Publication details

Theoretical and computational framework for the analysis of the relaxation properties of arbitrary spin systems. Application to high-resolution relaxometry

Authors

BOLIK-COULON N. KADEŘÁVEK Pavel PELUPESSY P. DUMEZ J.N. FERRAGE F. COUSIN S.F.

Year of publication 2020
Type Article in Periodical
Magazine / Source Journal of Magnetic Resonance
MU Faculty or unit

Central European Institute of Technology

Citation
Web https://www.sciencedirect.com/science/article/pii/S1090780720300367?via%3Dihub
Doi http://dx.doi.org/10.1016/j.jmr.2020.106718
Keywords Nuclear spin relaxation; Analytical relaxation computation; High-resolution relaxometry
Description A wide variety of nuclear magnetic resonance experiments rely on the prediction and analysis of relaxation processes. Recently, innovative approaches have been introduced where the sample travels through a broad range of magnetic fields in the course of the experiment, such as dissolution dynamic nuclear polarization or high-resolution relaxometry. Understanding the relaxation properties of nuclear spin systems over orders of magnitude of magnetic fields is essential to rationalize the results of these experiments. For example, during a high-resolution relaxometry experiment, the absence of control of nuclear spin relaxation pathways during the sample transfers and relaxation delays leads to systematic deviations of polarization decays from an ideal mono-exponential decay with the pure longitudinal relaxation rate. These deviations have to be taken into account to describe quantitatively the dynamics of the system. Here, we present computational tools to (1) calculate analytical expressions of relaxation rates for a broad variety of spin systems and (2) use these analytical expressions to correct the deviations arising in high-resolution relaxometry experiments. These tools lead to a better understanding of nuclear spin relaxation, which is required to improve the sensitivity of many pulse sequences, and to better characterize motions in macromolecules. (C) 2020 Published by Elsevier Inc.

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