DOI of the published article https://doi.org/10.1039/d3cp00509g
Rational Method for Defining and Quantifying Pseudo-components Based on NMR Spectroscopy
DOI:
https://doi.org/10.31224/3448Keywords:
Analysis, NMR Spectroscopy, Machine LearningAbstract
Poorly specified mixtures, whose composition is unknown, are ubiquitous in chemical and biochemical engineering. In the present work, we propose a rational method for defining and quantifying pseudo-components in such mixtures that is free of ad hoc assumptions. The new method requires only standard nuclear magnetic resonance (NMR) experiments and can be fully automated. In the first step, the method analyzes the composition of the poorly specified mixture in terms of structural groups, which is much easier than obtaining the component speciation. The structural groups are then clustered into pseudo-components based on information on the self-diffusion coefficients measured by pulsed-field gradient (PFG) NMR spectroscopy. We demonstrate the performance of the new method on several aqueous mixtures. The method is broadly applicable and provides a sound basis for modeling and simulation of processes with poorly specified mixtures, without the need for tedious and expensive structure elucidation. It is also attractive for process monitoring.
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Copyright (c) 2024 Thomas Specht, Kerstin Münnemann, Hans Hasse, Fabian Jirasek

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