TY - JOUR A1 - Wander, Lukas A1 - Lommel, Lukas A1 - Braun, Ulrike A1 - Meyer, Klas 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 highthroughput mass quantification of microplastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermoanalytical 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 - Mikroplastik KW - NIR KW - Sensor KW - Kompost KW - Multivariat PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-552605 VL - 33 IS - 7 SP - 1 EP - 13 PB - IOP Publishing Ltd. CY - Bristol AN - OPUS4-55260 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 - CONF A1 - Wander, Lukas A1 - Paul, Andrea A1 - Rurack, Knut A1 - Biyikal, Mustafa A1 - Juritsch, Elevtheria A1 - Bernstein, Thomas A1 - Bartholmai, Matthias A1 - Noske, Reinhard T1 - Kompaktsensor zur Online-Überwachung von Nitroaromaten N2 - Nitroaromaten und insbesondere Trinitrotoluol (TNT) sind weit verbreitete Spreng- und Umweltschadstoffe. Die größte Herausforderung bei der Detektion von TNT in der Gasphase ist der geringe Dampfdruck. Derzeit werden vielerorts günstige, schnelle, handliche und einfach zu bedienende Alternativen zur klassischen TNT-Analytik entwickelt. Aktuell existieren keine einheitlichen Richtlinien für Sprengstoffsensoren. Hier wird die Entwicklung eines Messplatzes zur Validierung von Sprengstoffsensoren sowie die Erprobung eines kompakten Mustersensors vorgestellt. T2 - 12. Kolloquium Prozessanalytik CY - Berlin, Germany DA - 28.11.2016 KW - Nitroaromaten KW - Fluoreszenzlöschung KW - Sensor PY - 2016 SP - P11, 61 EP - 62 AN - OPUS4-38402 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Paul, Andrea A1 - Wander, Lukas A1 - Becker, Roland A1 - Goedecke, Caroline A1 - Braun, Ulrike T1 - High-throughput NIR spectroscopic (NIRS) detection of microplastics in soil N2 - The increasing pollution of terrestrial and aquatic ecosystems with plastic debris leads to the accumulation of microscopic plastic particles of still unknown amount. To monitor the degree of contamination analytical methods are urgently needed, which help to quantify microplastics (MP). Currently, time-costly purified materials enriched on filters are investigated both by micro-infrared spectroscopy and/or micro-Raman. Although yielding precise results, these techniques are time consuming, and are restricted to the analysis of a small part of the sample in the order of few micrograms. To overcome these problems, here we tested a macroscopic dimensioned NIR process-spectroscopic method in combination with chemometrics. For calibration, artificial MP/soil mixtures containing defined ratios of polyethylene, polyethylene terephthalate, polypropylene, and polystyrene with diameters < 125 µm were prepared and measured by a process FT-NIR spectrometer equipped with a fiber optic reflection probe. The resulting spectra were processed by chemometric models including support vector machine regression (SVR), and partial least squares discriminant analysis (PLS-DA). Validation of models by MP mixtures, MP-free soils and real-world samples, e.g. and fermenter residue, suggest a reliable detection and a possible classification of MP at levels above 0.5 to 1.0 mass% depending on the polymer. The benefit of the combined NIRS chemometric approach lies in the rapid assessment whether soil contains MP, without any chemical pre-treatment. The method can be used with larger sample volumes and even allows for an online prediction and thus meets the demand of a high-throughput method. KW - Microplastics KW - Soil KW - Chemometrics KW - PLS-DA KW - Support vector machines KW - Near Infrared Spectroscopy PY - 2018 U6 - https://doi.org/10.1007/s11356-018-2180-2 SN - 1614-7499 SN - 0944-1344 VL - 26 IS - 8 SP - 7364 EP - 7374 PB - Springer AN - OPUS4-45405 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wander, Lukas A1 - Vianello, A. A1 - Vollertsen, J. A1 - Westad, F. A1 - Braun, Ulrike A1 - Paul, Andrea T1 - Exploratory analysis of hyperspectral FTIR data obtained from environmental microplastics samples N2 - Hyperspectral imaging of environmental samples with infrared microscopes is one of the preferred methods to find and characterize microplastics. Particles can be quantified in terms of number, size and size distribution. Their shape can be studied and the substances can be identified. Interpretation of the collected spectra is a typical problem encountered during the analysis. The image datasets are large and contain spectra of countless particles of natural and synthetic origin. To supplement existing Analysis pipelines, exploratory multivariate data analysis was tested on two independent datasets. Dimensionality reduction with principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) was used as a core concept. It allowed for improved visual accessibility of the data and created a chemical two-dimensional image of the sample. Spectra belonging to particles could be separated from blank spectra, reducing the amount of data significantly. Selected spectra were further studied, also applying PCA and UMAP. Groups of similar spectra were identified by cluster analysis using k-means, density based, and interactive manual clustering. Most clusters could be assigned to chemical species based