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 JF - Transactions on Emerging Topics in Computing 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 - JOUR A1 - Bornemann-Pfeiffer, Martin A1 - Kern, Simon A1 - Maiwald, Michael A1 - Meyer, Klas T1 - Calibration-Free Chemical Process and Quality Control Units as Enablers for Modular Production JF - Chemie Ingenieur Technik N2 - Modular chemical production is a tangible translation of the digital transformation of the process industry for specialty chemicals. In particular, it enables the speeding-up of process development and thus a quicker time to market by flexibly connecting and orchestrating standardised physical modules and bringing them to life (i.e., parameterising them) with digitally accumulated process knowledge. We focus on the specific challenges of chemical process and quality control, which in its current form is not well suited for modular production and provide possible approaches and examples of the change towards direct analytical methods, analytical model transfer or machine-supported processes. KW - Modular Production KW - Chemical Process Control KW - Process Analytical Technology KW - Digital Transformation KW - Industry 4.0 PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-517264 DO - https://doi.org/10.1002/cite.202000150 SN - 1522-2640 VL - 93 IS - 1-2 SP - 62 EP - 70 PB - Wiley-VCH CY - Weinheim AN - OPUS4-51726 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kuner, Maximilian A1 - Kühn, S. A1 - Haase, H. A1 - Meyer, Klas A1 - Koch, Matthias T1 - Cleaving Ergot Alkaloids by Hydrazinolysis - A Promising Approach for a Sum Parameter Screening Method JF - Toxins N2 - Ergot alkaloids are mycotoxins formed by fungi of the Claviceps genus, which are some of the most common contaminants of food and feed worldwide. These toxins are a structurally heterogeneous group of compounds, sharing an ergoline backbone. Six structures and their corresponding stereoisomers are typically quantified by either HPLC-FLD or HPLC-MS/MS and the values subsequently summed up to determine the total ergot alkaloid content. For the development of a screening method targeting all ergot alkaloids simultaneously, the alkaloids need to be transferred to one homogeneous structure: a lysergic acid derivative. In this study, two promising cleaving methods—acidic esterification and hydrazinolysis—are compared, using dihydroergocristine as a model compound. While the acidic esterification proved to be unsuitable, due to long reaction times and oxidation sensitivity, hydrazinolysis reached a quantitative yield in 40-60 min. Parallel workup of several samples is possible. An increasing effect on the reaction rate by the addition of ammonium iodide was demonstrated. Application of hydrazinolysis to a major ergot alkaloid mix solution showed that all ergopeptines were cleaved, but ergometrine/-inine was barely affected. Still, hydrazinolysis is a suitable tool for the development of a sum parameter screening method for ergot alkaloids in food and feed. KW - Ergot alkaloids KW - Sum parameter method KW - Hydrazinolysis KW - Esterification PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-527508 DO - https://doi.org/10.3390/toxins13050342 VL - 13 IS - 5 SP - 342 PB - MDPI CY - Basel, Switzerland AN - OPUS4-52750 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 JF - 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) 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 - 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 JF - Metrologia 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 - JOUR A1 - Bornemann-Pfeiffer, Martin A1 - Wolf, Jakob A1 - Meyer, Klas A1 - Kern, S. A1 - Angelone, D. A1 - Leonov, A. A1 - Cronin, L. A1 - Emmerling, Franziska T1 - Standardization and control of Grignard reactions in a universal chemical synthesis machine using online NMR T1 - Standardisierung und Kontrolle von Grignard-Reaktionen mittels Online-NMR in einer universellen chemischen Syntheseplattform JF - Angewandte Chemie - International Edition N2 - A big problem with the chemistry literature is that it is not standardized with respect to precise operational parameters, and real time corrections are hard to make without expert knowledge. This lack of context means difficult reproducibility because many steps are ambiguous, and hence depend on tacit knowledge. Here we present the integration of online NMR into an automated chemical synthesis machine (CSM aka. “Chemputer” which is capable of small-molecule synthesis using a universal programming language) to allow automated analysis and adjustment of reactions on the fly. The system was validated and benchmarked by using Grignard reactions which were chosen due to their importance in synthesis. The system was monitored in real time using online-NMR, and spectra were measured continuously during the reactions. This shows that the synthesis being done in the Chemputer can be dynamically controlled in response to feedback optimizing the reaction conditions according to the user requirements. N2 - Ein Problem der chemischen Literatur ist die fehlende Standardisierung bezüglich genauer Bedingungen, auch Echtzeit-Korrekturen sind ohne Expertenwissen nur schwer möglich. Dieser Mangel an Details erschwert experimentelle Reproduzierbarkeit, da Schritte oft mehrdeutig sind und daher von implizitem Wissen abhängen. Hier präsentieren wir die Integration von Online-NMR Spektroskopie in eine automatisierte chemische Syntheseplattform (CSM aka. “Chemputer”, unter Verwendung einer universellen Programmiersprache zur Synthese kleiner Moleküle fähig), um eine automatisierte Analyse und Anpassung von Reaktionen im laufenden Betrieb zu ermöglichen. Das System wurde anhand von Grignard-Reaktionen, die aufgrund ihrer Bedeutung für die Synthese ausgewählt wurden, validiert und einem Härtetest unterzogen. Synthesen wurden in Echtzeit mit Online-NMR überwacht, und die Spektren wurden während der Reaktionen kontinuierlich aufgenommen und analysiert. Dies zeigt, dass der Chemputer dynamisch mittels einer Regelung kontrolliert werden kann, um die Reaktionsbedingungen entsprechend den Anforderungen des Benutzers zu optimieren. KW - Grignard reaction KW - NMR spectroscopy KW - Process analytical technology KW - Process control KW - Grignard-Reaktion KW - NMR-Spektroskopie KW - Prozessanalytik KW - Prozesskontrolle PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-531260 DO - https://doi.org/10.1002/anie.202106323 SN - 1521-3773 SN - 1433-7851 N1 - Bibliografische Angaben für die deutsche Version: Angewandte Chemie 2021, Jg. 133, S. 1–7, ISSN 0044-8249, ISSN 1521-3757, https://doi.org/10.1002/ange.202106323 - Bibliographic information for the German version: Angewandte Chemie 2021, vol. 133, p. 1–7, ISSN 0044-8249, ISSN 1521-3757, https://doi.org/10.1002/ange.202106323 VL - 60 IS - 43 SP - 1 EP - 6 PB - Wiley-VCH CY - Weinheim AN - OPUS4-53126 LA - mul AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -