TY - CONF A1 - Kern, Simon A1 - Meyer, Klas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Ugly Spectra and Lousy interfaces – Challenges for Compact NMR Spectroscopy in Process Control N2 - With the introduction of advanced process analytical technology, the closeness of key process variables to their limits can be directly controlled and the product can be classified or even released in real time. Compact NMR instruments can make NMR spectroscopy accessible in industrial and harsh environments for process control. T2 - ProcessNet-Jahrestagung und 32. DECHEMA-Jahrestagung der Biotechnologen 2016 CY - Aachen, Germany DA - 12.09.2016 KW - Online NMR Spectroscopy KW - Smart Sensors KW - Industrie 4.0 KW - Reaction Monitoring PY - 2016 UR - http://onlinelibrary.wiley.com/doi/10.1002/cite.201650243/full U6 - https://doi.org/10.1002/cite.201650243 SN - 1522-2640 VL - 88 SP - 1304 EP - 1317 PB - Wiley-VCH Verlag GmbH & Co. KGaA CY - Weinheim AN - OPUS4-37317 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kern, Simon A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gräßer, Patrick A1 - Paul, Andrea A1 - King, R. A1 - Maiwald, Michael T1 - Online low-field NMR spectroscopy for process control of an industrial lithiation reaction—automated data analysis N2 - Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential for closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies. We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (Indirect Hard Modelling – IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union’s Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analysed by IHM with low calibration effort, compared to a multivariate PLS-R (Partial Least Squares Regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy. KW - Online NMR spectroscopy KW - Process analytical technology KW - Partial Least Squares Regression KW - Indirect Hard Modeling KW - Benchtop NMR Spectroscopy KW - Smart Sensors KW - CONSENS PY - 2018 UR - https://link.springer.com/article/10.1007/s00216-018-1020-z U6 - https://doi.org/10.1007/s00216-018-1020-z SN - 1618-2642 SN - 1618-2650 VL - 410 IS - 14 SP - 3349 EP - 3360 PB - Springer CY - Berlin, Heidelberg AN - OPUS4-44847 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -