Accurate measurements of self-diffusion coefficients with benchtop NMR using a QM model-based approach

  • The measurement of self-diffusion coefficients using pulsed-field gradient (PFG) nuclear magnetic resonance (NMR) spectroscopy is a well-established method. Recently, benchtop NMR spectrometers with gradient coils have also been used, which greatly simplify these measurements. However, a disadvantage of benchtop NMR spectrometers is the lower resolution of the acquired NMR signals compared to high-field NMR spectrometers, which requires sophisticated analysis methods. In this work, we use a recently developed quantum mechanical (QM) model-based approach for the estimation of self-diffusion coefficients from complex benchtop NMR data. With the knowledge of the species present in the mixture, signatures for each species are created and adjusted to the measured NMR signal. With this model-based approach, the self-diffusion coefficients of all species in the mixtures were estimated with a discrepancy of less than 2 % compared to self-diffusion coefficients estimated from high-field NMR data sets of the same mixtures. These results suggest benchtop NMR is a reliable tool for quantitative analysis of self-diffusion coefficients, even in complex mixtures.

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Metadaten
Author:Ellen SteimersORCiD, Yevgen Matviychuk, Daniel J. HollandORCiD, Hans Hasse, Erik von Harbou
URN:urn:nbn:de:hbz:386-kluedo-80592
DOI:https://doi.org/10.1002/mrc.5300
ISSN:1097-458X
Parent Title (English):Magnetic Resonance in Chemistry
Publisher:Wiley
Document Type:Article
Language of publication:English
Date of Publication (online):2024/04/17
Year of first Publication:2022
Publishing Institution:Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau
Date of the Publication (Server):2024/04/17
Issue:60/12
Page Number:18
First Page:1113
Last Page:1130
Source:https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/mrc.5300
Faculties / Organisational entities:Kaiserslautern - Fachbereich Maschinenbau und Verfahrenstechnik
DDC-Cassification:6 Technik, Medizin, angewandte Wissenschaften / 620 Ingenieurwissenschaften und Maschinenbau
Collections:Open-Access-Publikationsfonds
Licence (German):Zweitveröffentlichung