TY - GEN A1 - Blazek, M. A1 - Deilmann, M. A1 - Gasch, A. A1 - Gerlach, M. A1 - Grümbel, F. A1 - Kaiser, U. A1 - Kloska, M. A1 - Löbbecke, S. A1 - Maiwald, Michael A1 - Pötter, T. A1 - Rebner, K. A1 - Roos, E. A1 - Stieler, S. A1 - Stolz, D. A1 - Theuer, M. A1 - Berthold, J. A1 - Engelhard, H. T1 - Technologie-Roadmap "Prozesssensoren 4.0" N2 - Mit den Technologie-Roadmaps „Prozesssensoren 2005–2015“ [1] (2006) und „Prozesssensoren 2015+“ [2] und [3] (2009) wurden Grundlagen für alle Unternehmen der Prozessindustrie geschaffen, um zielgerichtet auf Kundenbedürfnisse der Prozessindustrie zugeschnittene Produktentwicklungen, technologische Weiterentwicklungen und Forschungsprojekte zum Erfolg zu bringen. Die Roadmap „Prozesssensoren 2015+“ fand große Akzeptanz aufgrund der soliden Betrachtung der Prozesse und der daraus abgeleiteten Thesen. Diese Aussagen haben in vollem Umfang weiterhin Gültigkeit. Im Rückblick auf die damals formulierten Entwicklungsziele wurden viele dieser Ziele im prognostizierten Zeithorizont auf den Weg gebracht und teilweise bereits umgesetzt. In dieser Technologie-Roadmap werden einige Beispiele dazu aufgezeigt. KW - Roadmap KW - Industrie 4.0 KW - Prozess-Sensoren KW - Prozessanalytik KW - Sensoren PY - 2015 UR - http://www.namur.net/fileadmin/media_www/Roadmap_Dateien/Roadmap_Prozesssensoren_4.0.pdf SP - 1 EP - 36 AN - OPUS4-34947 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - BOOK A1 - Maiwald, Michael A1 - Bassler, M. A1 - Deilmann, M. A1 - Ens, W. A1 - Frenzel, F. A1 - Gerlach, M. A1 - Großmann, J. A1 - Grümbel, F. A1 - Heisterkamp, M. A1 - Kaiser, U. A1 - Lambrecht, A. A1 - Ohlenkamp, R. A1 - Pötter, T. A1 - Pyka, P. A1 - Roos, E. A1 - Schmidt, A. A1 - Schünemann, U. A1 - Theuer, M. A1 - Tukle, A. A1 - Weber, N. T1 - Technologie-Roadmap „Prozess-Sensoren 2027+“ N2 - Die Technologie-Roadmap „Prozess-Sensoren 2027+“ ist eine Weiterentwicklung vorgängiger Technologie-Roadmaps. Im Zentrum dieser Roadmaps stehen Sensoren zur Erfassung von physikalischen und chemischen Messgrößen mittels spezifischer und unspezifischer Messverfahren, die zur Steuerung und dem besseren Verständnis von Prozessen dienen. Die Roadmap fasst die gemeinsame Technologie- und Marktsicht von Anwendern, Herstellern und Forschungseinrichtungen im Bereich Prozess-Sensorik in der verfahrenstechnischen Industrie zusammen. Sie beschreibt die wesentlichen Trends im Bereich Prozess-Sensorik und künftige Handlungsbedarfe für Hersteller, Anwender sowie für Einrichtungen der Forschung und Lehre. Für die aktuellen und zukünftigen Anforderungen an Prozess-Sensoren werden 19 Thesen formuliert. Die Thesen basieren auf den Thesen der vorangegangenen Roadmaps, wobei die aus heutiger Sicht erforderlichen Anpassungen, Ergänzungen und teilweise auch Streichungen vorgenommen wurden. Die Thesen sind in 5 Themencluster eingeordnet. Digitalisierung und Nachhaltigkeit sind übergreifende Kernthemen der künftigen Entwicklung. KW - Technologie-Roadmap Prozess-Sensoren KW - Prozessindustrie KW - Prozessanalytik KW - Sensorik KW - Digitalisierung KW - NAMUR PY - 2021 SP - 1 EP - 63 AN - OPUS4-53741 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zhou, Z. A1 - Han, Q. A1 - Wang, D. A1 - Macé, T. A1 - Kipphardt, Heinrich A1 - Maiwald, Michael A1 - Tuma, Dirk A1 - Uehara, S. A1 - Akima, D. A1 - Shimosaka, T. A1 - Jung, J. A1 - Oh, S.-H. A1 - van der Veen, A. A1 - van Wijk, J.I.T. A1 - Ziel, P. R. A1 - Konopelko, L. A1 - Valkova, M. A1 - Mogale, D.M. A1 - Botha, A. A1 - Brewer, P. A1 - Murugan, A. A1 - Minnaro, M.D. A1 - Miller, M. A1 - Guenther, F. A1 - Kelly, M.E. T1 - CCQM K101 Final report international comparison CCQM-K101:Oxygen in nitrogen-a track B comparison and that the matrix contains argon N2 - This key comparison aims to assess the capabilities of the participants to determine the amount-of-substance fraction oxygen in nitrogen. The GAWG has classified this as a track B comparison, due to the unexpected 50 μmol/mol argon mole fraction content