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 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-546405 DO - https://doi.org/10.1088/1361-6501/ac5e5f 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 - 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 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-552605 DO - https://doi.org/10.1088/1361-6501/ac5e5f 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 - 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 - 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 DO - 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 - 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 DO - 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 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 UR - https://nbn-resolving.org/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 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 - 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 DO - 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 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 - 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 DO - 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 -