Magnetic resonance T-T* relaxation correlation is a newly emerging and powerful tool to study the structure and dynamics of materials. However, the T-T* of solid-like materials may consist of a linear combination of exponential decays and non-exponential decays, and the traditional methods for processing T-T data would be not applicable. In this paper, a method of processing T-T* data with non-exponential decays was proposed. The critical idea is to decompose the data into two sub-datasets, exponential decays and non-exponential decays, employing a non-linear fitting method, and then to invert the sub-datasets and to combine the inversion results. We also introduce a related relaxation correlation measurement, T-T*, for examination of solid-like materials. The same data processing strategy as for T-T* was implemented. The effectiveness of the proposed method for processing non-exponential data, Sinc Gaussian and Gaussian decay, was validated with simulation and experiment. The results showed that the proposed method recovers T-T* and T-T* spectra with accurate relative signal intensities. The proposed method provides a platform for further development of MR methods applied to solid-like materials. These relaxation correlations are well suited to measuring composition of mixtures, with solid components in the mixture.
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http://dx.doi.org/10.1016/j.jmr.2021.107005 | DOI Listing |
Macromol Biosci
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Department of Chemistry, University of Victoria, Victoria, BC, V8W 2Y2, Canada.
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Dept. of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 7610001, Israel.
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Vertebrate oocyte polarity has been observed for two centuries and is essential for embryonic axis formation and germline specification, yet its underlying mechanisms remain unknown. In oocyte polarization, critical RNA-protein (RNP) granules delivered to the oocyte's vegetal pole are stored by the Balbiani body (Bb), a membraneless organelle conserved across species from insects to humans. However, the mechanisms of Bb formation are still unclear.
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Understanding the dynamic response of granular shear zones under cyclic loading is fundamental to elucidating the mechanisms triggering earthquake-induced landslides, with implications for broader fields such as seismology and granular physics. Existing prediction methods struggle to accurately predict many experimental and in situ landslide observations due to inadequate consideration of the underlying physical mechanisms. The mechanisms that influence landslide dynamic triggering, a transition from static (or extremely slow creeping) to rapid runout, remain elusive.
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