Diffusion Coefficients from NMR Experiments
Diffusion is a ubiquitous phenomenon. The mixing of heterogeneous media is a common everyday example of mass transport by diffusion processes. But even media that have already been mixed exhibit an internal mobility, self-diffusion. Diffusion coefficients allow quantification of transport and self-diffusion, their measurement by classical methods is often challenging. Here, the NMR method provides exceptionally well-suited approaches for the precise determination of self and transport diffusion coefficients.
Diffusion Coefficients of Poly(oxymethylene) dimethyl ether and Hydrogenated Vegetable Oils
Poly(oxymethylene) dimethyl ether (OME) and hydrogenated vegetable oils (HVO) are interesting synthetic fuels that can be produced from renewable resources. It is well known from combustion research that droplets moving through a hot gas can disintegrate explosively. This phenomenon occurs when diffusion is slower than heat transfer and overheating occurs inside the droplet. To test this hypothesis, information on the diffusion coefficients of OME is lacking in the literature. We measure self-diffusion coefficients in the mixtures at high dilution so that the results are identical to the corresponding transport diffusion coefficients. This allows us to test the hypothesis.
Measurement and Prediction of Self-Diffusion Coefficients Based on Active Learning Strategies
Information on diffusion coefficients in mixtures is essential in process engineering, e.g. for modeling transport phenomena and simulating thermal separation processes. However, since there is no measured data for many practically relevant components and their mixtures, prediction methods are crucial - including matrix completion methods (MCMs) from machine learning. To improve the prediction quality of MCMs, new data points are selected in an iterative procedure based on Active Learning strategies and measured with PFG NMR spectroscopy.
