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Recently, we presented a new approach for simultaneous phase and baseline correction of nuclear magnetic resonance (NMR) signals (SINC) that is based on multiobjective optimization. The algorithm can automatically correct large sets of NMR spectra, which are commonly acquired when reactions and processes are monitored with NMR spectroscopy. The aim of the algorithm is to provide spectra that can be evaluated quantitatively, for example, to calculate the composition of a mixture or the extent of reaction. In this work, the SINC algorithm is tested in three different studies. In an in‐house comparison study, spectra of different mixtures were corrected both with the SINC method and manually by different experienced users. The study shows that the results of the different users vary significantly and that their average uncertainty of the composition measurement is larger than the uncertainty obtained when the spectra are corrected with the SINC method. By means of a dilution study, we demonstrate that the SINC method is also applicable for the correction of spectra with low signal‐to‐noise ratio. Furthermore, a large set of NMR spectra that was acquired to follow a reaction was corrected with the SINC method. Even in this system, where the areas of the peaks and their chemical shifts changed during the course of reaction, the SINC method corrected the spectra robustly. The results show that this method is especially suited to correct large sets of NMR spectra and it is thus an important contribution for the automation of the evaluation of NMR spectra.
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