of the transfer standards, which effects the achievable performance of some measurement techniques such a GC-TCD. The separation of oxygen and argon is challenging, and not all systems in use are equally well designed for it. As this analytical challenge due to a substantial fraction of argon in the transfer standards became a reality, the Gas Analysis Working Group (GAWG) decided to qualify this key comparison as a regular key comparison and not as a core comparison, which may be used to support calibration and measurement capabilities (CMCs) for oxygen in nitrogen, or for oxygen in nitrogen mixtures containing argon only (see also the section on support to CMCs). KW - CCQM-K101 KW - Gas analysis PY - 2016 UR - http://iopscience.iop.org/article/10.1088/0026-1394/53/1A/08013 SN - 1681-7575 SN - 0026-1394 VL - 53 IS - Techn Suppl SP - 08013, 1 EP - 71 PB - IOP publishing AN - OPUS4-40013 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Gottu Mukkula, A. R. A1 - Kern, Simon A1 - Salge, M. A1 - Holtkamp, M. A1 - Guhl, Svetlana A1 - Fleischer, C. A1 - Meyer, Klas A1 - Remelhe, M. A1 - Maiwald, Michael A1 - Engell, S. T1 - An Application of Modifier Adaptation with Quadratic Approximation on a Pilot Scale Plant in Industrial Environment N2 - The goal of this work is to identify the optimal operating input for a lithiation reaction that is performed in a highly innovative pilot scale continuous flow chemical plant in an industrial environment, taking into account the process and safety constraints. The main challenge is to identify the optimum operation in the absence of information about the reaction mechanism and the reaction kinetics. We employ an iterative real-time optimization scheme called modifier adaptation with quadratic approximation (MAWQA) to identify the plant optimum in the presence of plant-model mismatch and measurement noise. A novel NMR PAT-sensor is used to measure the concentration of the reactants and of the product at the reactor outlet. The experiment results demonstrate the capabilities of the iterative optimization using the MAWQA algorithm in driving a complex real plant to an economically optimal operating point in the presence of plant-model mismatch and of process and measurement uncertainties. KW - Process Analytical Technology KW - Online NMR Spectroscopy KW - Process Industry KW - Iterative real-time optimization KW - Modifier adaptation KW - Plant-model mismatch KW - Reactor control KW - CONSENS PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-524531 DO - https://doi.org/10.1016/j.ifacol.2020.12.685 SN - 1522-2640 VL - 53 IS - 2 SP - 11773 EP - 11779 PB - Elsevier CY - Amsterdam AN - OPUS4-52453 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Oudwater, R. J. A1 - van Wijk, J. I. T. A1 - Persijn, S. A1 - Wessel, R. M. A1 - van der Veen, A. M. H. A1 - Mace, T. A1 - Sutour, C. A1 - Couette, J. A1 - Milton, M. A1 - Harling, A. A1 - Vargha, G. A1 - Uprichard, I. A1 - Haerri, H.-P. A1 - Niederhauser, B. A1 - Tuma, Dirk A1 - Maiwald, Michael A1 - Boissière, Claudia T1 - Final report on EURAMET QM-S8: Analysis of impurities in pure and balance gases used to prepare primary standard gas mixtures by the gravimetric method N2 - This project concerns the purity analysis of nitrogen as used in reference gas mixture preparation. This project was carried out without adding impurities to the gas used for this comparison, and is therefore more representative to evaluate the analysis of CO, CO2, CH4, O2, Ar and H2O impurities in high purity nitrogen. The analysis of the amount–of–substance fraction water was optional. Two 50 litre high purity nitrogen cylinders were purchased from a well-qualified supplier of specialty gases. The listed components were expected to be present in the pure nitrogen at the target levels as a result of the purification of the nitrogen. From the start of this comparison it was clear that the comparison may not lead to reference values for the constituents analysed. The results indicate that analyses of high purity gases are often limited by the limits of detection of analytical equipment used. The reports of the participating laboratories also indicate that there is no agreed method of determination of the uncertainty on a detection Limit value. The results provide useful information on the Performance of participants. For all analysed components there is reasonable agreement in results for LNE, VSL, Metas and NPL. For BAM only the Argon result is in agreement. KW - Gas analysis KW - Nitrogen KW - Purity analysis PY - 2013 DO - https://doi.org/10.1088/0026-1394/50/1A/08023 SN - 0026-1394 SN - 1681-7575 VL - 50 IS - 08023 SP - 1 EP - 58 PB - Institute of Physics Publishing CY - Bristol AN - OPUS4-35896 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Wander, Lukas A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gottu Mukkula, A. R. A1 - Holtkamp, M. A1 - Salge, M. A1 - Fleischer, C. A1 - Weber, N. A1 - King, R. A1 - Engell, S. A1 - Paul, Andrea A1 - Pereira Remelhe, M. A1 - Maiwald, Michael T1 - Flexible Automation with compact NMR instruments N2 - Modular plants using intensified continuous processes represent an appealing concept to produce pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes, and it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and includes a compact Nuclear Magnetic Resonance (NMR) spectrometer for online quality monitoring as well as a new model-based control approach. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including ro-bust evaluation of sensor data. Here, we present alternatives for the quantitative determination of the analytes using modular, physically motivated models. These models can be adapted to new substances solely by the use of their corresponding pure component spectra, which can either be derived from experimental spectra as well as from quantum mechanical models or NMR predictors. Modular means that spec-tral models can simply be exchanged together with alternate reagents and products. Beyond that, we comprehensively calibrated an NIR spectrometer based on online NMR process data for the first time within an industrial plant. The integrated solution was developed for a metal organic reac-tion running on a commercial-scale modular pilot plant and it was tested under industrial conditions. T2 - 7th Annual PANIC Conference CY - Hilton Head Island, South Carolina, USA DA - 03.03.2019 KW - Online NMR Spectroscopy PY - 2019 AN - OPUS4-47715 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kern, Simon A1 - Wander, Lukas A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gottu Mukkula, A. R. A1 - Holtkamp, M. A1 - Salge, M. A1 - Fleischer, C. A1 - Weber, N. A1 - Engell, S. A1 - Paul, Andrea A1 - Pereira Remelhe, M. A1 - Maiwald, Michael T1 - Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals N2 - Modular plants using intensified continuous processes represent an appealing concept for the production of pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes; besides, it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and is based on a compact nuclear magnetic resonance (NMR) spectrometer. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including robust evaluation of sensor data. Beyond monitoring the product quality, online NMR data was used in a new iterative optimization approach to maximize the plant profit and served as a reliable reference for the calibration of a near-infrared (NIR) spectrometer. The overall approach was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance. KW - NMR Spectroscopy KW - NIR Spectroscopy KW - Real-time process monitoring KW - Real-time quality control KW - Continuous processes KW - CONSENS KW - Data Fusion PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-480623 DO - https://doi.org/10.1007/s00216-019-01752-y SN - 1618-2642 SN - 1618-2650 VL - 411 IS - 14 SP - 3037 EP - 3046 PB - Springer Nature CY - Heidelberg AN - OPUS4-48062 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Hampel, U. A1 - Schütze, A. A1 - Rädle, M. A1 - Rück, T. A1 - Krawczyk-Becker, M. A1 - Musch, T. A1 - Maiwald, Michael A1 - Fröhlich, H. J. A1 - Zeck, S. T1 - Positionspapier Sensorik für die Digitalisierung chemischer Produktionsanlagen N2 - Die chemische Industrie steht derzeit, wie viele andere Industriebereiche, vor den Herausforderungen einer Digitalisierung der Produktion. Sie ist der Schlüssel für die Flexibilisierung von Prozessen und Anlagen, für die Verkürzung von Produkteinführungszeiten sowie für den Zuschnitt der Produktion auf wechselnde Nachfrage und kürzere Produktlebenszyklen. Die Messtechnik und Sensorik spielt neben der intelligenten Datenverarbeitung eine Schlüsselrolle für die Digitalisierung. Flexiblere Anlagen benötigen Sensorik zur Überwachung des Anlagenzustandes, zur Früherkennung nicht bestimmungsgemäßer Betriebszustände sowie für eine bedarfsgerechte Wartung. Da die Entwicklung neuer und verbesserter Messtechnik und Sensorik grundlegend aus verschiedenen Richtungen gedacht werden muss, haben sich Akteure aus verschiedenen Branchen zusammengetan und dieses Positionspapier erstellt. Es basiert auf einer grundlegenden Analyse des Ist-Stands sowie des Bedarfs der Industrie, die unter anderem auf einem eigens dafür durchgeführten Workshop mit Sensorentwicklern, Anlagenherstellern sowie Anlagenbetreibern am 18. Juni 2019 bei der DECHEMA in Frankfurt a. M. diskutiert wurden. Diese Aktivitäten wurden maßgeblich von der Initiative Wanted Technologies der ProcessNet sowie dem AMA Verband für Sensorik und Messtechnik e.V. initiiert. KW - Prozessindustrie KW - Smarte Sensoren KW - Prozessanalytik KW - DECHEMA KW - Positionspapier PY - 2020 UR - https://dechema.de/Sensorik SP - 1 EP - 20 PB - DECHEMA CY - Frankfurt am Main AN - OPUS4-50403 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Maiwald, Michael A1 - Sperling, M. A1 - Huber, C. A1 - Hayen, H. A1 - Teutenberg, T. A1 - Belder, D. A1 - Karst, U. A1 - Hagenhoff, B. A1 - Vogel, M. T1 - Prozessanalytik: Spektroskopie und Miniaturisierung N2 - Forderungen nach höherer Geschwindigkeit und die Komplexität der Fragen geben der analytischen Chemie neue Impulse. So nutzt die Prozessanalytik gepulste Ramanspektrometer, die Elemente Arsen und Quecksilber dominieren die Forschung in der Speziesanalytik, und die Omics-Techniken entwickeln sich zu Multi-Omics-Ansätzen. Ambiente MS-Techniken benötigen keine aufwendige Probenvorbereitung, multidimensionale Trenntechniken werden verstärkt in der Routine eingesetzt, und Chip-basierte Trennungen fallen durch Schnelligkeit auf. Molekülspektroskopie und Massenspektrometrie dominieren die bildgebenden Verfahren, und die Lateralauflösung der ToF-Sekundärionenmassenspektrometrie hat sich bei Oberflächenuntersuchungen verbessert. KW - Prozessanalytik KW - Quanten-Kaskadenlaser KW - Photonendichtewellen-Spektroskopie KW - Gepulste Ramanspektrometer KW - Partikelmesstechnik KW - Prozesssensoren PY - 2016 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-361371 UR - http://onlinelibrary.wiley.com/doi/10.1002/nadc.20164046080/abstract DO - https://doi.org/10.1002/nadc.20164046080 SN - 1868-0054 VL - 64 IS - 5 SP - 497 EP - 508 PB - Wiley-VCH Verlag GmbH & Co. KGaA CY - Weinheim AN - OPUS4-36137 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Koegler, M. A1 - Paul, Andrea A1 - Anane, E. A1 - Birkholz, M. A1 - Bunker, A. A1 - Viitala, T. A1 - Maiwald, Michael A1 - Junne, S. A1 - Neubauer, P. T1 - Comparison of time-gated surface-enhanced Raman spectroscopy (TG-SERS) and classical SERS based monitoring of Escherichia coli cultivation samples N2 - The application of Raman spectroscopy as a monitoring technique for bioprocesses is severely limited by a large background signal originating from fluorescing compounds in the culture media. Here, we compare time-gated Raman (TG-Raman)-, continuous wave NIRprocess Raman (NIR-Raman), and continuous wave micro-Raman (micro-Raman) approaches in combination with surface enhanced Raman