TY - JOUR A1 - Bornemann-Pfeiffer, Martin A1 - Kern, Simon A1 - Maiwald, Michael A1 - Meyer, Klas T1 - Calibration-Free Chemical Process and Quality Control Units as Enablers for Modular Production N2 - Modular chemical production is a tangible translation of the digital transformation of the process industry for specialty chemicals. In particular, it enables the speeding-up of process development and thus a quicker time to market by flexibly connecting and orchestrating standardised physical modules and bringing them to life (i.e., parameterising them) with digitally accumulated process knowledge. We focus on the specific challenges of chemical process and quality control, which in its current form is not well suited for modular production and provide possible approaches and examples of the change towards direct analytical methods, analytical model transfer or machine-supported processes. KW - Modular Production KW - Chemical Process Control KW - Process Analytical Technology KW - Digital Transformation KW - Industry 4.0 PY - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-517264 SN - 1522-2640 VL - 93 IS - 1-2 SP - 62 EP - 70 PB - Wiley-VCH CY - Weinheim AN - OPUS4-51726 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 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-524531 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 - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Paul, Andrea A1 - Wander, Lukas A1 - Gräßer, Patrick A1 - Maiwald, Michael T1 - Design and Validation of a Compact NMR Analyser 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 Unionʼs Research Project CONSENS (Integrated Control and Sensing) 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 - 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017) CY - Potsdam, Germany DA - 10.05.2017 KW - Prozessanalytik KW - Reaction Monitoring KW - Online NMR Spectrsocopy KW - Process Analytical Technology KW - Industrie 4.0 KW - EuroPACT PY - 2017 SP - 72 EP - 73 CY - Frankfurt a. M. AN - OPUS4-40229 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Meyer, Klas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Online low-field NMR spectroscopy of an industrial lithiation reaction step for process control N2 - Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectroscopy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory. Within the project CONSENS, the continuous production of high-value products in small production scale is advanced by introducing benchtop NMR spectroscopy. CONSENS is a research and innovation project on integrated control and sensing for sustainable operation of flexible intensified processes. This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Furthermore, first online spectra of the lithiation reaction in batch mode were acquired in lab scale. The reaction was performed in a 25 mL glass reactor with thermal jackets for temperature control of the reaction mixture. The Li-HMDS was dosed stepwise by using a glass syringe. First spectra in the proton and fluorine domain were recorded online using a flowrate of 3.5 mL min–1 and a simple 5 mm polytetrafluoroethylene tube (PTFE) as a flow cell. T2 - 10. Interdisziplinaeres Doktorandenseminar Fachgruppe "Analytische Chemie" der GDCh CY - Berlin, Germany DA - 28.02.2016 KW - Online NMR Spectroscopy KW - Reaction monitoring PY - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-354443 AN - OPUS4-35444 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Maiwald, Michael T1 - First steps towards field integration of benchtop NMR spectroscopy for online monitoring and process control N2 - Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectros-copy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical com-parison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory. Wthin the project CONSENS (www.consens-spire.eu), the continuous production of high-value products in small production scale is advanced by introducing benchtop NMR spectroscopy. CONSENS is a research and innovation project on inte-grated control and sensing for sustainable operation of flexible intensified processes. This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Furthermore, first online spectra of the lithiation reaction in batch mode were acquired in lab scale. The reaction was performed in a 25 mL glass reactor with thermal jackets for temperature control of the reaction mixture. The Li-HMDS was dosed stepwise by using a glass syringe. First spectra in the proton and fluorine domain were recorded online using a flowrate of 3.5 mL min–1 and a simple 5 mm polytetrafluoroethylene tube (PTFE) as a flow cell. T2 - 11. Kolloquium Prozessanalytik CY - Wien, Autria DA - 30.11.2015 PY - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-351597 AN - OPUS4-35159 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Zientek, Nicolai A1 - Maiwald, Michael A1 - Gräßer, P. T1 - First steps towards field integration of benchtop NMR spectroscopy for online monitoring and process control N2 - Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectroscopy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory. Within the project CONSENS, the continuous production of high-value products in small production scale is advanced by introducing MR-NMR spectroscopy. CONSENS is a research and innovation project on integrated control and sensing for sustainable operation of flexible intensified processes. This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Additionally, the first results of the lithiation reaction in lab scale regarding the pure components and reaction mixtures are going to be discussed. T2 - Pro2NMR Autum School CY - Aachen, Germany DA - 08.12.2015 PY - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-351097 AN - OPUS4-35109 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kern, Simon A1 - Zientek, Nicolai A1 - Maiwald, Michael T1 - First steps towards field integration of benchtop NMR spectroscopy for online monitoring and process control N2 - Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectroscopy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory. Within the project CONSENS, the continuous production of high-value products in small production scale is advanced by introducing MR-NMR spectroscopy. CONSENS is a research and innovation project on integrated control and sensing for sustainable operation of flexible intensified processes. This poster will present the first steps of the process integration of a benchtop NMR instrument for a lithiation process and outlines further fields of activity and potential challenges. Hereby, the following issues are going to be addressed: explosion-proof housing for the spectrometer, automation of signal processing (data pretreatment, evaluation and communication to the control system), flow cells and measuring conditions. Additionally, the first results of the lithiation reaction in lab scale regarding the pure components and reaction mixtures are going to be discussed. T2 - Small Molecule NMR Conference CY - Baveno, Italy DA - 17.09.2015 PY - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-351085 AN - OPUS4-35108 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 - 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 - 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 - CONF A1 - Kern, Simon A1 - Bornemann-Pfeiffer, Martin A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Wander, Lukas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Advances of Model-Based Data Evaluation Concepts for Quantitative Online NMR Spectroscopy 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 used for process characterisation and optimisation. 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 online NMR spectroscopy 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 module 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 - SciX 2018 CY - Atlanta, GA, USA DA - 22.10.2018 KW - Online NMR Spectroscopy PY - 2018 N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. AN - OPUS4-46377 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 - CONF A1 - Abele, M. A1 - Kern, Simon A1 - Maiwald, Michael A1 - Falkenstein, S. A1 - Meyer, Klas A1 - Friedrich, Y. A1 - Korth, K. T1 - Industrielle Anwendungen der Niederfeld-NMR-Spektroskopie für die Prozess- und Qualitätskontrolle von Silanen N2 - Trialkoxysilane haben sich in den vergangenen Jahren als vielseitig einsetzbare Organosilane erwiesen. Die Einsatzgebiete erstrecken sich vom Witterungsschutz von Bauwerken über haftvermittelnde Eigenschaften in der Glasfaserindustrie, bei Dicht- und Klebstoffen, in Farben und Lacken bis hin zur Modifizierung von polymeren Werkstoffen. Kommerzielle Benchtop-NMR-Spektrometer haben das Potential auch im Bereich der Silanchemie als Online-Methode zur Reaktionsüberwachung und für die Qualitätskontrolle eingesetzt zu werden. Interessante NMR-Kerne für die oben genanntem Produkte sind 1H und 29Si. In einer gemeinsamen Forschungskooperation zwischen EVONIK und BAM wurde anhand verschiedener Fallstudien die Anwendbarkeit der Niederfeld-NMR-Spektroskopie zur chemischen Analyse von Silanen evaluiert. Im Zuge der Fallstudien wurde gezeigt, wie Niederfeld-NMR-Spektroskopie die Möglichkeiten der Konzentrationsmessung auf neue Anwendungsgebiete erweitert, in denen bestehende Technologien wie z. B. NIR, Raman, UV/VIS, etc. mangels Referenzdaten nicht quantitativ eingesetzt werden können. Fallstudie 1: Oligomerisierung Eine Fallstudie setzte dazu an, den Hydrolyse- und Kondensationsverlauf mit einer geeigneten Online-NMR-Analytik zu beobachten, den Reaktionsfortschritt der Hydrolyse und Kondensation auf dieser Basis besser zu verstehen und zu optimieren. Zu diesem Zweck werden durch Zugabe von Wasser zunächst die Alkoxysubstituenten eines Trialkoxysilans hydrolysiert und entsprechende Silanole gebildet. Diese können dann über eine SiOH-Funktion an den zu modifizierenden Werkstoff anbinden und über weitere Silanolgruppen unter Ausbildung von Siloxaneinheiten vernetzen. Fallstudie 2: Spaltung von cyclischen Silanverbindungen In einer weiteren Fallstudie wurde die Kinetik der Aufspaltungen einer cyclischen Silanverbindung untersucht. Die Online-NMR-Analytik kam hierbei sowohl im Labor als auch in der industriellen Produktionsanlage zum Einsatz. Hierfür wurde eine vollständig automatisierte Einhausung verwendet, welche den Einsatz eines kommerziellen NMR-Spektrometers in explosionsgeschützten Bereichen ermöglicht. Fallstudie 3: Qualitätskontrolle für Produktmischungen von Trialkoxysilanen Für Produktmischungen eines Trialkoxysilans und weiteren Bestandteilen wie u. a. org. Stabilisatoren, Organozinnverbindungen, eines aromatischen Amins und org. Peroxide wurden quantitative 1H-Spektren akquiriert und eine automatische Auswertungsmethode basierend auf Indirect Hard Modeling (IHM) entwickelt. Für die Nebenkomponenten, deren Stoffmengenanteile bis zu 3 Mol-% betragen, wurden durch die zugrunde gelegte Methode typischerweise korrekte experimentelle Stoffmengenanteile gefunden, die weniger als 0,2 Mol-% vom Referenzwert abweichen. T2 - 15. Kolloquium Arbeitskreis Prozessanalytik CY - Marl, Germany DA - 25.11.2019 KW - Prozessanalytik KW - Qualitätskontrolle KW - Silane KW - Online-NMR-Spektroskopie KW - Trialkoxysilane PY - 2019 AN - OPUS4-49825 LA - deu 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 U6 - 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 - 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 -