on reference spectra. While the results support findings obtained with a ‘targeted analysis’ based on automated library search, exploratory analysis points the attention towards the group of unidientified spectra that remained and are otherwise easily overlooked. KW - Microplastics KW - FTIR KW - Exploratory analysis PY - 2020 U6 - https://doi.org/10.1039/c9ay02483b VL - 12 IS - 6 SP - 781 EP - 791 PB - Royal Society of Chemistry AN - OPUS4-50396 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wander, Lukas A1 - Vianello, A. A1 - Vollertsen, J. A1 - Braun, Ulrike A1 - Paul, Andrea T1 - Multivariate analysis of large µ-FTIR datasets in search of microplastics N2 - µ-FTIR spectroscopy is a widely used technique in microplastics research. It allows to simultaneously characterize the material of the small particles, fibers or fragments, and to specify their size distribution and shape. Modern detectors offer the possibility to perform two-dimensional imaging of the sample providing detailed information. However, datasets are often too large for manual evaluation calling for automated microplastic identification. Library search based on the comparison with known reference spectra has been proposed to solve this problem. To supplement this ‘targeted analysis’, an exploratory approach was tested. Principal component analysis (PCA) was used to drastically reduce the size of the data set while maintaining the significant information. Groups of similar spectra in the prepared data set were identified with cluster analysis. Members of different clusters could be assigned to different polymer types whereas the variation observed within a cluster gives a hint on the chemical variability of microplastics of the same type. Spectra labeled according to the respective cluster can be used for supervised learning. The obtained classification was tested on an independent data set and results were compared to the spectral library search approach. T2 - CEST 2019 CY - Rhodes, Greece DA - 04.09.2019 KW - FTIR KW - Microplastics KW - Multivariate data analysis PY - 2019 AN - OPUS4-48889 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wander, Lukas A1 - Vianello, A. A1 - Braun, Ulrike A1 - Vollertsen, J. A1 - Paul, Andrea T1 - Analyzing large μ-FTIR data sets in search of microplastics N2 - Working towards a comprehensive understanding of introduction pathways, number, and fate of micro¬plastics in the environment, suitable analytical methods are a precondition. Micro-spectroscopic methods are probably the most widely used techniques. Besides their ability to measure single spectra of a particle or fiber, most modern FTIR- and Raman microscopes are also capable of two-dimensional imaging. This is very appealing to microplastics research because it allows to simultaneously characterize the analytes chemically as well as their size (distribution) and shape. Two-dimensional imaging on extensive sample areas with FTIR-micros¬copes is facilitated by focal plane array (FPA) detectors resulting in large data sets comprised of up to several million spectra. With numbers too large for manual inspection of each individual spectrum, automated data evaluation is inevitable. Identifying different polymers based on the comparison with known reference spectra (library search) has proven to be a suitable approach. For that purpose, FTIR-spectra of common plastics can be collected to create an individual reference library. To Supplement this ‘targeted analysis’, looking for known substances via library search, an exploratory approach was tested. Principal component analysis (PCA) proved to be a helpful tool to drastically reduce the size of the data set while maintaining the significant information. Subsequently, cluster analysis was used to find groups of similar spectra. Spectra found in different clusters could be assigned to different polymer types. The variation observed within clusters gives a hint on chemical variability of microplastics of the same polymer found in the sample. Spectra labeled according to the respective cluster/polymer type were used to build a classification model which allowed to quickly predict the polymer type based on the FTIR spectrum. Classification was tested on a second, independent data set and results were compared to the spectral library search procedure. T2 - ANAKON 2019 CY - Münster, Germany DA - 25.03.2019 KW - Microplastics KW - FTIR KW - Principal component analysis (PCA) PY - 2019 AN - OPUS4-47658 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 - RPRT A1 - Altmann, Korinna A1 - Abusafia, A A1 - Bannick, C-G A1 - Braun, U A1 - Crasselt, Claudia A1 - Dittmar, S A1 - Fuchs, M A1 - Gehde, M A1 - Hagendorf, C A1 - Heller, C A1 - Herper, D A1 - Heymann, S A1 - Kerndorff, A A1 - Knefel, M A1 - Jekel, M A1 - Lelonek, M A1 - Lunkenbein, T A1 - Obermaier, N A1 - Manhart, M A1 - Meurer, Maren A1 - Miclea, P-T A1 - Paul, A A1 - Richter, S A1 - Ricking, M A1 - Rohner, C A1 - Ruhl, A A1 - Sakai, Y A1 - Saravia Arzabe, C A1 - Scheid, C A1 - Schmitt, M A1 - Schnarr, M A1 - Schwertfirm, F A1 - Steinmetz, H A1 - Wander, Lukas A1 - Wiesner, Yosri A1 - Zechmeister, L T1 - RUSEKU - Repräsentative Untersuchungsstrategien für ein integratives Systemverständnis von spezifischen Einträgen von Kunststoffen in die Umwelt : Abschlussbericht N2 - Im Verbundprojekt RUSEKU wurde die Probenahme von Wasserproben entscheidend weiterentwickelt. Wichtig ist hierbei zu gewährleisten, dass genügend Merkmalsträger in jeder Probe untersucht werden. Es muss daher eine für den Probenahmeort repräsentative Beprobung hinsichtlich des Wasservolumens in Abhängigkeit der Partikelanzahl gewährleistet sein. Das Hauptaugenmerk lag im vorliegenden Projekt auf einer praxisnahen Beprobungsstrategie. Es wurden verschiedene Konzepte ausprobiert. • Grundsätzlich hat sich gezeigt, dass eine Stichprobe eine Momentaufnahme des MP-Massengehaltes zeigt. Es wird eine hohe Statistik, also eine Vielzahl an Messungen am gleichen Probenahmeort, benötigt, um eine valide Aussage über den MP-Gehalt zu machen. • Es zeigt sich, dass eine integrale Probenahme über mehrere Wochen mit dem SK routinemäßig möglich ist. Die erfassten MP-Massen sind reproduzierbar und robust. • Die DFZ ist für Stichproben geeignet. Partikel < 50 µm werden eventuell unterschätzt • Die fraktionierte Filtration kann für Stich- und Mischproben direkt im Feld genutzt werden. Fraktionen von 10 und 5 µm werden später im Labor Vakuum filtriert. Es erfolgt eine Fraktionierung der Probe mit Siebmaschenweiten von 1000, 500, 100, 50, 10 und 5 µm. • Die fraktionierte Filtration kann auch anschließend an die Beprobung mit dem SK zur Anwendung kommen. Wird die mit dem SK gewonnene Wasserprobe fraktioniert filtriert, kann neben einem MP-Gesamtgehalt auch eine Einschätzung über die Partikelgrößen gewonnen werden. • Für Wässer mit geringen Partikelzahlen wurde ein Messfiltertiegel entwickelt. Dieser hat eine Maschenweite von 6 µm. Seine Anwendung kann mögliche Verluste beim Transferieren vom Probenahmetool zum Messgefäß und mögliche Kontaminationen reduzieren. Die Optimierung der Probenahmestrategie wurde durch Modellversuche und Simulationen unterstützt. Modellversuche zum Sinkverhalten und Simulationen von MP in realen Gewässern verdeutlichten das komplexe Verhalten der Partikel. Es konnte gezeigt werden, dass Partikel ab einer bestimmten Größe (und kleiner) bei genügend starker Turbulenz sich in der Wassersäule unabhängig von ihrer Dichte verhalten und so auch MP mit kleiner Dichte (z.B. PE) in der gesamten Wassersäule zu finden sind. Es konnte mit dem TEM die Existenz von NP gezeigt werden. Ein wesentlicher Aspekt des RUSEKU Projektes war die Beprobung realer Kompartimente. Beprobt wurde neben Oberflächengewässern, das urbane Abwassersystem der Stadt Kaiserslautern, Waschmaschinenabwasser und Flaschenwasser. • In Oberflächengewässern wurde hauptsächlich PE gefunden. Je nach Probe und Gewässer konnten auch PP, PS, PET, PA, SBR und Acrylate nachgewiesen werden. • Im urbanen Abwassersystem der Stadt Kaiserslautern konnte an allen Probenahmestandorten MP nachgewiesen werden. Es wurde hauptsächlich PE, neben geringeren Mengen an PP, PS und SBR gefunden. Nach einem Regenereignis war der SBR Anteil deutlich erhöht. • Die Beprobung eines realen Wäschepostens, bestehend aus T-Shirts und Hemden mit PA/CO oder PES/CO Mischgewebe, zeigte einen PA- und PES-Austrag im Waschwasser. Der überwiegende Teil der detektierten Fasern ist aber auf Baumwolle zurückzuführen. Reine gravimetrische Messungen zur Detektion von MP führen zu einer starken Überschätzung. • In Flaschenwasser (PET-Flaschen) konnte MP detektiert werden. PET wurde nur im stillen Mineralwasser, nicht in Mineralwasser mit Kohlensäure gefunden werden. Teilweise wurde auch das MP-Material des Verschlusses im Wasser detektiert. • Für Luftproben konnte ein Aufbau zur größenselektiven Beprobung getestet werden. Neben der Probenahme hat das Projekt auch gezeigt, dass die TED-GC/MS geeignet für die MP-Detektion im Routinebetrieb ist. Die TED-GC/MS konnte weiter optimiert werden. Es wurden MP-Massen bestimmt. Im Projekt wurden erste realitätsnahe Referenzmaterialien für die MP Detektion hergestellt. Die Herstellung von realitätsnahen Polymeren in ausreichender Homogenität und Menge hat sich als große Herausforderung herausgestellt. KW - Mikroplastik KW - Probennahme KW - TED-GC/MS KW - Fraktionierte Filtration KW - Mikroplastikreferenzmaterial PY - 2022 SP - 1 EP - 201 AN - OPUS4-57800 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Kern, Simon T1 - Innen hui und außen pfui – Smarte Prozess-Sensoren in der gegenwärtigen Automatisierungslandschaft der Prozessindustrie N2 - Der Wandel von der aktuellen Automation zum smarten Sensor ist im vollen Gange. Automatisierungstechnik, sowie die Informations- und Kommunikationstechnik (IKT) verschmelzen zunehmend. Eine Topologie für smarte Sensoren, die das Zusammenwirken mit daten- und modellbasierten Steuerungen bis hin zur Softsensorik beschreibt gibt es bis heute jedoch noch nicht. Um zu einer störungsfreien Kommunikation aller Komponenten auf Basis eines einheitlichen Protokolls zu kommen sollte die Prozessindustrie die Weichen für eine smarte und sichere Kommunikationsarchitektur stellen. Sie verwehrt stattdessen die Entwicklungen ihrer Zulieferer und wartet lieber ab. Der Beitrag greift die Anforderungen der Technologie-Roadmap „Prozess-Sensoren 4.0“ auf und zeigt Möglichkeiten zu ihrer Realisierung am Beispiel eines Online-NMR-Analysators, der im Rahmen eines EU-Projekts entwickelt wurde. T2 - 13. Dresdner Sensor Symposium CY - Dresden, Germany DA - 04.12.2017 KW - Smarte Feldgeräte KW - Process Control KW - Modulare Produktion KW - Online-NMR-Spektroskopie KW - Indirect Hard Modeling KW - Industrie 4.0 PY - 2017 UR - https://www.ama-science.org/proceedings/details/2717 SN - 978-3-9816876-5-1 U6 - https://doi.org/10.5162/13dss2017/2.1 SP - 61 EP - 66 PB - AMA Service GmbH CY - Berlin AN - OPUS4-43252 LA - deu 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 U6 - 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 - CONF A1 - Maiwald, Michael A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Zientek, Nicolai A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Kern, Simon T1 - Strangers in the Night—Smart Process Sensors in Our Current Automation Landscape 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. Smart sensors enable concepts like self-diagnostics, self-calibration, and self-configuration/parameterization whenever our current automation landscape allows it. Here we summarize the currently discussed general requirements for process sensors 4.0 and introduce a smart online NMR sensor module as example, which was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). T2 - Eurosensors 2017 Conference CY - Paris, France DA - 03.09.2017 KW - Process Monitoring KW - Smart Sensors KW - CONSENS KW - Online NMR Spectroscopy KW - Mini-plant PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-415772 UR - http://www.mdpi.com/2504-3900/1/4/628 VL - 1 SP - 628 EP - 631 PB - MDPI CY - Basel AN - OPUS4-41577 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 - TY - CONF A1 - Guhl, Svetlana A1 - Kern, Simon A1 - Meyer, Klas A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Maiwald, Michael T1 - Online NMR Spectroscopy for Process Monitoring in Intensified Continuous Production Plants N2 - Process analytical techniques are extremely useful tools for chemical production and manufacture and are of particular interest to the pharmaceutical, food and (petro-) chemical industries. 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. A major advantage of NMR spectroscopy is that the method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method which is independent of the matrix. This is an important prerequisite for robust data evaluation strategies within a control concept and reduces the need for extensive maintenance of the evaluation model over the time of operation. Additionally, NMR spectroscopy provides orthogonal, but complimentary physical information to conventional, e.g., optical spectroscopy. It increases the accessible information for technical processes, where aromatic-toaliphatic conversions or isomerizations occur and conventional methods fail due to only minor changes in functional groups. As a technically relevant example, the catalytic hydrogenation of 2-butyne-1,4-diol and further pharmaceutical reactions were studied using an online NMR sensor based on a commercially available low-field NMR spectrometer within the framework of the EU project CONSENS (Integrated Control and Sensing). T2 - 4th European Conference on Process Analytics and Control Technology (EuroPACT 2017) CY - Potsdam, Germany DA - 10.05.2017 KW - Process Monitoring KW - CONSENS KW - Online NMR Spectroscopy KW - Process Analytical Technology KW - Process control KW - Hydration KW - EuroPACT PY - 2017 SP - 103 EP - 103 CY - Frankfurt a. M. AN - OPUS4-40231 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wander, Lukas A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Bornemann-Pfeiffer, Martin A1 - Gräßer, Patrick A1 - Acker, J. A1 - Maiwald, Michael T1 - Process monitoring with online NMR spectroscopy – An enabler for “Industrie 4.0” in process industry N2 - Improvement in deep process understanding is a mandatory prerequisite for the application of modern concepts like Industrial Internet of Things (IIoT) or “Industrie 4.0”. This is particularly relevant in new process concepts such as intensified production in modularized plants. The direct hyphenation with online methods of process analytical technology (PAT) allows profound insights into the actual reactions within chemical and pharmaceutical production steps and provides necessary information for associated control strategies. While the industrial application of online Raman spectroscopy has already been successfully demonstrated, low-field NMR spectroscopy is not yet adequately developed as an online method for use in process industry. The high information content combined with the low calibration effort makes NMR spectroscopy a highly promising method for modern process automation with a high flexibility due to short set-up times and low requirements regarding validation. This is a major advantage especially within multi-purpose production plants, as well as for processes suffering from fluctuating quality of raw materials. NMR spectroscopy has a high potential for direct quantitative information, while cutting the calibration and validation needs to a minimum and thus exhibiting short set-up times. Within the EU project