW, UK.
Metal-air batteries are promising energy storage systems with high specific energy density and low dependence on critical materials. However, their development is hindered by slow kinetics, low roundtrip efficiency, deficient capacity recovery, and limited lifetime. This work explores the effect of cycling protocols on the lifetime of Li-O cells, and the interplay between electrolyte composition and the upper cut-off voltage during charge.
View Article and Find Full Text PDFSoft Matter
January 2025
Department of Physics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India.
We study the kinetics of vapor-liquid and vapor-solid phase separation of a hydrodynamics preserving three-dimensional one-component Lennard Jones system in the presence of an external gravitational field using extensive molecular dynamic simulation. A bicontinuous domain structure is formed when the homogeneous system near the critical density is quenched inside the coexistence region. In the absence of gravity, the domain morphology is statistically self-similar and the length scale grows as per the existing laws.
View Article and Find Full Text PDFACS Nano
January 2025
Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States.
Spiking neural networks seek to emulate biological computation through interconnected artificial neuron and synapse devices. Spintronic neurons can leverage magnetization physics to mimic biological neuron functions, such as integration tied to magnetic domain wall (DW) propagation in a patterned nanotrack and firing tied to the resistance change of a magnetic tunnel junction (MTJ), captured in the domain wall-magnetic tunnel junction (DW-MTJ) device. Leaking, relaxation of a neuron when it is not under stimulation, is also predicted to be implemented based on DW drift as a DW relaxes to a low energy position, but it has not been well explored or demonstrated in device prototypes.
View Article and Find Full Text PDFCurr Drug Deliv
January 2025
School of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
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