School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QJ, UK.
Prog Nucl Magn Reson Spectrosc. 2020 Feb;116:1-18. doi: 10.1016/j.pnmrs.2019.09.001. Epub 2019 Sep 6.
The analysis of mixtures by NMR spectroscopy is challenging. Diffusion-ordered NMR spectroscopy enables a pseudo-separation of species based on differences in their translational diffusion coefficients. Under the right circumstances, this is a powerful technique; however, when molecules diffuse at similar rates separation in the diffusion dimension can be poor. In addition, spectral overlap also limits resolution and can make interpretation challenging. Matrix-assisted diffusion NMR seeks to improve resolution in the diffusion dimension by utilising the differential interaction of components in the mixture with an additive to the solvent. Tuning these matrix-analyte interactions allows the diffusion resolution to be optimised. This review presents the background to matrix-assisted diffusion experiments, surveys the wide range of matrices employed, including chromatographic stationary phases, surfactants and polymers, and demonstrates the current state of the art.
通过 NMR 光谱分析混合物具有挑战性。扩散排序 NMR 光谱法可基于其在平移扩散系数上的差异实现对物质的类分离。在适当的条件下,这是一种强大的技术;然而,当分子以相似的速率扩散时,在扩散维度上的分离效果可能不佳。此外,光谱重叠也会限制分辨率,并使解释变得具有挑战性。基质辅助扩散 NMR 通过利用混合物成分与溶剂添加剂之间的差异相互作用来提高扩散维度的分辨率。调整这些基质-分析物相互作用可以优化扩散分辨率。本综述介绍了基质辅助扩散实验的背景,调查了广泛使用的基质,包括色谱固定相、表面活性剂和聚合物,并展示了当前的技术水平。