CONSENS, an NMR analyzer for direct implementation in an industrial process environment was developed based on a commercially available laboratory instrument. The challenge was not only the hyphenation to the production plant itself, but also to fulfill all requirements of chemical industry, e.g., explosion safety regulations (ATEX), robust automation and modern, as well as classical communication interfaces. The presented NMR module involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation. The module transforms the acquired online spectra of various technically relevant reactions to either conventional 4‒20 mA signals as well as WiFi based OPC-UA communication protocols. The concept was evaluated on two processes of pharmaceutical and chemical industry. As the first example the continuous synthesis of 2-nitrodiphenylamine starting from aniline and o-fluoronitrobenzene, activated by an organometallic lithium reagent, was studied. This application is highly demanding for a reliable automated evaluation of the obtained NMR spectra, which was realized by developing a physically motivated model-based approach. In the second example, a stage of the synthesis of the industrially important solvent tetrahydrofurane consisting of the catalytic hydrogenation of 2-butine-1,4-diol was monitored. This reaction is proceeding via an intermediate product and suffers from competitive reaction paths. In this application different spectroscopic methods were combined with the data obtained from classical process sensors, e.g., pressure, temperature and flow transducers for the development of innovative control concepts. T2 - ACHEMA CY - Frankfurt/M., Germany DA - 11.06.2018 KW - Nuclear magnetic resonance KW - Process monitoring KW - Process industry KW - Low field nmr KW - Industrie 4.0 PY - 2018 N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. AN - OPUS4-45197 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Guhl, Svetlana A1 - Kern, Simon A1 - Meyer, Klas A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Maiwald, Michael T1 - Produzieren Sie schon oder kalibrieren Sie noch? – Online-NMR-Spektrometer als Smarte Feldgeräte N2 - Der Vortrag zeigt allgemeine Anforderungen an "smarte Feldgeräte" und deren Entwicklung in den vergangenen Jahren. Am Beispiel eines smarten Online-NMR-Sensors, der in einem EU-Projekt von der BAM entwickelt wurde, wird die Umsetzung der Anforderung aufgezeigt. Schließlich werden weitere Technologieanforderungen und Lösungsansätze vorgestellt. T2 - ProcessNet-Jahrestagung und 33. DECHEMA-Jahrestagung der Biotechnologen CY - Aachen, Germany DA - 10.09.2018 KW - Prozessanalytik KW - Prozessindustrie KW - Online-NMR-Spektroskopie KW - Datenkonzepte KW - Datenanalyse KW - CONSENS PY - 2018 UR - https://onlinelibrary.wiley.com/doi/abs/10.1002/cite.201855229 U6 - https://doi.org/10.1002/cite.201855229 SN - 0009-286X N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. VL - 90 IS - 9 SP - 1236 EP - 1236 PB - Wiley-VCH Verlag GmbH & Co. KGaA CY - Weinheim AN - OPUS4-45901 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wander, Lukas A1 - Kern, Simon A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Maiwald, Michael T1 - Assessment and validation of various flow cell designs for quantitative online NMR spectroscopy N2 - Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction and process control. Robust field integration of NMR systems have to face explosion protection or integration into process control systems with short set-up times. This paves the way for industrial automation in real process environments. The design of failsafe, temperature and pressure resistant flow through cells along with their NMR-specific requirements is an essential cornerstone to enter industrial production plants and fulfill explosion safety requirements. NMR-specific requirements aim at full quantitative pre-magnetization and acquisition with maximum sensitivity while reducing sample transfer times and dwell-times. All parameters are individually dependent on the applied NMR instrument. Luckily, an increasing number of applications are reported together with an increasing variety of commercial equipment. However, these contributions have to be reviewed thoroughly. The performance of sample flow cells commonly used in online analytics and especially for low-field NMR spectroscopy was experimentally and theoretically investigated by 1H-NMR experiments and numerical simulations. Here, we demonstrate and discuss an automated test method to determine the critical parameters of flow through cells for quantitative online NMR spectroscopy. The setup is based on randomized setpoints of flow rates in order to reduce temperature related effects. Five flow cells and tubings were assessed and compared for high-field as well as low-field NMR spectrometers. T2 - Small Molecule NMR Conference (SMASH) CY - Baveno, Italy DA - 17.09.2017 KW - Online NMR spectroscopy KW - Reaction monitoring KW - Flow cell KW - Process control KW - SMASH PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-419485 UR - http://www.smashnmr.org/conference/program AN - OPUS4-41948 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 - Wander, Lukas A1 - Paul, Andrea A1 - Becker, Roland A1 - Maiwald, Michael A1 - Braun, Ulrike T1 - Speeding up microplastics analysis with modern NIR spectroscopy N2 - Annually vast amounts of plastics are produced world-wide. However, recycling and waste management is still insufficient resulting in large quantities of plastics being released into the environment. Degradation by sunlight, mechanical and biological factors lead to the breakdown of this waste into little fragments. By convention particles smaller than 5 mm are referred to as microplastics (MP). The occurrence of MP has been reported by researchers virtually all around the globe. Gaining knowledge on MP is currently a time-consuming process because analysis mainly relies on micro-infrared and micro-Raman methods. Prior to that the particles need to undergo purification and enrichment. Thus, only small numbers and volumes of samples can be investigated. Here we tested NIR spectroscopy combined with a multivariate data analysis as a means of speeding up the process of MP analysis. Experiments were performed using the most abundant polymers polyethylene, polypropylene, polyethylene terephthalate and polystyrene. MP samples were obtained by adding the cryomilled and sieved (<125 µm) particles to approximately 1 g of standard soil at 0,5–10 mass%. Spectra were recorded with a fiber optic reflection probe connected to a FT-NIR spectrometer. 5–10 spectra recorded of each sample were used for the calibration of chemometric models (partial least squares regression, PLSR). “Unknown” test samples were then used to test the model’s capability to predict the type and amount of polymer. In samples containing 1–5 % of the polymers the prediction yielded the highest degree of agreement with the gravimetric reference values. At low polymer loads some false positive results in the identification were observed. Large amounts of polymers limited the prediction capability by a nonlinear behaviour of the absorption. Further testing was done with real world samples such as compost and washing machine filters. Even though the calibration did not account for these highly complex sample compositions, satisfactory results could be achieved. T2 - Adlershofer Forschungsforum CY - Berlin, Germany DA - 10.11.2017 KW - NIR spectroscopy KW - Microplastics KW - Mikroplastik KW - Chemometrics PY - 2017 AN - OPUS4-42916 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wander, Lukas 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 using NMR instruments, in particular, after acquisition of the FID the data needs to be corrected in real-time for common effects using automated methods. When it comes to NMR data evaluation under industrial process conditions, the shape of signals can change drastically due to nonlinear effects. However, the structural and quantitative information is still present but needs to be extracted by applying predictive models. Acquired raw spectra were processed with the following tools: · Phase correction using the Entropy minimization method · Baseline correction using a low-order Polynomial fit · Alignment (icoshift) Pure component models based on Pseudo-Voigt functions can be derived via peak fitting of measured pure components or by the use of spin calculations. T2 - Tackling the Future of Plant Operation - Jointly towards a Digital Process Industry CY - Barcelona, Spain DA - 13.12.2017 KW - Process Monitoring KW - Online NMR Spectroscopy KW - Indirect Hard Modeling KW - Spectral Modeling KW - Process Analytical Technology KW - CONSENS PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-434346 AN - OPUS4-43434 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kern, Simon A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Müller, S. A1 - Maiwald, Michael A1 - Kowarik, Stefan T1 - Artificial neural networks for quantitative online NMR spectroscopy N2 - Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data. KW - Online NMR spectroscopy KW - Real-time process monitoring KW - Artificial neural networks KW - Automation KW - Process industry PY - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-507508 SN - 1618-2642 VL - 412 IS - 18 SP - 4447 EP - 4459 PB - Springer CY - Berlin AN - OPUS4-50750 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 - 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 - Wander, Lukas A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Maiwald, Michael T1 - Keramikdurchflusszellen für das industrielle Reaktionsmonitoring mit Niederfeld-NMR-Spektroskopie N2 - Derzeit verfügbare Niederfeld-NMR-Spektrometer sind oft für Laborapplikationen konzipiert. Für den Einsatz im industriellen Prozessmonitoring müssen deshalb Anpassungen vorgenommen werden. Ein wichtiger Aspekt ist die Gestaltung der Messzelle. Sie muss über eine hohe thermische-, chemische und vor allem mechanische Beständigkeit verfügen. Hinzu kommt die Besonderheit des NMR-Experiments, das auf die Durchlässigkeit von Radiofrequenzen angewiesen ist. Keramik ist ein in der Hochfeld-NMR-Spektroskopie bewährtes Material das diese Eigenschaften vereint. Um im Prozessmonitoring die Interessen kleiner Bypass-Volumina, großer Durchflussgeschwindigkeit und großes Signal-zu-Rausch-Verhältnis mit der nötigen Vormagnetisierungszeit in Einklang zu bringen, ist eine im Messbereich aufgeweitete Zellgeometrie vorteilhaft. Die Fertigung einer Keramikmesszelle für die Niederfeld-NMR-Spektroskopie für Drücke bis 7 MPa mit dieser besonderen Geometrie wurde mit Hilfe eines modernen additiven Fertigungsverfahrens realisiert. Quantitative NMR-Messungen an konstant durch das Spektrometer strömenden Flüssigkeiten werden durch eine maximale Durchflussgeschwindigkeit limitiert. Diese wird von vielen Einflussgrößen bestimmt und sollte vor jeder quantitativen Messreihe experimentell für das individuelle System ermittelt werden. Zu diesem Zweck wurde eine automatisierte Laboranordnung konzipiert. Der Vergleich der neuen NMR-Keramikzelle mit bestehenden Messzellen u. a. anhand dieses Parameters untermauert ihre Eignung für das industrielle Prozessmonitoring. T2 - 13. Herbstkolloquium Arbeitskreis Prozessanalytik CY - Esslingen, Germany DA - 20.11.2017 KW - Keramikdurchflusszelle KW - Niederfeld-NMR KW - Online-NMR PY - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-430918 AN - OPUS4-43091 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wander, Lukas A1 - Braun, Ulrike A1 - Becker, Roland A1 - Maiwald, Michael A1 - Paul, Andrea T1 - Mikroplastikanalyse: Nahinfrarotspektroskopie und chemometrische Auswertung N2 - Für die Erfassung der Verbreitung von Mikroplastik (MP) in der Umwelt ist die zeit- und kostenaufwendige Analysestrategie und der damit verbundene geringe Probendurchsatz eine limitierende Größe. Eine große Zahl verschiedener Studien dokumentriet das Auftreten von MP über den gesamten Globus. Meist sind die Studien aufgrund des großen analytischen Aufwands auf exemplarische, stichpunktartige Untersuchungen kleiner Umweltaliquoten und zahlenmäßig kleiner Probenumfänge begrenzt. Um die Verbreitung, die Eintragspfade und den Verbleib von MP in der Umwelt besser zu verstehen und effektive Vermeidungsstrategien abzuleiten, ist es jedoch notwendig, analytisch mehr Proben erfassen zu können. Bildgebende mikro-spektroskopische Methoden wie das Raman- und FTIR-Imaging ermöglichen eine zeitaufwendige, umfassende Charakterisierung kleiner Umweltaliquoten. Neben der Partikelanzahl sind zusätzlich Informationen zu Partikelgröße, Größenverteilung und Oberflächenmorphologie zugänglich. Chemische und thermische Extraktionsverfahren sind bereits deutlich schneller und können diese Informationen durch eine Massenbilanz vervollständigen. Die analysierbare Probenmenge ist jedoch auf Milligramm Mengen beschränkt. Wir schlagen daher vor, die Analyse von Proben auf MP durch ein vorangestelltes Screening mit der Nahinfrarot-Spektroskopie (NIRS) zur komplementieren. In diesem wird bereits eine erste Einschätzung über die Präsenz von MP in einer Probe gefällt und dadurch die wertvolle Messzeit anderer Methoden effizienter genutzt. NIR zur Analyse von Polymeren wird seit langem eingesetzt, jedoch bisher lediglich im Rahmen einer Studie zur Mikroplastikuntersuchung mittels Hyperspektraler Bildgebung beschrieben. Der NIR Spektralbereich findet sich zwischen dem sichtbaren Licht und dem mittleren Infrarot (MIR). MIR Spektren sind durch klar definierte Banden charakterisiert, welche mehrheitlich von den Grundschwingungen der Moleküle stammen. Die höheren Energien im nahen Infrarot regen hingegen Kombinations- und Oberschwingungen der Streck und Biegeschwingungen an. Die resultierenden Absorptionsbanden sind oft breit und relativ unspezifisch. Erst mit Hilfe einer computergestützten Datenauswertung lassen sich aus diesen Spektren nützliche Informationen gewinnen. Dies erklärt die steigende Popularität der NIR-Spektroskopie in der jüngeren Vergangenheit mit einem Schwerpunkt als prozessanalytische Methode. NIR Spektrometer für das industrielle Prozessmonitoring zeichnen sich durch eine kompakte und robuste Konstruktionsweise aus. Die verfügbaren faseroptischen Reflexionssonden eignen sich gut um pulverförmige Proben zu untersuchen. Der räumlich erfassbare Messbereich kann durch die Sondengeometrie variiert werden. Sind die untersuchten Partikel im Verhältnis zur abgetasteten Fläche klein, wird als spektrale Information die Summe der Absorption aller Partikel im Sichtfeld erfasst. Die Methode ist deshalb nicht für Detailuntersuchungen von MP geeignet, erlaubt es jedoch innerhalb weniger Minuten eine Einschätzung über das Vorkommen von Mikroplastik in einer Probe zu treffen. Exemplarisch wurden für diese Untersuchungen vier der am weitesten verbreiteten Kunststoffe Polyethylen (PE), Polyethylenterephthalat (PET), Polypropylen (PP) und Polystyrol (PS) gewählt. Aus den additivfreien Polymeren wurden nach einer Kryo-vermahlung und anschließender Siebung (< 125 µm) Modellproben generiert. Die Polymere wurden dafür zu einem Massenanteil von 1 % mit einem Standardboden (LUFA2.3, gesiebt < 125 µm) vermischt. Die Gesamtmenge von 1 g je Probe wurde in Aluminiumbehältern präpariert und 8 Messungen an unterschiedlichen, zufällig gewählten Positionen vorgenommen. Die erhaltenen Spektren wurden zur Kalibrierung chemometrischer Modelle genutzt. In einem hierarchischen Ansatz wurde anhand der NIR-Spektren eine Klassifizierung vorgenommen: 1. Bestimmung ob eine Probe MP enthält (Ja/Nein). 2. Identifikation der Polymere in der Probe. Eine aussagekräftige Klassifizierung beruht auf einer Vorbehandlung der Spektren. Hierdurch werden die Unterschiede zwischen den einzelnen Polymerbanden hervorgehoben. Die Eignung der so erstellten Modelle wurde anhand eines Referenzmaterials und am Beispiel von Realproben erfolgreich getestet. Dabei zeigte sich, dass nicht nur in den erstellten Polymer-Bodenmischungen, sondern auch in den Rückständen von fermentiertem Bioabfall und in Filterrückständen einer Waschmaschine, MP richtig erkannt wurde. Weiterhin zeigten Tests mit Mikroplastik-freien Bodenproben unterschiedlicher Herkunft, dass keine falsch-positive Resultate erzeugt wurden. Alle vier untersuchten Polymere, d.h. PE, PET, PS und PP mit einem Massenanteil von 1 % in einer Bodenmatrix werden auch bei einer gemischten Polymerzusammensetzung mit der NIR-Spektroskopie erkannt. Der kombinierte Einsatz von NIRS und Chemometrie ermöglicht die Entscheidung über ein potenzielles Vorkommen sowie die Zuordnung des Materials der enthaltenen Polymerpartikel für eine Massefraktion ≥ 1 % in einer (trockenen) Probenmenge von 1 g innerhalb von 10–15 min. Der zeitaufwendige Schritt der Methode liegt hier in der Erstellung geeigneter chemometrischer Modelle sowie deren Validierung. Wesentliche Voraussetzung ist dabei, dass bei der Kalibrierung die Varianz der zu erwartenden Partikel und der Matrix realistisch abgebildet wird. T2 - GDCh Jahrestagung der Wasserchemischen Gesellschaft CY - Papenburg, Ems, Germany DA - 07.05.2018 KW - Mikroplastik KW - Nahinfrarotspektroskopie KW - Chemometrie KW - Boden PY - 2018 AN - OPUS4-44887 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wander, Lukas A1 - Kern, Simon A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Reddy Gottu Mukkula, A. 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 - NMR-Spektroskopie als Online-Referenzmethode in der Prozessindustrie N2 - In der Prozessindustrie findet die optische Spektroskopie (z. B. NIR- und Raman-Spektroskopie) als Online-Analytik zunehmend Anwendung zur Überwachung che-mischer Qualitäts¬attribute in der Produktion. Ihr ganzes Potential entfalten die Methoden aber meist nur in Kombination mit einer aufwendigen, multivariaten Kalibrierung. Diese muss alle relevanten Zustände des Systems abdecken und bedarf einer geeigneten Referenz¬analytik. Moderne instrumentelle Analysengeräte weisen eine hohe Empfind¬lich¬keit und Robustheit auf, sind aber dennoch stark von Fehler und Variabilität der Probennahme beeinflusst, was sich auf die Richtigkeit und Qualität des multivariaten Modells auswirkt. Diese Probleme lassen sich verringern, indem die Referenzanalytik ebenfalls online erfolgt. Eine mögliche Lösung stellt die hochauflösende NMR-Spektroskopie als quanti¬tative Online-Referenzanalytik dar. Insbesondere kom¬pakte NMR-Spektrometer auf Basis von Permanent¬magneten sind für diesen Zweck geeignet. Ausschlusskriterien für herkömmlicher NMR-Systeme, wie der große Wartungs-aufwand (Kryotechnik) und der Platz¬bedarf, werden damit vermieden. Im Rahmen des EU-Projekts CONSENS wurde die Nutzung einer Online-Referenz¬analytik mit NMR-Spektroskopie am Beispiel einer industriellen Pilotanlage erfolgreich realisiert. Untersuchungsgegenstand war die kontinuierliche Synthese eines Aus¬gangsstoffs für die pharmazeutische Industrie. Die enthaltenen metallorganischen Verbindungen sind für die bisher genutzte HPLC Analytik unzu-gänglich und die Analyse ausgewählter Proben erfolgte nach dem Quenchen der Lösung oft mit einem großen zeitlichen Abstand zur Probennahme. Konzen-trationswerte auf Basis von Online-NMR-Spektren standen hingegen mit einer zeitlichen Auflösung von drei Spektren pro Minute über den gesamten Reaktionsverlauf hinweg zur Verfügung. Außerdem konnten durch die NMR-Spektroskopie intermediär auftretende Spezies erstmal quantitativ bestimmt und diese Daten für die Kalibrierung eines NIR-Spektrometers genutzt werden. T2 - ANAKON 2019 CY - Münster, Germany DA - 25.03.2019 KW - NMR-Spektroskopie KW - Prozessanalytik KW - Online-Referenzmethode PY - 2019 AN - OPUS4-47659 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wander, Lukas A1 - Kern, Simon A1 - Meyer, Klas A1 - Bornemann-Pfeiffer, Martin A1 - Guhl, Svetlana A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Prozess-Spektroskopie: Analytik für die kontinuierliche Produktion N2 - Der Vortrag zeigt aktuelle Entwicklungen und Betätigungsfelder des Fachbereichs Prozessanalytik zum Thema Automation in der Analytik. Dies Umfasst die Laborautomation am Beispiel der Probenpräparation für die Röntgenfluoreszenzanalyse und moderne Synthesekonzepte in der organischen Chemie. Außerdem wird die Rolle der Prozessanalytik in der kontinuierlichen Produktion thematisier. Als Anschauungsgegenstand dienen die Überwachung einer Hydroformylierung mittels Raman- und NMR-Spektroskopie und der Einsatz eines NMR-Sensors in einer modularen Produktionsanlage im Pilotmaßstab. T2 - 4. Analytiktag CY - Duisburg, Germany DA - 07.11.2019 KW - NMR-Spektroskopie KW - Raman-Spektroskopie PY - 2019 N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. AN - OPUS4-49579 LA - mul 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 -