TY - CONF A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Kern, Simon A1 - Gräßer, Patrick A1 - Maiwald, Michael ED - Maiwald, Michael T1 - Process monitoring of an intensified continuous production unit with compact NMR spectroscopy N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analyzers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are cur-rently not available off the rack. Recently, promising benchtop NMR instruments with acceptable performance came to market and process integrated sensors developed on basis of such laboratory instruments are on their way. T2 - 12. Kolloquium des Arbeitskreises Prozessanalytik CY - Berlin, Germany DA - 28.11.2016 KW - Online NMR spectroscopy KW - Modular production units KW - Low field NMR spectroscopy PY - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-383646 SP - P17, 75 EP - 77 AN - OPUS4-38364 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Meyer, Klas A1 - Gräßer, Patrick A1 - Guhl, Svetlana 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 - Industrie 4.0 KW - Online NMR spectroscopy KW - Reaction monitoring KW - Smart sensors PY - 2016 AN - OPUS4-37405 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Meyer, Klas A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Online low-field NMR spectroscopy in modular plants for chemical production N2 - Die Online-Reaktionsverfolgung ist der Schlüssel zur chemischen Prozesskontrolle. Heute werden in diesem Bereich hauptsächlich Methoden der optischen Spektroskopie eingesetzt. Durch aktuelle Entwicklungen im Bereich kompakter Niederfeld-NMR-Spektrometer auf Basis von Permanentmagnetsystemen ist erstmals auch die Integration unmittelbar in einer industriellen Produktionsumgebung möglich. Diese Geräte sind robuste und relativ preiswerte Analysatoren, welche die Vorteile eines wartungsfreundlichen Betriebs ohne Notwendigkeit von kryogenen Flüssigkeiten, sowie eine einfache Handhabung vereinen. Aktuell auf dem Markt verfügbare Geräte sind jedoch ausschließlich auf den Einsatz im Laborbetrieb ausgerichtet. Für die Kopplung als Online-Methode im Prozesseinsatz ist die Entwicklung geeigneter Durchflusszellen notwendig. Diese ermöglichen idealerweise ein gutes Signal-Rausch-Verhältnis, eine ausreichende Robustheit und müssen die Anforderungen an die Integration in industrielle Anlagen erfüllen (z.B. Explosionsschutz, Temperierung). Intensivierte kontinuierliche Prozesse stehen im Fokus der aktuellen Forschung. Im Vergleich zu etablierten Batch-Verfahren besteht in modularen chemischen Anlagen die Möglichkeit durch kurze Umrüstzeiten zwischen Kampagnen effektiv auf die Marktentwicklung zu reagieren. Bei kontinuierlicher Prozessführung sind Online-Sensoren und eine zuverlässige und schnelle Regelung der Produktqualität essentiell. Andernfalls besteht ein großes Risiko, große Mengen nicht-spezifikationskonformer Produkte zu erhalten. Dies wird im Rahmen des Forschungsprojekts CONSENS (Integrated Control and Sensing) der Europäischen Union durch die Entwicklung und Integration intelligenter Sensormodule zur Prozessüberwachung und -steuerung in modularen Anlagenkonzepten thematisiert. Das vorgestellte NMR-Analysatormodul mit der Baugröße von 57 x 57 x 85 cm basiert auf einem kompakten 43,5-MHz-NMR-Spektrometer. Dieses ist zusammen mit einem Akquisitionsrechner und einer programmierbaren Steuerung für die automatisierte Daten-aufbereitung (Phasing, Baseline-Korrektur) und Auswertung in ein explosionsgeschütztes Gehäuse integriert. Für die automatisierte Datenanalyse kommt die Methode des Indirect Hard Modelings (IHM) zum Einsatz. Die entwickelten IHM-Modelle werden mittels Online-Hochfeld-NMR-Spektroskopie als Referenzverfahren in einem Versuchsaufbau zur Überwachung kontinuierlicher Reaktionen auf Basis eines mit Spritzenpumpen betriebenen 1/8" Rohrreaktors validiert. N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and relatively inexpensive analysers, which feature advantages like low cost, low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, sufficient robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack. Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. If these are not available, there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS (Integrated Control and Sensing [3]) by development and integration of smart sensor modules for process monitoring and control within such modular plant setups. The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method. T2 - Praktische Probleme der Kernresonanzspektroskopie CY - Erlangen, Germany DA - 16.01.2017 KW - Online NMR spectroscopy KW - Automated data evaluation KW - NMR sensor KW - Process control PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-389819 AN - OPUS4-38981 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Low field NMR spectroscopy for sustainable and flexible production of high quality chemical products N2 - The main development goal of process industries is to advance the continuous production of high-value products that meet high quality demands in flexible intensified continuous plants by introducing novel online sensing equipment and closed-loop control (CONSENS – integrated control and sensing- is funded from the European Union’s Horizon 2020 research and innovation programme). Therefore, we present the field integration of a benchtop NMR instrument into a modular production environment, focussing on suitable equipment for operation in hazardous areas with risk of explosive atmospheres. We investigated a pharmaceutical reaction step in order to describe challenges for the experimental design, the evaluation of complex NMR spectra and demonstrate automated data analysis tools. T2 - 5th Panic - Practical Applications of NMR in Industry Conferece CY - Hilton Head Island, SC 29928, USA DA - 20.02.2017 KW - Online NMR spectroscopy KW - Automated data evaluation KW - Process control PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-392333 AN - OPUS4-39233 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Kern, Simon A1 - Gräßer, Patrick A1 - Maiwald, Michael T1 - Process monitoring of an intensified continuous production unit with compact NMR spectroscopy N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and inexpensive analysers, which feature advantages like low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack. Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. Otherwise there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS by development and integration of smart sensor modules for process monitoring and control within such modular plant setups. The presented NMR module is provided in an explosion proof housing with a module size of 57 x 57 x 85 cm and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method. T2 - Workshop for Process Industry - Tackling the Future of Plant Operation CY - Frankfurt am Main, Germany DA - 25.01.2017 KW - Online NMR spectroscopy KW - Process analytical technology KW - Prozessanalytik KW - Process control KW - CONSENS PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-391386 AN - OPUS4-39138 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Michalik-Onichimowska, Aleksandra A1 - Riedel, Jens A1 - Panne, Ulrich A1 - King, R. A1 - Maiwald, Michael T1 - Fitting of physically motivated spectral models – a simple calibration-free method for evaluation of online NMR spectra N2 - Currently, research in chemical manufacturing moves towards flexible plug-and-play approaches focusing on modular plants, capable of producing small scales on-demand with short down-times between individual campaigns. This approach allows for efficient use of hardware, a faster optimization of the process conditions, and thus, an accelerated introduction of new products to the market. Driven mostly by the search for chemical syntheses under biocompatible conditions, so-called “click” chemistry rapidly became a growing field of research. The resulting simple one-pot reactions are so far only scarcely accompanied by an adequate optimization via comparably straightforward and robust analysis techniques. Here we report on a fast and reliable calibration-free online high field NMR monitoring approach for technical mixtures. It combines a versatile fluidic system, continuous-flow measurement with a time interval of 20 s per spectrum, and a robust, automated algorithm to interpret the obtained data. All spectra were acquired using a 500 MHz NMR spectrometer (Varian) with a dual band flow probe having a 1/16-inch polymer tubing working as a flow cell. Single scan 1H NMR spectra were recorded with an acquisition time of 5 s, relaxation delay of 15 s. As a proof-of-concept, the thiol-ene coupling between N-boc cysteine methyl ester and allyl alcohol was conducted in non-deuterated solvents while its time-resolved behaviour was characterised with step tracer experiments. Through the application of spectral modeling the signal area for each reactant can be deconvoluted in the online spectra and thus converted to the respective concentrations or molar ratios. The signals which were suitable for direct integration were used herein for comparison purposes of both methods. T2 - Quantitative NMR Methods for Reaction and Process Monitoring (NMRPM) CY - Kaiserslautern, Germany DA - 19.01.2017 KW - Online NMR spectroscopy KW - Thiol-ene coupling KW - Data processig PY - 2017 AN - OPUS4-39009 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Wander, Lukas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Mathematical and statistical tools for online NMR spectroscopy in chemical processes N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process Monitoring and control, as demonstrated within the European Union’s Horizon 2020 project CONSENS. We present a range of approaches for the automated spectra analysis moving from conventional multivariate statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants or derivatives and robust automation schemes. T2 - 13. Dresdner Sensor Symposium CY - Dresden, Germany DA - 04.12.2017 KW - Online NMR spectroscopy KW - Process control KW - Partial least squares regression KW - Indirect hard modeling KW - Quantum mechanics KW - First principles PY - 2017 UR - https://www.ama-science.org/proceedings/details/2748 SN - 978-3-9816876-5-1 U6 - https://doi.org/10.5162/13dss2017/P2.07 SP - P2, 209 EP - 212 PB - AMA Service GmbH CY - Berlin AN - OPUS4-43254 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Meyer, Klas A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Process monitoring of intensified continuous production units with compact NMR spectroscopy N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and inexpensive analysers, which feature advantages like low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack. Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. Otherwise there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS (www.consens-spire.eu) by development and integration of smart sensor modules for process monitoring and control within such modular plant setups. The presented NMR module is provided in an explosion proof housing with a module size of 57 x 57 x 85 cm and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method. T2 - Seminar, Institute of Technical Biocatalysis, Hamburg University of Technology CY - Hamburg, Germany DA - 13.01.2017 KW - Process monitoring KW - Online NMR spectroscopy KW - Indirect hard modeling KW - Process control KW - Process analytical technology KW - CONSENS PY - 2017 AN - OPUS4-43551 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Reading between the lines – Automated data analysis for low field NMR spectra N2 - For reaction monitoring and process control using NMR instruments, in particular, after acquisition of the FID the data needs to be corrected in real-time for common effects using fast interfaces and automated methods. When it comes to NMR data evaluation under industrial process conditions, the shape of signals can change drastically due to nonlinear effects. Additionally, the multiplet structure becomes more dominant because of the comparably low-field strengths which results in overlapping of multiple signals. However, the structural and quantitative information is still present but needs to be extracted by applying predictive models. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modeling). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants, or derivatives and robust automation schemes. T2 - Small Molecule NMR Conference (SMASH) CY - Baveno, Italy DA - 17.09.2017 KW - Online NMR spectroscopy KW - Data analysis KW - Chemometrics KW - Indirect hard modeling KW - Spectral modeling KW - Line prediction KW - CONSENS KW - SMASH PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-419498 UR - http://www.smashnmr.org/conference/program AN - OPUS4-41949 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Wander, Lukas A1 - Meyer, Klas A1 - Maiwald, Michael T1 - Simple calibration concept of an online NMR module demonstrated in a modularised production plant N2 - Monitoring specific information (such as physico-chemical properties, chemical re-actions, etc.) is the key to chemical process control. Within the CONSENS Project, the challenge to adapt a commercially available benchtop NMR spectrometer to the full requirements of an automated chemical production environment was tack-led. The developed online NMR module was provided in an explosion proof housing and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit, a programmable logic controller for automated triggering, flow con-trol, as well as data communication. First results of an aromatic coupling reaction in lab scale showed a general feasibil-ity according to the signal information in the acquired NMR spectra even though with a considerable overlap. Due to the comparatively low field strength of the NMR spectrometer multivariate methods had to be considered for the prediction of con-centration profiles based on spectral data. Typically, for industrial application of those methods, e.g. Partial Least Squares Regression (PLS-R) as well as Indirect Hard Modeling, large amount of calibration data is demanded, which must be ac-quired in time consuming lab-scale experiments and offline analytics. When it comes to changes in raw materials (e.g., varying functional groups, additional stabi-lizing agents) calibration experiments and data evaluation models are developed again. Here we present an approach of automated data analysis tools for low field NMR spectra with minimal calibration effort. The algorithms are based on Indirect Hard Modeling, whereby each component in each mixture spectra can be rep-resented by several flexible peak functions (pure component models). This means, that only pure component NMR spectra are needed to generate a first evaluation model. The flexibility of peak functions in the spectral model can be adjusted via constraints of peak parameters. The area of any pure component model can either be converted to concentrations based on a one-point calibration on raw material concentration or even neat solvent signals. In several cases it has been shown, the IHM works almost independently of the matrix of the real samples. Such a calibration can be repeated daily in the beginning of each process run with minimal time effort. Moreover, additional pure components can be added to the model or even substitut-ed while keeping the previously adjusted peak function constraints. The proposed method exhibited good agreement of resulting concentration data from low field NMR spectra, when compared to an online high field NMR spectrometer as refer-ence instrument. T2 - 13. Kolloquium des Arbeitskreises Prozessanalytik der DECHEMA und der GDCh-Fachgruppe Analytische Chemie CY - Esslingen, Germany DA - 20.11.2017 KW - Online monitoring KW - Online NMR spectroscopy KW - Modularised production PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-430999 AN - OPUS4-43099 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Mathematical and statistical tools for online NMR spectroscopy in chemical processes N2 - Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which are calibration intensive. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process monitoring and control. Within the European Union’s Research Project CONSENS (Integrated CONtrol and SENsing, www.consens-spire.eu) by development and integration of a smart NMR module for process monitoring was designed and delivers online spectra of various reactions. The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation. For reaction monitoring and process control using NMR instruments after acquisition of the FID the data needs to be corrected in real-time for common effects using fast interfaces and automated methods. When it comes to NMR data evaluation under industrial process conditions, the shape of signals can change drastically due to nonlinear effects. Additionally, the multiplet structure becomes more dominant because of the comparably low-field strengths which results in overlapping of multiple signals. However, the structural and quantitative information is still present but needs to be extracted by applying predictive models. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants, or derivatives and robust automation schemes. T2 - 13. Dresdner Sensor Symposium CY - Dresden, Germany DA - 04.12.2017 KW - Process Monitoring KW - Process sensors KW - Process analytical technology KW - Online NMR spectroscopy KW - Direct loop control KW - Numerical methods KW - Spectral modeling KW - Indirect hard modeling KW - CONSENS PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-432085 AN - OPUS4-43208 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Wander, Lukas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Already Analyzing or Still Calibrating? - Demonstration of an online NMR analyzer in pilot scale N2 - The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example. Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). Based on concentration measurements of reagents and products by the NMR analyzer a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu). T2 - analytica conference 2018 CY - München, Germany DA - 10.04.2018 KW - Online NMR spectroscopy PY - 2018 AN - OPUS4-44680 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kern, Simon A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Müller, S. A1 - Maiwald, Michael A1 - Kowarik, Stefan T1 - Training data of quantitative online NMR spectroscopy for artificial neural networks N2 - Data set of low-field NMR spectra of continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). 1H spectra (43 MHz) were recorded as single scans. Two different approaches for the generation of artificial neural networks training data for the prediction of reactant concentrations were used: (i) Training data based on combinations of measured pure component spectra and (ii) Training data based on a spectral model. Synthetic low-field NMR spectra First 4 columns in MAT-files represent component areas of each reactant within the synthetic mixture spectrum. Xi (“pure component spectra dataset”) Xii (“spectral model dataset”) Experimental low-field NMR spectra from MNDPA-Synthesis This data set represents low-field NMR-spectra recorded during continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). Reference values from high-field NMR results are included. KW - NMR spectroscopy KW - Real-time process monitoring KW - Artificial neural networks KW - Online NMR spectroscopy KW - Automation KW - Process industry PY - 2020 U6 - https://doi.org/10.5281/zenodo.3677139 PB - Zenodo CY - Geneva AN - OPUS4-50456 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -