Dipolar filtered magic-sandwich-echoes as a tool for probing molecular motions using time domain NMR.

Autor: Filgueiras JG; Instituto de Física de São Carlos, Universidade de São Paulo, P.O. Box 369, São Carlos, 13560-970 SP, Brazil. Electronic address: jfilgueiras@ifsc.usp.br., da Silva UB; Instituto de Física de São Carlos, Universidade de São Paulo, P.O. Box 369, São Carlos, 13560-970 SP, Brazil., Paro G; Instituto de Física de São Carlos, Universidade de São Paulo, P.O. Box 369, São Carlos, 13560-970 SP, Brazil., d'Eurydice MN; School of Chemical and Physical Sciences, Victoria University of Wellington, PO Box 600, Wellington, New Zealand., Cobo MF; Instituto de Física de São Carlos, Universidade de São Paulo, P.O. Box 369, São Carlos, 13560-970 SP, Brazil., deAzevedo ER; Instituto de Física de São Carlos, Universidade de São Paulo, P.O. Box 369, São Carlos, 13560-970 SP, Brazil. Electronic address: azevedo@ifsc.usp.br.
Jazyk: angličtina
Zdroj: Journal of magnetic resonance (San Diego, Calif. : 1997) [J Magn Reson] 2017 Dec; Vol. 285, pp. 47-54. Date of Electronic Publication: 2017 Oct 20.
DOI: 10.1016/j.jmr.2017.10.008
Abstrakt: We present a simple 1 H NMR approach for characterizing intermediate to fast regime molecular motions using 1 H time-domain NMR at low magnetic field. The method is based on a Goldmann Shen dipolar filter (DF) followed by a Mixed Magic Sandwich Echo (MSE). The dipolar filter suppresses the signals arising from molecular segments presenting sub kHz mobility, so only signals from mobile segments are detected. Thus, the temperature dependence of the signal intensities directly evidences the onset of molecular motions with rates higher than kHz. The DF-MSE signal intensity is described by an analytical function based on the Anderson Weiss theory, from where parameters related to the molecular motion (e.g. correlation times and activation energy) can be estimated when performing experiments as function of the temperature. Furthermore, we propose the use of the Tikhonov regularization for estimating the width of the distribution of correlation times.
(Copyright © 2017 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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