spectroscopy (SERS) for their potential to overcome this limit. For that purpose, we monitored metabolite concentrations of Escherichia coli bioreactor cultivations in cell-free supernatant samples. We investigated concentration transients of glucose, acetate, AMP, and cAMP at alternating substrate availability, from deficiency to excess. Raman and SERS signals were compared to off-line metabolite analysis of carbohydrates, carboxylic acids, and nucleotides. Results demonstrate that SERS, in almost all cases, led to a higher number of identifiable signals and better resolved spectra. Spectra derived from the TG-Raman were comparable to those of micro-Raman resulting in well-discernable Raman peaks, which allowed for the identification of a higher number of compounds. In contrast, NIR-Raman provided a superior performance for the quantitative evaluation of analytes, both with and without SERS nanoparticles when using multivariate data analysis. KW - Time-gated Raman (TG-Raman) KW - Surface-enhanced Raman spectroscopy (SERS) KW - Multivariate data analysis KW - Metabolite quantification KW - Escherichia coli PY - 2018 DO - https://doi.org/10.1002/btpr.2665 SN - 1520-6033 SN - 8756-7938 VL - 34 IS - 6 SP - 1533 EP - 1542 PB - Wiley AN - OPUS4-45831 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kern, Simon A1 - Wander, Lukas A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gottu Mukkula, A. R. A1 - Holtkamp, M. A1 - Salge, M. A1 - Fleischer, C. A1 - Weber, N. A1 - Engell, S. A1 - Paul, Andrea A1 - King, R. A1 - Maiwald, Michael T1 - Raw data of pilot plant runs for CONSENS project (Case study 1) N2 - In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and o-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum. The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17. In the following the contents of the files are explained. KW - Process Analytical Technology KW - Multivariate Data Analysis KW - Nuclear Magnetic Resonance KW - Near Infrared Spectroscopy KW - Continuous Manufacturing KW - CONSENS PY - 2018 DO - https://doi.org/10.5281/zenodo.1438233 PB - Zenodo CY - Geneva AN - OPUS4-48063 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - RPRT A1 - Maiwald, Michael A1 - Gasch, A. A1 - Gerlach, M. A1 - Kaiser, U. A1 - Kloska, M. A1 - Matalla, N. A1 - Morr, W. A1 - Panzke, R. A1 - Stieler, S. A1 - Westerkamp, D. T1 - Prozess-Sensoren 2015+ - Technologie-Roadmap für Prozess-Sensoren in der chemisch-pharmazeutischen Industrie PY - 2009 SP - 1 EP - 71 AN - OPUS4-20699 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Fricke, F. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Meyer, Klas A1 - Kowarik, Stefan A1 - Hierzegger, R. A1 - Westerdick, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy Using a Novel Data Augmentation Method N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are valuable analytical and quality control methods for most industrial chemical processes as they provide information on the concentrations of individual compounds and by-products. These processes are traditionally carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been realized to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra, to train an ANN with better prediction performance and speed than state-of-the-art analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. KW - Industry 4.0 KW - Cyber-Physical Systems KW - Artificial Neural Networks KW - Mass Spectrometry KW - Nuclear Magnetic Resonance Spectroscopy KW - Modular Production PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-539412 UR - https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9638378 DO - https://doi.org/10.1109/TETC.2021.3131371 SN - 2168-6750 VL - 10 IS - 1 SP - 87 EP - 98 PB - IEEE AN - OPUS4-53941 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Fricke, F. A1 - Mahmood, S. A1 - Hoffmann, J. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Meyer, Klas A1 - Kowarik, S. A1 - Westerdick, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. T2 - 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) CY - Grenoble, France DA - 01.02.2021 KW - Industry 4.0, KW - Cyber-physical systems KW - Artificial neural networks KW - Mass spectrometry KW - Nuclear magnetic resonance spectroscopy PY - 2021 DO - https://doi.org/10.23919/DATE51398.2021.9473958 SP - 615 EP - 620 PB - IEEE AN - OPUS4-55360 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Fricke, F. A1 - Mahmood, S. A1 - Hoffmann, J. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Meyer, Klas A1 - Kowarik, Stefan A1 - Westerdicky, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. T2 - 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) CY - Online meeting DA - 01.02.2021 KW - Industry 4.0 KW - Cyber-Physical Systems KW - Artificial Neural Networks KW - Mass Spectrometry KW - Nuclear Magnetic Resonance Spectroscopy PY - 2021 UR - www.date-conference.com SN - 978-3-9819263-5-4 SP - 615 EP - 620 PB - Research Publishing AN - OPUS4-52180 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Alfeld, M. A1 - Eckhardt, H.-S. A1 - Kraft, J. A1 - Maiwald, Michael A1 - Meermann, Björn A1 - Merz, K. A1 - Prikler, S. A1 - Richert, J. A1 - Steiner, G. A1 - von Tümpling, W. T1 - Trendbericht Analytische Chemie N2 - Zusätzlich zu Methodenentwicklung, Miniaturisierung und Kopplungsverfahren zeigen sich die Hyperspektroskopie zusammen mit Imaging‐Verfahren, der Einzelmolekülnachweis und der Einsatz von 3‐D‐Druckern als neue Schwerpunkte. Hinzu kommen künstliche Intelligenz bei Sensoren, Bildgebungsverfahren und Prozesssteuerung sowie die Vernetzung von Analyse‐ und Laborgeräten. Trends und Forschungsthemen aus der analytischen Chemie, zusammengestellt von elf Autoren, koordiniert von Günter Gauglitz. KW - Multielementanalytik KW - Multimodale Analytik KW - Kristallolgraphie KW - Prozessanalytik KW - Prozessindustrie KW - Industrielle Analytik KW - Chemometrik KW - Chemometrie PY - 2020 DO - https://doi.org/10.1002/nadc.20204095786 SN - 1868-0054 VL - 68 IS - 4 SP - 52 EP - 60 PB - Wiley CY - Weinheim AN - OPUS4-50609 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zientek, Nicolai A1 - Laurain, C. A1 - Meyer, Klas A1 - Paul, Andrea A1 - Engel, D. A1 - Guthausen, G. A1 - Kraume, M. A1 - Maiwald, Michael T1 - Automated data evaluation and modelling of simultaneous F-19-H-1 medium-resolution NMR spectra for online reaction monitoring N2 - 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. KW - NMR KW - 1H-NMR KW - 19F-NMR KW - Medium-resolution NMR KW - Online NMR KW - Quantitative NMR KW - Reaction monitoring KW - Data processing KW - Automation KW - Process analytical technology KW - IHM KW - Indirect hard modeling KW - Chemometrics KW - PLS-R KW - Partial least squares regression PY - 2016 UR - http://onlinelibrary.wiley.com/doi/10.1002/mrc.4216/abstract DO - https://doi.org/doi:10.1002/mrc.4216 VL - 54 SP - 513 EP - 520 PB - John Wiley & Sons, Ltd CY - Hoboken, New Jersey, USA AN - OPUS4-36135 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zientek, Nicolai A1 - Laurain, Clement A1 - Meyer, Klas A1 - Paul, Andrea A1 - Engel, D. A1 - Guthausen, G. A1 - Kraume, M. A1 - Maiwald, Michael T1 - Automated data evaluation and modeling of simultaneous 19F-1H medium resolution NMR spectra for online reaction monitoring N2 - Medium resolution nuclear magnetic resonance spectroscopy (MR-NMR) currently develops to an important analytical tool for both quality control and process monitoring. 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 were treated by an automated baseline and phase correction using the minimum entropy method. The evaluation strategies comprised direct integration, automated line fitting, indirect hard modeling, and partial least squares regression. T2 - 10. Kolloquium Arbeitskreis Prozessanalytik CY - Gerlingen, Germany DA - 25.11.2014 KW - Online NMR spectroscopy KW - Data evaluation KW - Reaction monitoring KW - Indirect hard modeling PY - 2014 UR - http://arbeitskreis-prozessanalytik.de/images/stories/Veranstaltungen/Kolloquien/10_kolloquium_2014/tagungsband_10_kolloquium_ak_prozessanalytik_2014_hq-druck_f.pdf SP - P04, 24 EP - 25 PB - BAM Bundesanstalt für Materialforschung und -prüfung CY - Berlin AN - OPUS4-38360 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Guthausen, G. A1 - Dalitz, F. A1 - Zientek, Nicolai A1 - Nirschl, H. A1 - Kraume, M. A1 - Maiwald, Michael T1 - Applikationen der Medium-Resolution-NMR-Spektroskopie in der Prozessanalytik: Potenzial und Herausforderungen N2 - Die kernmagnetische Resonanz (NMR) erlaubt über die zeitaufgelöste Messung der chemischen Verschiebung und der Kopplungskonstanten eine andere Blickweise auf Moleküle, die an Reaktionen und anderen dynamischen Prozessen beteiligt sind und ermöglicht somit die Charakterisierung von Prozessen, die über optische Eigenschaften funktioneller Gruppen oft nicht zugänglich sind, z. B. Hydrierungen oder Isomerisierungen KW - Medium-Resolution-NMR-Spektroskopie KW - Prozessanalytik PY - 2012 SN - 0009-286X SN - 1522-2640 VL - 84 IS - 8 SP - 1364 PB - Wiley-VCH Verl. CY - Weinheim AN - OPUS4-28269 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zientek, Nicolai A1 - Laurain, Clement A1 - Meyer, Klas A1 - Kraume, M. A1 - Guthausen, G. A1 - Maiwald, Michael T1 - Simultaneous 19F-1H medium resolution NMR spectroscopy for online reaction monitoring N2 - Medium resolution nuclear magnetic resonance (MR-NMR) spectroscopy is currently a fast developing field, which has an enormous potential to become an important analytical tool for reaction monitoring, in hyphenated techniques, and for systematic investigations of complex mixtures. The recent developments of innovative MR-NMR spectrometers are therefore remarkable due to their possible applications in quality control, education, and process monitoring. MR-NMR spectroscopy can beneficially be applied for fast, non-invasive, and volume integrating analyses under rough environmental conditions. Within this study, a simple 1/16'' fluorinated ethylene propylene (FEP) tube with an ID of 0.04'' (1.02 mm) was used as a flow cell in combination with a 5 mm glass Dewar tube inserted into a benchtop MR-NMR spectrometer with a 1H Larmor frequency of 43.32 MHz and 40.68 MHz for 19F. For the first time, quasi-simultaneous proton and fluorine NMR spectra were recorded with a series of alternating 19F and 1H single scan spectra along the reaction time coordinate of a homogeneously catalysed esterification model reaction containing fluorinated compounds. The results were compared to quantitative NMR spectra from a hyphenated 500 MHz online NMR instrument for validation. Automation of handling, pre-processing, and analysis of NMR data becomes increasingly important for process monitoring applications of online NMR spectroscopy and for its technical and practical acceptance. Thus, NMR spectra were automatically baseline corrected and phased using the minimum entropy method. Data analysis schemes were designed such that they are based on simple direct integration or first principle line fitting, with the aim that the analysis directly revealed molar concentrations from the spectra. Finally, the performance of 1/16'' FEP tube set-up with an ID of 1.02 mm was characterised regarding the limit of detection (LOQ (1H) = 0.335 mol L-1 and LOQ (19F) = 0.130 mol L-1 for trifluoroethanol in D2O (single scan)) and maximum quantitative flow rates up to 0.3 mL min-1. Thus, a series of single scan 19F and 1H NMR spectra acquired with this simple set-up already presents a valuable basis for quantitative reaction monitoring. KW - NMR KW - 1H KW - 19F KW - Medium-resolution NMR KW - Online NMR KW - Quantitative NMR KW - Reaction monitoring KW - Data processing KW - Process analytical technology PY - 2014 DO - https://doi.org/10.1016/j.jmr.2014.10.007 SN - 1090-7807 SN - 0022-2364 VL - 249 SP - 53 EP - 62 PB - Elsevier CY - San Diego, Calif. AN - OPUS4-32008 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -