Dokument-ID Dokumenttyp Autoren/innen Persönliche Herausgeber/innen Haupttitel Abstract Auflage Verlagsort Verlag Herausgeber (Institution) Erscheinungsjahr Titel des übergeordneten Werkes Jahrgang/Band ISBN Veranstaltung Veranstaltungsort Beginndatum der Veranstaltung Enddatum der Veranstaltung Ausgabe/Heft Erste Seite Letzte Seite URN DOI Lizenz Datum der Freischaltung OPUS4-36135 Zeitschriftenartikel Zientek, Nicolai; Laurain, C.; Meyer, Klas; Paul, Andrea; Engel, D.; Guthausen, G.; Kraume, M.; Maiwald, Michael Automated data evaluation and modelling of simultaneous F-19-H-1 medium-resolution NMR spectra for online reaction monitoring Medium-resolution nuclear magnetic resonance spectroscopy (MR-NMR) currently develops to an important analytical tool for both quality control and processmonitoring. In contrast to high-resolution onlineNMR (HR-NMR),MR-NMRcan be operated under rough environmental conditions. A continuous re-circulating stream of reaction mixture fromthe reaction vessel to the NMR spectrometer enables a non-invasive, volume integrating online analysis of reactants and products. Here, we investigate the esterification of 2,2,2-trifluoroethanol with acetic acid to 2,2,2-trifluoroethyl acetate both by 1H HR-NMR (500MHz) and 1H and 19F MRNMR (43MHz) as amodel system. The parallel online measurement is realised by splitting the flow,which allows the adjustment of quantitative and independent flow rates, both in the HR-NMR probe as well as in the MR-NMR probe, in addition to a fast bypass line back to the reactor. One of the fundamental acceptance criteria for online MR-MNR spectroscopy is a robust data treatment and evaluation strategy with the potential for automation. The MR-NMR spectra are treated by an automated baseline and phase correction using the minimum entropy method. The evaluation strategies comprise (i) direct integration, (ii) automated line fitting, (iii) indirect hard modelling (IHM) and (iv) partial least squares regression (PLS-R). To assess the potential of these evaluation strategies for MR-NMR, prediction results are compared with the line fitting data derived from the quantitative HR-NMR spectroscopy. Although, superior results are obtained from both IHM and PLS-R for 1H MR-NMR, especially the latter demands for elaborate data pretreatment, whereas IHM models needed no previous alignment. Hoboken, New Jersey, USA John Wiley & Sons, Ltd 2016 Magnetic Resonance in Chemistry 54 513 520 doi:10.1002/mrc.4216 2016-05-23