This article shows the concept of PGSE NMR for mixture analysis, which is still crucial in NMR. The separation of sucrose and glucose is examplified. As NMR is no good separation technique - structure elucidation from multicomponent mixtures is still a problem for NMR (whereas a fast structure elucidation from single components is only possible with NMR!). Stronger magnets, new probes and new data evaluation methods may help to solve the multicomponent problem of NMR.

With the help of a combination of entropy minimization and spectral dissimilarity calulations together, a better resolving of pure component spectra from multicomponent mixtures may be obtained. Examples for ¹H PGSE-NMR mixture spectra show that the suggested entropy minimization approache gives slightly better results compared to direct exponential curve resolution (DECRA) and positive matrix factorization (PMF) See also dx.doi.org/10.1002/jcc.10080

Multi-dimensional NMR experiments like HMQC (Heteronuclear Multiple Quantum Correlation) and HSQC (Heteronuclear Single Quantum Correlation) require a longer sampling time (minute range) if only small amounts (µg..mg range) of the compound under investigation are available. Reducing the spectral widths and number of increments may speed up the data aquisition time by a factor of three. Examples for sucrose and a substituted ethyl alpha-cyanocinnamate are given.