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 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 - Gottu Mukkula, A. R. A1 - Kern, Simon A1 - Salge, M. A1 - Holtkamp, M. A1 - Guhl, Svetlana A1 - Fleischer, C. A1 - Meyer, Klas A1 - Remelhe, M. A1 - Maiwald, Michael A1 - Engell, S. T1 - An Application of Modifier Adaptation with Quadratic Approximation on a Pilot Scale Plant in Industrial Environment N2 - The goal of this work is to identify the optimal operating input for a lithiation reaction that is performed in a highly innovative pilot scale continuous flow chemical plant in an industrial environment, taking into account the process and safety constraints. The main challenge is to identify the optimum operation in the absence of information about the reaction mechanism and the reaction kinetics. We employ an iterative real-time optimization scheme called modifier adaptation with quadratic approximation (MAWQA) to identify the plant optimum in the presence of plant-model mismatch and measurement noise. A novel NMR PAT-sensor is used to measure the concentration of the reactants and of the product at the reactor outlet. The experiment results demonstrate the capabilities of the iterative optimization using the MAWQA algorithm in driving a complex real plant to an economically optimal operating point in the presence of plant-model mismatch and of process and measurement uncertainties. KW - Process Analytical Technology KW - Online NMR Spectroscopy KW - Process Industry KW - Iterative real-time optimization KW - Modifier adaptation KW - Plant-model mismatch KW - Reactor control KW - CONSENS PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-524531 DO - https://doi.org/10.1016/j.ifacol.2020.12.685 SN - 1522-2640 VL - 53 IS - 2 SP - 11773 EP - 11779 PB - Elsevier CY - Amsterdam AN - OPUS4-52453 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bruno, Francesco A1 - Fiorucci, Letizia A1 - Vignoli, Alessia A1 - Meyer, Klas A1 - Maiwald, Michael A1 - Ravera, Enrico T1 - pyIHM: Indirect Hard Modeling, in Python N2 - NMR is a powerful analytical technique that combines an exquisite qualitative power, related to the unicity of the spectra of each molecule in a mixture, with an intrinsic quantitativeness, related to the fact that the integral of each peak only depends on the number of nuclei (i.e., the amount of substance times the number of equivalent nuclei in the signal), regardless of the molecule. Signal integration is the most common approach in quantitative NMR but has several drawbacks (vide infra). An alternative is to use hard modeling of the peaks. In this paper, we present pyIHM, a Python package for the quantification of the components of NMR spectra through indirect hard modeling, and we discuss some numerical details of the implementation that make this approach robust and reliable. KW - Algorithms KW - Chemical Structure KW - Deconvolution KW - Mixtures KW - NMR spectroscopy PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-626793 DO - https://doi.org/10.1021/acs.analchem.4c06484 SN - 1520-6882 VL - 97 IS - 8 SP - 4598 EP - 4605 PB - ACS Publications CY - Washington D.C. AN - OPUS4-62679 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Thiele, Isabel A1 - Santolin, Lara A1 - Meyer, Klas A1 - Machatschek, Rainhard A1 - Bölz, Uwe A1 - Tarazona, Natalia A. A1 - Riedel, Sebastian L. T1 - Microbially synthesized poly(hydroxybutyrate-co-hydroxyhexanoate) with low to moderate hydroxyhexanoate content: Properties and applications N2 - Plastic pollution is the biggest environmental concern of our time. Breakdown products like micro- and nanoplastics inevitably enter the food chain and pose unprecedented health risks. In this scenario, bio-based and biodegradable plastic alternatives have been given a momentum aiming to bridge a transition towards a more sustainable future. Polyhydroxyalkanoates (PHAs) are one of the few thermoplastic polymers synthesized 100 % via biotechnological routes which fully biodegrade in common natural environments. Poly(hydroxybutyrate-cohydroxyhexanoate) [P(HB-co-HHx)] is a PHA copolymer with great potential for the commodity polymers industry, as its mechanical properties can be tailored through fine-tuning of its molar HHx content. We have recently developed a strategy that enables for reliable tailoring of the monomer content of P(HB-co-HHx). Nevertheless, there is often a lack of comprehensive investigation of the material properties of PHAs to evaluate whether they actually mimic the functionalities of conventional plastics. We present a detailed study of P(HB-co-HHx) copolymers with low to moderate hydroxyhexanoate content to understand how the HHx monomer content influences the thermal and mechanical properties and to link those to their abiotic degradation. By increasing the HHx fractions in the range of 2 – 14 mol%, we impart an extension of the processing window and application range as the melting temperature (Tm) and glass temperature (Tg) of the copolymers decrease from Tm 165 ◦C to 126 ◦C, Tg 4 ◦C to − 5.9 ◦C, accompanied by reduced crystallinity from 54 % to 20 %. Elongation at break was increased from 5.7 % up to 703 % at 14 mol% HHx content, confirming that the range examined was sufficiently large to obtain ductile and brittle copolymers, while tensile strength was maintained throughout the studied range. Finally, accelerated abiotic degradation was shown to be slowed down with an increasing HHx fraction decreasing from 70 % to 55 % in 12 h. KW - Molecular Biology KW - General Medicine KW - Biochemistry KW - Structural Biology PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-595636 DO - https://doi.org/10.1016/j.ijbiomac.2024.130188 VL - 263 SP - 1 EP - 9 PB - Elsevier B.V. AN - OPUS4-59563 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 A1 - Rademann, K. A1 - Panne, Ulrich A1 - Maiwald, Michael T1 - Quantitative NMR spectroscopy for gas analysis for production of primary reference gas mixtures N2 - Due to its direct correlation to the number of spins within a sample quantitative NMR spectroscopy (qNMR) is a promising method with absolute comparison abilities in complex systems in technical, as well as metrological applications. Most of the samples studied with qNMR are in liquid state in diluted solutions, while gas-phase applications represent a rarely applied case. Commercially available NMR equipment was used for purity assessment of liquid and liquefied hydrocarbons serving as raw materials for production of primary reference gas standards. Additionally, gas-phase studies were performed within an online NMR flow probe, as well as in a high-pressure NMR setup to check feasibility as verification method for the composition of gas mixtures. KW - Quantitative NMR spectroscopy KW - Gas-phase NMR spectroscopy KW - Primary reference gas mixtures PY - 2017 UR - http://www.sciencedirect.com/science/article/pii/S1090780716302518 DO - https://doi.org/10.1016/j.jmr.2016.11.016 SN - 1090-7807 SN - 1096-0856 VL - 275 SP - 1 EP - 10 AN - OPUS4-38803 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 - JOUR A1 - Golub, Tino Petar A1 - Meyer, Klas A1 - Paul, Andrea A1 - Kipphardt, Heinrich A1 - Tuma, Dirk T1 - Exploring the potential of a setup for combined quantification of hydrogen in natural gas – Raman and NMR spectroscopy N2 - An accurate measurement of the amount fraction of hydrogen in gas mixtures is mandatory for practical applications, requiring methods that are fast, continuous, robust, and cost-effective. This study compares the performance of Raman and benchtop NMR process spectroscopy for determining the hydrogen amount fraction in gas mixtures. A setup was designed to integrate both techniques, enabling measurements of the same sample. Tests were conducted with gravimetrically prepared gas mixtures of reference quality ranging from 1.20 cmol/mol to 85.83 cmol/mol of hydrogen. The results demonstrate that Raman spectroscopy provides superior performance, with a minimal root mean square error (RMSE) of 0.22 cmol/mol and excellent linearity. In contrast, benchtop NMR spectroscopy faced challenges, such as overlapping peaks and longer measurement times, resulting in a higher RMSE of 0.71 cmol/mol. Raman spectroscopy proves to be particularly well-suited for practical applications due to its high accuracy and linearity. Meanwhile, benchtop NMR spectroscopy holds potential for future enhancements through ongoing technological advances, such as higher magnetic field strengths. In summary, the results from our study indicate that Raman spectroscopy is already a serviceable method for precise hydrogen quantification, whereas benchtop NMR spectroscopy can be attributed potential for future applications. KW - Hydrogen amount fraction KW - Raman spectroscopy KW - NMR spectroscopy KW - Field applicability PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-610093 DO - https://doi.org/10.1016/j.saa.2024.125087 SN - 1386-1425 VL - 325 SP - 1 EP - 9 PB - Elsevier B.V. CY - Amsterdam AN - OPUS4-61009 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 - Bornemann-Pfeiffer, Martin A1 - Meyer, Klas A1 - Lademann, J. A1 - Kraume, M. A1 - Maiwald, Michael T1 - Contributions towards variable temperature shielding for compact NMR instruments N2 - The application of compact NMR instruments to hot flowing samples or exothermically reacting mixtures is limited by the temperature sensitivity of permanent magnets. Typically, such temperature effects directly influence the achievable magnetic field homogeneity and hence measurement quality. The internal-temperature control loop of the magnet and instruments is not designed for such temperature compensation. Passive insulation is restricted by the small dimensions within the magnet borehole. Here, we present a design approach for active heat shielding with the aim of variable temperature control of NMR samples for benchtop NMR instruments using a compressed airstream which is variable in flow and temperature. Based on the system identification and surface temperature measurements through thermography, a model predictive control was set up to minimise any disturbance effect on the permanent magnet from the probe or sample temperature. This methodology will facilitate the application of variable-temperature shielding and, therefore, extend the application of compact NMR instruments to flowing sample temperatures that differ from the magnet temperature. KW - Benchtop NMR KW - Continuous Processes KW - Inline Analytics KW - Model Predictive Control KW - Process Analytical Tecnology KW - Temperature Control PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-579219 DO - https://doi.org/10.1002/mrc.5379 SN - 1097-458X SP - 1 EP - 10 PB - John Wiley & Sons Ltd. AN - OPUS4-57921 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -