TY - CONF A1 - Meyer, Klas A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Bornemann-Pfeiffer, Martin A1 - Wander, Lukas A1 - Maiwald, Michael T1 - Compact NMR Spectroscopy: A Versatile Tool for Automated Continuous-Flow Production of Chemicals and Pharmaceuticals N2 - Chemical companies must find new paths to successfully survive in a changing environment. The potential of digital technologies belongs to these. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds. Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. The advances of a fully automated NMR sensor were exploited, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as, e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. NMR appeared as preeminent online analytical tool and allowed using a modular data analysis tool, which even served as reliable reference method for further PAT applications. In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals. T2 - USP qNMR Emerging Technologies Workshop & Roundtable CY - Online meeting DA - 17.11.2020 KW - Quantitative NMR spectroscopy KW - Benchtop-NMR KW - Process Analytical Technology PY - 2020 AN - OPUS4-51595 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 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 - Fricke, F. A1 - Mahmood, S. A1 - Hoffmann, J. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Meyer, Klas A1 - Kowarik, S. A1 - Westerdick, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. T2 - 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) CY - Grenoble, France DA - 01.02.2021 KW - Industry 4.0, KW - Cyber-physical systems KW - Artificial neural networks KW - Mass spectrometry KW - Nuclear magnetic resonance spectroscopy PY - 2021 DO - https://doi.org/10.23919/DATE51398.2021.9473958 SP - 615 EP - 620 PB - IEEE AN - OPUS4-55360 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Meyer, Klas T1 - Flexible Prozessanalytik für die pharmazeutische Produktion - Benchtop-NMR-Spektroskopie im industriellen Einsatz N2 - Im Rahmen des EU-Projekts „CONSENS – Integrated Control and Sensing“ wurde ein vollautomatisiertes, gemäß Atmosphère-Explosibles(ATEX)-Regeln zertifiziertes Analysatormodul auf Basis eines kommerziellen Benchtop-Kernspinresonanzspektrometers (Engl. nuclear magnetic resonance, NMR) entwickelt und im Umfeld einer modularen containerbasierten Produktionsanlage validiert. Auf Basis der gewonnenen Daten konnten sowohl eine iterative Optimierung der Prozessparameter erfolgen als auch Referenzdaten für die Kalibrierung eines Nahinfrarot-Spektrometers gewonnen werden. KW - Prozessanalytik KW - NMR-Spektroskopie KW - Modulare Produktion KW - Kalibriertransfer PY - 2022 VL - 12 IS - 3 SP - 122 EP - 129 PB - Editio Cantor Verlag CY - Aulendorf AN - OPUS4-55402 LA - deu 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 - INPR A1 - Tchipilov, Teodor A1 - Meyer, Klas A1 - Weller, Michael G. T1 - Quantitative 1H nuclear magnetic resonance (qNMR) of aromatic amino acids for protein quantification N2 - qNMR is a valuable technique for metrological studies due to the uniformity of its signal response for all chemical species of an isotope of interest, which enables compound-independent calibration. However, protein quantification remained challenging as large molecules produce wide, low-intensity signals that reduce the already low sensitivity. Combining qNMR with the hydrolysis of protein samples into amino acids circumvents many of these issues and facilitates the use of NMR spectroscopy for absolute protein and peptide quantification.In this work, different conditions have been tested for quantifying aromatic amino acids and proteins. First, we examined the pH-based signal shifts in the aromatic region. The preferable pH depends on the selection of the amino acids for quantification and which internal standard substance should be used to avoid peak overlap. Several aromatic compounds, such as terephthalic acid, sulfoisophthalic acid, and benzene tricarboxylic acid, have been applied as internal standards. The quantification of amino acids from an amino acid