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 U6 - 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 - JOUR A1 - Wander, Lukas A1 - Lommel, Lukas A1 - Meyer, Klas A1 - Braun, Ulrike A1 - Paul, Andrea T1 - Development of a low-cost method for quantifying microplastics in soils and compost using near-infrared spectroscopy N2 - Near-infrared (NIR) spectroscopy is a promising candidate for low-cost, nondestructive, and high-throughput mass quantification of micro¬plastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermo-analytical approaches commonly used for this type of analysis. This study shows how the application of NIR spectroscopy for mass quantification of microplastics can be extended to smaller analyte levels by combining it with a simple and rapid microplastic enrichment protocol. For this purpose, the widely used flotation of microplastics in a NaCl solution, accelerated by centrifugation, was chosen which allowed to remove up to 99 % of the matrix at recovery rates of 83–104 %. The spectroscopic measurements took place directly on the stainless-steel filters used to collect the extracted particles to reduce sample handling to a minimum. Partial least squares regression (PLSR) models were used to identify and quantify the extracted microplastics in the mass range of 1–10 mg. The simple and fast extraction procedure was systematically optimized to meet the requirements for the quantification of microplastics from common PE-, PP-, and PS-based packaging materials with a particle size < 1 mm found in compost or soils with high natural organic matter content (> 10 % determined by loss on ignition). Microplastics could be detected in model samples at a mass fraction of 1 mg g-1. The detectable microplastic mass fraction is about an order of magnitude lower compared to previous studies using NIR spectroscopy without additional enrichment. To emphasize the cost-effectiveness of the method, it was implemented using some of the cheapest and most compact NIR spectrometers available. KW - NIR KW - Soil KW - compost KW - PLSR PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-546405 SN - 0957-0233 VL - 33 IS - 7 SP - 075801 EP - 075814 PB - IOP Publishing Ltd. CY - UK AN - OPUS4-54640 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Paul, Andrea A1 - Meyer, Klas A1 - Ruiken, Jan-Paul A1 - Illner, M. A1 - Müller, D.-N. A1 - Esche, E. A1 - Wozny, G. A1 - Westad, Frank A1 - Maiwald, Michael T1 - Process spectroscopy in microemulsions — Raman spectroscopy for online monitoring of a homogeneous hydroformylation process N2 - A major industrial reaction based on homogeneous catalysis is hydroformylation for the production of aldehydes from alkenes and syngas. Hydroformylation in microemulsions, which is currently under investigation at Technische Universität Berlin on a mini-plant scale, was identified as a cost efficient approach which also enhances product selectivity. Herein, we present the application of online Raman spectroscopy on the reaction of 1-dodecene to 1-tridecanal within a microemulsion. To achieve a good representation of the operation range in the mini-plant with regard to concentrations of the reactants a design of experiments was used. Based on initial Raman spectra partial least squares regression (PLSR) models were calibrated for the prediction of 1-dodecene and 1-tridecanal. Limits of predictions arise from nonlinear correlations between Raman intensity and mass fractions of compounds in the microemulsion system. Furthermore, the prediction power of PLSR models becomes limited due to unexpected by-product formation. Application of the lab-scale derived calibration spectra and PLSR models on online spectra from a mini-plant operation yielded promising estimations of 1-tridecanal and acceptable predictions of 1-dodecene mass fractions suggesting Raman spectroscopy as a suitable technique for process analytics in microemulsions. KW - Raman KW - Online KW - Chemometrics KW - Hydroformylation KW - Mini-plant KW - Microemulsion PY - 2017 U6 - https://doi.org/10.1088/1361-6501/aa54f0 SN - 1361-6501 SN - 0957-0233 VL - 28 IS - 3 SP - 035502-1 EP - 035502-11 PB - IOP Publishing Ltd CY - UK AN - OPUS4-39032 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Meyer, Klas A1 - Ruiken, J.-P. A1 - Illner, M. A1 - Paul, Andrea A1 - Müller, D. A1 - Esche, E. A1 - Wozny, G. A1 - Maiwald, Michael T1 - Process spectroscopy in microemulsions - setup and multi-spectral approach for reaction monitoring of a homogeneous hydroformylation process N2 - Reaction monitoring in disperse systems, such as emulsions, is of significant technical importance in various disciplines like biotechnological engineering, chemical industry, food science, and a growing number other technical fields. These systems pose several challenges when it comes to process analytics, such as heterogeneity of mixtures, changes in optical behavior, and low optical activity. Concerning this, online nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for process monitoring in complex reaction mixtures due to its unique direct comparison abilities, while at the same time being non-invasive and independent of optical properties of the sample. In this study the applicability of online-spectroscopic methods on the homogeneously catalyzed hydroformylation system of 1-dodecene to tridecanal is investigated, which is operated in a mini-plant scale at Technische Universität Berlin. The design of a laboratory setup for process-like calibration experiments is presented, including a 500 MHz online NMR spectrometer, a benchtop NMR device with 43 MHz proton frequency as well as two Raman probes and a flow cell assembly for an ultraviolet and visible light (UV/VIS) spectrometer. Results of high-resolution online NMR spectroscopy are shown and technical as well as process-specific problems observed during the measurements are discussed. KW - Online-spectroscopy KW - Quantitative NMR spectroscopy KW - Process analytical technology KW - Microemulsions PY - 2017 U6 - https://doi.org/10.1088/1361-6501/aa54f3 SN - 0957-0233 SN - 1361-6501 VL - 28 IS - 3 SP - 035501-1 EP - 035501-11 PB - IOP Publishing Ltd. AN - OPUS4-39091 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 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-480623 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 - 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 - Bremser, Wolfram 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 environ¬ments 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 - Advanced Mathematical and Computational Tools in Metrology and Testing conference CY - Glasgow, United Kingdom DA - 29.08.2017 KW - Online NMR Spectroscopy KW - Process Control KW - Partial Least Squares Regression KW - Indirect Hard Modelling KW - Quantum Mechanics KW - First Principles PY - 2018 SN - 978-9-813-27429-7 VL - 89 SP - 229 EP - 234 PB - World Scientific CY - New Jersey AN - OPUS4-51391 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -