Laboratory of Engineering Thermodynamics (LTD), Technische Universität Kaiserslautern, Erwin-Schrödinger-Straße 44, Kaiserslautern, 67663, Germany.
Department of Chemical and Process Engineering, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand.
Magn Reson Chem. 2022 Dec;60(12):1113-1130. doi: 10.1002/mrc.5300. Epub 2022 Aug 23.
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.
使用脉冲梯度（PFG）核磁共振（NMR）光谱法测量自扩散系数是一种成熟的方法。最近，带有梯度线圈的台式 NMR 光谱仪也已被使用，这极大地简化了这些测量。然而，台式 NMR 光谱仪的一个缺点是与高场 NMR 光谱仪相比，所获得的 NMR 信号的分辨率较低，这需要复杂的分析方法。在这项工作中，我们使用了最近开发的基于量子力学（QM）模型的方法，从复杂的台式 NMR 数据中估计自扩散系数。根据混合物中存在的物质的知识，为每个物质创建特征并将其调整到测量的 NMR 信号。使用这种基于模型的方法，与从相同混合物的高场 NMR 数据集估计的自扩散系数相比，混合物中所有物质的自扩散系数的估计差异小于 2％。这些结果表明，即使在复杂的混合物中，台式 NMR 也是定量分析自扩散系数的可靠工具。