standard, as well as from a certified reference material (bovine serum albumin), was performed. Using the first two suggested internal standards, recovery was ~ 97 % for histidine, phenylalanine, and tyrosine at a concentration of approximately 1 mM in solution. Acidic hydrolysis of a certified reference material (CRM) of bovine serum albumin (BSA) and subsequent quantification of Phe and Tyr yielded recoveries of 98 ± 2 and 88 ± 4 %, respectively, at a protein concentration of 16 g/L or 250 µM. KW - Amino acid analysis KW - AAA KW - Protein hydrolysis KW - Metrology KW - Traceability KW - Reference materials KW - Internal standards KW - Calibration PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-564520 DO - https://doi.org/10.20944/preprints202211.0569.v1 SP - 1 EP - 13 PB - MDPI CY - Basel AN - OPUS4-56452 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Bornemann-Pfeiffer, Martin A1 - Kern, S. A1 - Guhl, Svetlana A1 - Wander, Lukas A1 - Maiwald, Michael T1 - Compact NMR Spectroscopy in the field: A Versatile Tool for Automated Continuous- Flow Production N2 - Chemical companies must find new paths to successfully survive in a changing environment. The potential of digital technologies belongs to these. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds. Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as, e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals. T2 - 9th Annual Practical Applications of NMR in Industry Conference (PANIC) CY - Nashville, Tennessee, USA DA - 17.10.2021 KW - Process Analytical Technology KW - Benchtop-NMR KW - NMR spectroscopy PY - 2021 AN - OPUS4-53585 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Meyer, Klas T1 - Laboratory accreditation as a reliable indicator of technical competence for testing, calibration and measurement organizations – An introduction to ISO/IEC 17025 using the example of qNMR spectroscopy N2 - ISO/IEC 17025 is the worldwide quality standard for testing and calibration laboratories. It is the basis for accreditation by an accreditation body. The current version was published in 2018. Implementing ISO/IEC 17025 as part of laboratory quality initiatives offers both laboratory and business benefits, such as expanding the potential customer base for testing and/or calibration, increasing the reputation and image of the laboratory at national and international level, continuous improvement of the data quality and the effectiveness of the laboratory or creation of a good basis for most other quality systems in the laboratory sector, such as GxP. The main difference between a proper approach to analysis and a formal accreditation is shown in a targeted documentation, especially on the qualification of the personnel, the test equipment and the validation of the analytical methods. Using quantitative NMR spectroscopy as an example, it is shown how accreditation can be carried out and what documentation is required. In our case, we have described the procedure in an SOP ("Determination of the quantitative composition of simple mixtures of structurally known compounds with 1H-NMR spectroscopy") and supported it with a modular system of organizational and equipment SOPs. The special feature is that the accredited method is independent for the choice of the analyte and the matrix and therefore it is possible to operate with a single validated method. In our case, we have proposed three quality levels ("leagues") with different levels of analytical effort, which differ in their measurement uncertainty, in order to simplify the workflow and analysis design. T2 - 9th Annual Practical Applications of NMR in Industry Conference (PANIC) CY - Online meeting DA - 17.10.2021 KW - Quantitative NMR Spectroscopy KW - qNMR KW - Accreditation KW - ISO 17025 KW - ISO/IEC 17025 KW - PANIC PY - 2021 AN - OPUS4-53564 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Fricke, F. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Meyer, Klas A1 - Kowarik, Stefan A1 - Hierzegger, R. A1 - Westerdick, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy Using a Novel Data Augmentation Method N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are valuable analytical and quality control methods for most industrial chemical processes as they provide information on the concentrations of individual compounds and by-products. These processes are traditionally carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been realized to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra, to train an ANN with better prediction performance and speed than state-of-the-art analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. KW - Industry 4.0 KW - Cyber-Physical Systems KW - Artificial Neural Networks KW - Mass Spectrometry KW - Nuclear Magnetic Resonance Spectroscopy KW - Modular Production PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-539412 UR - https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9638378 DO - https://doi.org/10.1109/TETC.2021.3131371 SN - 2168-6750 VL - 10 IS - 1 SP - 87 EP - 98 PB - IEEE AN - OPUS4-53941 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Kern, S. A1 - Guhl, Svetlana A1 - Bornemann-Pfeiffer, Martin A1 - Wander, L. A1 - Kowarik, S. A1 - Liehr, S. A1 - Maiwald, Michael T1 - Modular process control with compact NMR spectroscopy - From field integration to automated data analysis N2 - Chemical companies must find new paths to stay productive in a rapidly changing environment. One of these is the potential of digital technologies. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market. Process safety is improved due to smaller amounts processed and the abilities of efficient heat-transfer allow for otherwise difficult-to-produce compounds. To exploit these advantages, a fully automated process control along with real-time quality control is mandatory and should be based on “chemical” information. The advances of a fully automated NMR analyzer were demonstrated, using a given pharmaceutical reaction step operated within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated to the requirements of an automated chemical production environment such as explosion safety, field communication, and robust data evaluation. Obtained results were used for direct loop advanced process control and real-time optimization of the process. NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further PAT applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated.Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals. T2 - 5th European Conference on Process Analytics and Control Technology (EuroPACT) CY - Online meeting DA - 15.11.2021 KW - NMR spectroscopy KW - Benchtop-NMR KW - Modular production KW - Process Analytical Technology PY - 2021 AN - OPUS4-53776 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Abele, M. A1 - Falkenstein, S. A1 - Friedrich, Y. A1 - Kern, Simon A1 - Korth, K. A1 - Maiwald, Michael T1 - Industrial Applications of Low-Field NMR Spectroscopy for Process and Quality Control of Silanes N2 - The combination of different silanes as starting materials and as a product of hydrolysis by several alcohols or water creates a range of hundreds of technical products for a wide range of applications. In recent years, functional trialkoxysilanes have proven to be multi-purpose organosilanes. Applications range from weather protection of buildings to bonding-imparting properties in the glass fiber industry, for sealants and adhesives, for coatings and paints to the modification of polymer materials. Commercial benchtop NMR spectrometers have the potential to be used in silane chemistry as an online method for reaction monitoring and quality control [1]. Interesting NMR nuclei for the above-mentioned products are 1H and 29Si. In a joint research cooperation between EVONIK and BAM, the applicability of low-field NMR spectroscopy for the chemical analysis of silanes was evaluated based on various case studies. In the course of the case studies it was shown how low-field NMR spectroscopy extends the application range of chemical analysis to new applications where existing technologies such as NIR, Raman, UV/VIS, etc. cannot be used quantitatively due to lack of reference data. T2 - 5th European Conference on Process Analytics and Control Technology (EuroPACT) CY - Online meeting DA - 15.11.2021 KW - NMR spectroscopy KW - Benchtop-NMR KW - Silanes KW - Quality Control PY - 2021 AN - OPUS4-53777 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Westwood, S. A1 - Martos, G. A1 - Josephs, R. A1 - Choteau, T. A1 - Wielgosz, R. A1 - Davies, S. A1 - Moawad, M. A1 - Tarrant, G. A1 - Chan, B. A1 - Alamgir, M. A1 - de Rego, E. A1 - Wollinger, W. A1 - Garrido, B. A1 - Fernandes, J. A1 - de Sena, R. A1 - Oliveira, R. A1 - Melanson, J. A1 - Bates, J. A1 - Mai Le, P. A1 - Meija, J. A1 - Quan, C. A1 - Huang, T. A1 - Zhang, W. A1 - Ma, R. A1 - Zhang, S. A1 - Hao, Y. A1 - He, Y. A1 - Song, S. A1 - Wang, H. A1 - Su, F. A1 - Zhang, T. A1 - Li, H. A1 - Lam, W. A1 - Wong, W. A1 - Fung, W. A1 - Philipp, Rosemarie A1 - Dorgerloh, Ute A1 - Meyer, Klas A1 - Piechotta, Christian A1 - Riedel, Juliane A1 - Westphalen, Tanja A1 - Giannikopoulou, P. A1 - Alexopoulos, Ch. A1 - Kakoulides, E. A1 - Kitamaki, Y. A1 - Yamazaki, T. A1 - Shimizu, Y. A1 - Kuroe, M. A1 - Numata, M. A1 - Pérez-Castorena, A. A1 - Balderas-Escamilla, M. A1 - Garcia-Escalante, J. A1 - Krylov, A. A1 - Mikheeva, A. A1 - Beliakov, M. A1 - Palagina, M. A1 - Tkachenko, I. A1 - Spirin, S. A1 - Smirnov, V. A1 - Tang Lin, T. A1 - Pui Sze, C. A1 - Juan, W. A1 - Lingkai, W. A1 - Ting, L. A1 - Quinde, L. A1 - Yizhao, C. A1 - Lay Peng, S. A1 - Fernandes-Whaley, M. A1 - Prevoo-Franzsen, D. A1 - Quinn, L. A1 - Nhlapo, N. A1 - Mkhize, D. A1 - Marajh, D. A1 - Chamane, S. A1 - Ahn, S. A1 - Choi, K. A1 - Lee, S. A1 - Han, J. A1 - Baek, S. A1 - Kim, B. A1 - Marbumrung, S. A1 - Jongmesuk, P. A1 - Shearman, K. A1 - Boonyakong, C. A1 - Bilsel, M. A1 - Gündüz, S. A1 - Ün, I. A1 - Yilmaz, H. A1 - Bilsel, G. A1 - Gökçen, T. A1 - Clarkson, C. A1 - Warren, J. A1 - Achtar, E. T1 - Mass fraction assignment of Bisphenol-A high purity material N2 - The CCQM-K148.a comparison was coordinated by the BIPM on behalf of the CCQM Organic Analysis Working Group for NMIs and DIs which provide measurement services in organic analysis under the CIPM MRA. It was undertaken as a "Track A" comparison within the OAWG strategic plan. CCQM-K148.a demonstrates capabilities for assigning the mass fraction content of a solid organic compound having moderate molecular complexity, where the compound has a molar mass in the range (75 - 500) g/mol and is non-polar (pKow < −2), when present as the primary organic component in a neat organic solid and where the mass fraction content of the primary component in the material is in excess of 950 mg/g. Participants were required to report the mass fraction of Bisphenol A present in one supplied unit of the comparison material. Participants using a mass balance method for the assignment were also required to report their assignments of the impurity components present in the material. Methods used by the seventeen participating NMIs or DIs were predominantly based on either stand-alone mass balance (summation of impurities) or qNMR approaches, or the combination of data obtained using both methods. The results obtained using thermal methods based on freezing-point depression methods were also reported by a limited number of participants. There was excellent agreement between assignments obtained using all three approaches to assign the BPA content. The assignment of the values for the mass fraction content of BPA consistent with the KCRV was achieved by most of the comparison participants with an associated relative standard uncertainty in the assigned value in the range (0.1 - 0.5)%. KW - Bisphenol-A KW - Purity assessment KW - Interlaboratory key comparison KW - Metrology PY - 2021 DO - https://doi.org/10.1088/0026-1394/58/1A/08015 VL - 58 IS - 1A SP - 08015 PB - IOP Publishing AN - OPUS4-54188 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Fricke, F. A1 - Meyer, Klas A1 - Mahmood, S. A1 - Hoffmann, J. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Kowarik, Stefan A1 - Westerdick, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. T2 - 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) CY - Online meeting DA - 01.02.2021 KW - Industry 4.0 KW - Cyber-Physical Systems KW - Artificial Neural Networks KW - Mass Spectrometry KW - Nuclear Magnetic Resonance Spectroscopy PY - 2021 UR - www.date-conference.com AN - OPUS4-52181 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Abele, M. A1 - Falkenstein, S. A1 - Friedrich, Y. A1 - Kern, S. A1 - Korth, K. A1 - Maiwald, Michael T1 - Industrielle Anwendungen der Niederfeld-NMR-Spektroskopie für die Qualitätskontrolle von Silanen N2 - Aus der Kombination verschiedener Silane als Ausgangsstoffe und als Produkt der Hydrolyse durch eine Reihe von Alkoholen oder Wasser ergibt sich eine Palette von hunderten technischen Produkten für verschiedenste Anwendungen. Funktionelle Trialkoxysilane haben sich in den vergangenen Jahren als vielseitig einsetzbare Organosilane erwiesen. Die Einsatzgebiete erstrecken sich vom Witterungsschutz von Bauwerken über haftvermittelnde Eigenschaften in der Glasfaserindustrie, bei Dicht- und Klebstoffen, in Farben und Lacken bis hin zur Modifizierung von polymeren Werkstoffen. Kommerzielle Benchtop-NMR-Spektrometer haben das Potential auch im Bereich der Silanchemie als Online-Methode zur Reaktionsüberwachung und für die Qualitätskontrolle eingesetzt zu werden. Interessante NMR-Kerne für die oben genanntem Produkte sind 1H und 29Si. In einer gemeinsamen Forschungskooperation zwischen EVONIK und BAM wurde anhand verschiedener Fallstudien die Anwendbarkeit der Niederfeld-NMR-Spektroskopie zur chemischen Analyse von Silanen evaluiert. Die Möglichkeiten der Konzentrationsbestimmung erweitern die Anwendungsgebiete, in denen bestehende Technologien wie z. B. NIR, Raman, UV/VIS, etc. mangels Referenzdaten nicht quantitativ eingesetzt werden können. Eine Fallstudie setzte dazu an, den Hydrolyse- und Kondensationsverlauf mit geeigneter Online-NMR-Analytik zu beobachten, den Reaktionsfortschritt der Hydrolyse und Kondensation auf dieser Basis besser zu verstehen und zu optimieren. Zu diesem Zweck werden durch Zugabe von Wasser zunächst die Alkoxysubstituenten eines Trialkoxysilans hydrolysiert und entsprechende Silanole gebildet. Diese können dann über eine SiOH-Funktion an den zu modifizierenden Werkstoff anbinden und über weitere Silanolgruppen unter Ausbildung von Siloxaneinheiten vernetzen. In einer weiteren Fallstudie wurde die Kinetik der Aufspaltungen einer cyclischen Silanverbindung untersucht. Die Online-NMR-Analytik kam hierbei sowohl im Labor als auch in der industriellen Produktionsanlage zum Einsatz. Hierfür wurde eine automatisierte Einhausung verwendet, welche den Einsatz eines kommerziellen NMR-Spektrometers in explosionsgeschützten Bereichen ermöglicht. T2 - Praktische Probleme der Kernresonanzspektroskopie CY - Online meeting DA - 16.03.2021 KW - NMR-Spektroskopie KW - Benchtop-NMR KW - Silane KW - Prozessanalytik PY - 2021 AN - OPUS4-52298 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Fricke, F. A1 - Mahmood, S. A1 - Hoffmann, J. A1 - Brandalero, M. A1 - Liehr, Sascha A1 - Kern, Simon A1 - Meyer, Klas A1 - Kowarik, Stefan A1 - Westerdicky, S. A1 - Maiwald, Michael A1 - Hübner, M. T1 - Artificial Intelligence for Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy N2 - Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control. T2 - 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) CY - Online meeting DA - 01.02.2021 KW - Industry 4.0 KW - Cyber-Physical Systems KW - Artificial Neural Networks KW - Mass Spectrometry KW - Nuclear Magnetic Resonance Spectroscopy PY - 2021 UR - www.date-conference.com SN - 978-3-9819263-5-4 SP - 615 EP - 620 PB - Research Publishing AN - OPUS4-52180 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kern, Simon A1 - Wander, Lukas A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gottu Mukkula, A. R. A1 - Holtkamp, M. A1 - Salge, M. A1 - Fleischer, C. A1 - Weber, N. A1 - Engell, S. A1 - Paul, Andrea A1 - Pereira Remelhe, M. A1 - Maiwald, Michael T1 - Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals N2 - Modular plants using intensified continuous processes represent an appealing concept for the production of pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes; besides, it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and is based on a compact nuclear magnetic resonance (NMR) spectrometer. