The interpretation of small molecule diffusion coefficients: Quantitative use of diffusion-ordered NMR spectroscopy

Abstract

Measuring accurate molecular self-diffusion coefficients, D, by nuclear magnetic resonance (NMR) techniques has become routine as hardware, software and experimental methodologies have all improved. However, the quantitative interpretation of such data remains difficult, particularly for small molecules. This review article first provides a description of, and explanation for, the failure of the Stokes-Einstein equation to accurately predict small molecule diffusion coefficients, before moving on to three broadly complementary methods for their quantitative interpretation. Two are based on power laws, but differ in the nature of the reference molecules used. The third addresses the uncertainties in the Stokes-Einstein equation directly. For all three methods, a wide range of examples are used to show the range of chemistry to which diffusion NMR can be applied, and how best to implement the different methods to obtain quantitative information from the chemical systems studied.

Publication DOI: https://doi.org/10.1016/j.pnmrs.2019.11.002
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Chemical Engineering & Applied Chemistry
College of Engineering & Physical Sciences > Aston Institute of Materials Research (AIMR)
Additional Information: © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: DOSY,Diffusion NMR,Molecular weight,Stokes-Einstein equation,Analytical Chemistry,Biochemistry,Nuclear and High Energy Physics,Spectroscopy
Full Text Link:
Related URLs: https://linking ... 079656519300585 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Review article
Published Date: 2020-04-01
Published Online Date: 2019-11-26
Accepted Date: 2019-11-20
Authors: Evans, Robert (ORCID Profile 0000-0003-1471-201X)

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