TY - JOUR A1 - Zientek, Nicolai A1 - Meyer, Klas A1 - Kern, Simon A1 - Maiwald, Michael T1 - Quantitative online NMR spectroscopy in a nutshell N2 - Online NMR spectroscopy is an excellent tool to study complex reacting multicomponent mixtures and gain process insight and understanding. For online studies under process conditions, flow NMR probes can be used in a wide range of temperature and pressure. This paper compiles the most important aspects towards quantitative process NMR spectroscopy in complex multicomponent mixtures and provides examples. After NMR spectroscopy is introduced as an online method and for technical samples without sample preparation in deuterated solvents, influences of the residence time distribution, pre-magnetization, and cell design are discussed. NMR acquisition and processing parameters as well as data preparation methods are presented and the most practical data analysis strategies are introduced. KW - Prozessanalytik KW - Process analytical technology KW - Online NMR spectroscopy KW - Online monitoring PY - 2016 U6 - https://doi.org/10.1002/cite.201500120 SN - 0009-286X VL - 88 IS - 6 SP - 698 EP - 709 PB - Wiley-VCH Verlag GmbH & Co. KGaA CY - Weinheim, Germany AN - OPUS4-36333 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Meyer, Klas A1 - Kern, Simon A1 - Zientek, Nicolai A1 - Guthausen, G. A1 - Maiwald, Michael T1 - Process control with compact NMR N2 - Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction and process control. An increasing number of applications are reported. To build an interdisciplinary bridge between “process control” and “compact NMR”,we give a short overviewon current developments in the field of process Engineering such as modern process design, integrated processes, intensified processes along with requirements to process control, model based control, or soft sensing. Finally, robust field integration of NMR systems into processes environments, facing explosion protection or Integration into process control systems, are briefly discussed. KW - Prozessanalytik KW - Quantitative NMR-Spektroskopie KW - Industrie 4.0 KW - Reaction monitoring KW - Process control KW - Online NMR spectroscopy KW - Compact NMR PY - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-373562 UR - http://www.sciencedirect.com/science/article/pii/S0165993616300073 SN - 0165-9936 VL - 83 IS - Part A / SI SP - 39 EP - 52 PB - Elsevier AN - OPUS4-37356 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 -