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including robust evaluation of sensor data. Beyond monitoring the product quality, online NMR data was used in a new iterative optimization approach to maximize the plant profit and served as a reliable reference for the calibration of a near-infrared (NIR) spectrometer. The overall approach was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance. KW - NMR Spectroscopy KW - NIR Spectroscopy KW - Real-time process monitoring KW - Real-time quality control KW - Continuous processes KW - CONSENS KW - Data Fusion PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-480623 DO - https://doi.org/10.1007/s00216-019-01752-y SN - 1618-2642 SN - 1618-2650 VL - 411 IS - 14 SP - 3037 EP - 3046 PB - Springer Nature CY - Heidelberg AN - OPUS4-48062 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kern, Simon A1 - Wander, Lukas A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Gottu Mukkula, A. R. A1 - Holtkamp, M. A1 - Salge, M. A1 - Fleischer, C. A1 - Weber, N. A1 - Engell, S. A1 - Paul, Andrea A1 - King, R. A1 - Maiwald, Michael T1 - Raw data of pilot plant runs for CONSENS project (Case study 1) N2 - In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and o-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum. The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17. In the following the contents of the files are explained. KW - Process Analytical Technology KW - Multivariate Data Analysis KW - Nuclear Magnetic Resonance KW - Near Infrared Spectroscopy KW - Continuous Manufacturing KW - CONSENS PY - 2018 DO - https://doi.org/10.5281/zenodo.1438233 PB - Zenodo CY - Geneva AN - OPUS4-48063 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Maiwald, Michael T1 - qNMR an der BAM - Aktuelle Aktivitäten und Strategie N2 - Der Vortrag gibt eine Übersicht über aktuelle qNMR-Aktivitäten im Fachbereich 1.4. Dies umfasst beispielsweise die Online-Anwendung zur Prozessüberwachung, aber auch die Reinheitsuntersuchung von Reinstoffkomponenten für die Herstellung von Referenzgasgemischen. Zusätzlich wird ein Ausblick in die aktuelle Strategie hinsichtlich der Rückführung von qNMR-Ergebnissen mittels primärer Referenzmaterialien gegeben. T2 - 10. Sitzung der Next-NMR-Arbeitsgruppe CY - Karlsruhe, Germany DA - 11.12.2018 KW - qNMR KW - NMR-Spektroskopie PY - 2018 AN - OPUS4-47131 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maiwald, Michael A1 - Meyer, Klas A1 - Gräßer, Patrick A1 - Wander, Lukas A1 - Guhl, Svetlana A1 - Bornemann-Pfeiffer, Martin A1 - Paul, Andrea A1 - Kern, Simon T1 - NMR Spectroscopy for Online Monitoring and Process Control N2 - The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. The talk introduces a smart online NMR sensor module provided in an explosion proof housing as example. This sensor was developed for an intensified industrial process (pharmaceutical lithiation reaction step) funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control. T2 - Lonza Shared Best Practice Seminar CY - Visp, Switzerland DA - 26.02.2019 KW - Process Analytical Technology KW - Reaction Monitoring KW - Online NMR Spectroscopy KW - Compact NMR Spectroscopy KW - Quantitative NMR Spectroscopy PY - 2019 N1 - Geburtsname von Bornemann-Pfeiffer, Martin: Bornemann, M. - Birth name of Bornemann-Pfeiffer, Martin: Bornemann, M. AN - OPUS4-47453 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Wander, Lukas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Already Producing or Still Calibrating? – Advances of Model-Based Automation for Online NMR Spectroscopy N2 - The transition from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example. Due to NMR spectroscopy as an “absolute comparison method”, independent of the matrix, it runs with very short set-up times in combination with “modular” spectral models. These are based on pure component NMR spectra without the need for tedious calibrations runs. We present approaches from statistical, (i.e., Partial Least Squares Regression) to physically motivated models (i.e., Indirect Hard Modelling). Based on concentration measurements of reagents and products by the NMR analyser a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu). T2 - 2nd Reaction Monitoring Symposium CY - Bath, UK DA - 28.01.2019 KW - Process Analytical Technology KW - NMR Spectroscopy KW - Modular Production PY - 2019 AN - OPUS4-47309 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Guhl, Svetlana A1 - Kern, Simon A1 - Wander, Lukas A1 - Gräßer, Patrick A1 - Acker, J. A1 - Maiwald, Michael T1 - Online NMR and Raman Spectroscopy – Combination of PAT tools for Process Monitoring 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”. 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 advanced 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 a robust 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 novel calibration concepts. This is a major advantage compared to other analytical methods, especially regarding multi-purpose plant strategies, as well as processes suffering from fluctuating quality of raw materials. The work presented here focusses on the heterogeneous catalyzed hydrogenation of 2-butyne-1,4-diol, as a step of the synthesis of industrially important solvent tetrahydrofuran. This reaction is proceeding via an intermediate product and suffers from competitive reaction paths. In this application, online NMR and Raman spectroscopy were combined with data from classical process sensors, e.g., pressure, temperature, and flow transducers in a highly automated setup for the development of innovative control concepts. T2 - Quantitative NMR Methods for Reaction and Process Monitoring (NMRPM) CY - Kaiserslautern, Germany DA - 31.01.2019 KW - Process Analytical Technology KW - Hydrogenation KW - Compact NMR Spectroscopy KW - Online-NMR spectroscopy PY - 2019 AN - OPUS4-47310 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas A1 - Peters, Claudia A1 - Maiwald, Michael T1 - Interlaboratory Comparison of Low-Field NMR Spectrometers – Purities at 200 and 10 mmol/L N2 - Due to its advantages of being a direct comparison method, quantitative NMR spectroscopy (qNMR) becomes more and more popular in industry. While conventional high-field NMR systems are often associated with high investment and operational costs, the upcoming market of permanent-magnet based benchtop NMR systems show a considerable option for a lot of applications. The mobility of these systems allows to bring them more closely to the real production environment, e.g. for at-line quality control. In this work we present an interlaboratory comparison study investigating the qNMR performance of state-of-the-art benchtop NMR spectrometers. Therefore, BAM prepared two samples of a mixture of NMR reference standards tetramethylbenzene (TMB) and tetrachloronitrobenzene (TCNB) at concentration levels of 200 mM and 10 mM. These “ready-to-use” samples were sent to participant laboratories, which performed analysis on their benchtop NMR equipment of different vendors and fields from 43 to 80 MHz. Raw data was reported back and further investigated by using different data analysis methods at BAM. After this very first qNMR comparison study of benchtop NMR spectrometers show promising results, following studies are planned to cover more parts of the qNMR process, e.g. sample preparation and weighing, but also data analysis, as commonly done in similar studies for high-field NMR spectroscopy in industry and metrology. T2 - Quantitative NMR Methods for Reaction and Process Monitoring (NMRPM) CY - Kaiserslautern, Germany DA - 31.01.2019 KW - qNMR KW - Compact NMR spectroscopy KW - Interlaboratory Comparison PY - 2019 AN - OPUS4-47311 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -