TY - CONF A1 - Maiwald, Michael T1 - Integrated and Networked Systems and Processes - How NMR Spectroscopy Can Transform our Chemical and Pharmaceutical Production N2 - Chemical and pharmaceutical companies need to find new ways to survive successfully in a changing environment, while finding more flexible ways of product and process development to bring their products to market faster - especially high-value, high-end products such as fine chemicals or pharmaceuticals. This is complicated by changes in value chains along a potential circular economy. One current approach is flexible and modular chemical production units that use multi-purpose equipment to produce various high-value products with short downtimes between campaigns and can shorten time-to-market for new products. Online NMR spectroscopy will play an important role for plant automation and quality control, as the method brings very high linearity, matrix independence and thus works almost calibration-free. Moreover, these properties ideally enable automated and machine-aided data analysis for the above-mentioned applications. Using examples, this presentation will outline a possible more holistic approach to digitalization and the use of machine-based processes in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes. T2 - 43rd FGMR Annual Discussion Meeting CY - Karlsruhe, Germany DA - 12.09.2022 KW - Digital Transformatioin KW - Process Industry KW - Pharmaceuticals KW - Specialty Chemicals KW - Automation KW - Online NMR Spectroscopy KW - Industry 4.0 PY - 2022 AN - OPUS4-55715 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas 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 - JOUR A1 - Maiwald, Michael T1 - Next Generation Automation - Arbeitskreis 3.7: Smarte Sensorik, Aktorik und Kommunikation N2 - Der AK 3.7 ist ein "erweiterter" AK und je zur Hälfte mit NAMUR-Vertretern und Vertretern der Geräte- und Softwarehersteller besetzt. Er wurde ins Leben gerufen, um Begrifflichkeiten der digitalen Transformation aufzugreifen, wie etwa Smarte Sensorik, Sensordatenfusion, Schwarmsensorik oder Softsensorik. Eine erste Aufgabe bestand darin, einige exemplarische Anwendungsfälle der Nutzung smarter Eigenschaften von Feldgeräten sowie deren zukünftige Kommunikationsmöglichkeiten sowohl mit Bezug auf Bestandsanlagen als auch mit Blick auf einen potentiellen Technologiewechsel zu betrachten. Neuer Scope des AK 3.7 ist eine "Next Generation Automation" um einen potentiellen Technologiewechsel rechtzeitig vorauszudenken. Dieses erfolgt unter vollständiger gedanklicher Trennung von heutiger Automatisierung und auch vom NOA-Konzept. Ebenso wird ein Technologiewechsel in der Produktion der Prozessindustrie (wahrscheinlich modulbasiert) postuliert. Ziel des AK 3.7 wird es in Zukunft sein, diese Anforderungen an smarte Feldgeräte aufzugreifen und gemeinsam mit den thematisch überlappenden Interessenskreisen in Standards zu übersetzen. KW - Prozessindustrie KW - Automation KW - NAMUR KW - Sensorik KW - Aktorik KW - Kommunikation PY - 2021 SN - 2190-4111 SN - 2364-3137 IS - 9 SP - 73 PB - Vulkan Verlag CY - Essen AN - OPUS4-54336 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Cairns, Warren R. L. A1 - Butler, Owen T. A1 - Cavoura, Olga A1 - Davidson, Christine M. A1 - Todolí-Torró, José-Luis A1 - von der Au, Marcus T1 - Atomic spectrometry update – a review of advances in environmental analysis N2 - Highlights in the field of air analysis included: a new focus on measuring micro- and nanoplastic particles in air, the development of hyphenated ICP-MS systems for in situ sampling and measurement of airborne metallic particles and the reported use of wearable black carbon sensors for measuring exposure to diesel fumes within the workplace. Significant advancements in the analysis of waters have been made in developing novel resin materials and new protocols for existing commercially available resins, aimed at the determination and speciation of trace levels of metals and metalloids in water matrices. These developments have been validated for sample purification and pre-concentration. In addition to traditional column chemistry, on-line hyphenated techniques were employed to enhance speciation analysis, with optimized methods enabling faster analysis and facilitating a more holistic approach by allowing the simultaneous detection of multiple species or elements in a single run. Efforts have also been directed towards detecting particles in the micro- and nanometer range, broadening the analytical scope beyond the ionic fraction. This year, the focus shifted from natural and engineered nanoparticles towards the critical field of plastic pollution, with several innovative methodologies introduced. Furthermore, to achieve better precision and lower detection limits in the field of MS/MS, numerous studies explored the behaviour of gases and reactions within reaction cells, contributing to the refinement of these techniques. In the analysis of soils and plants, methods aimed at improving the efficiency of green solvents were again prominent. Developments in AES were largely driven by the desire to create small, low-cost, low-power-consumption instrumentation suitable for field deployment. The study of NPs in soil and plant systems continued to be a focus for sp-ICP-MS. The past year has again seen a large volume of publications featuring LIBS, with particular interest in methods to enhance signal intensity and thereby improve limits of detection. Of interest in XRF was the development of in-house spectrometers for underwater mercury screening and in vivo plant analysis. Developments in geological analysis include new homogeneous natural and synthetic materials that have been developed as reference materials (RMs) in the analysis of geological samples by microanalytical techniques, such as LA-ICP-MS, LIBS and SIMS. Additional information on already existing RMs has been obtained for in situ isotope ratio determinations. Attention has been paid to sample preparation and purification methods able to shorten the analysis time and to improve the accuracy. Much attention has been paid to the use of LA-ICP-MS/MS as a means for removing spectral interferences in the case of in situ localized isotopic analysis and dating of geological materials. The development of new chemometric models as well as software has continued to improve data quality. The use of artificial intelligence is growing and techniques such as machine learning have led to significant improvements in the quality of geochemical results. KW - Review KW - Water KW - Environment PY - 2025 DO - https://doi.org/10.1039/D4JA90056A SN - 0267-9477 VL - 40 IS - 1 SP - 11 EP - 69 PB - Royal Society of Chemistry CY - London AN - OPUS4-62283 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Paul, Andrea T1 - Potential of multivariate data analysis (MVA) in X-ray fluorescence analysis N2 - X-ray fluorescence spectrometry (XRF) is used, for example, in geochemistry, archaeology, materials science and agriculture to analyze the elemental composition of various samples [1]. Quantitative spectrum analysis typically applies methods such as fundamental parameters or intensity correction [1, 2]. However, there are also approaches to analyze XRF spectra using data-driven MVA approaches that are not based on a physical model. Principal component analysis (PCA) enables the visualization of data and the discovery of hidden relationships between analytical signals and sample parameters [1, 3]. Classification methods, e.g. PCA, cluster or discriminant analysis, can help to distinguish samples based on various complex integral features such as authenticity or origin of the sample [3]. MVA can also be used to correlate various external factors with elemental composition. In addition to classifying mineral wool into different material types based on characteristic oxides, PCA also enables the visualization of problem cases and supports the detection of possible outliers [4]. Multivariate regression methods such as partial least squares regression (PLSR) are a powerful tool for the quantitative analysis of spectra. In contrast to univariate analysis, in which only one characteristic is used as the basis for the regression, entire spectra or spectral ranges are analyzed here. It has been shown that the quantitative determination of C, H, N and O in polymers based on WDXRF spectra can be achieved by PLSR [5]. However, in the presence of complex matrix effects, the limitations of PLSR become clear, as was shown in a reference case (EDXRF spectra of steel and ore samples) [2]. Here, PLSR still outperformed the fundamental parameter approach, but proved to be less accurate than an intensity correction approach. Neural networks, which are better able to deal with nonlinear effects, are only an alternative if both a large number of calibration samples are available for adequate network training and a lot of time is available for network optimization. Despite limitations, it can be summarized that MVA, if used correctly, can contribute to increasing the informative value of XRF and to opening up new fields of application in areas of growing economic importance [1-5]. T2 - 12. PRORA Fachtagung Prozessnahe Röntgenanalytik CY - Berlin, Germany DA - 28.11.2024 KW - Chemometrics KW - Mineral wool KW - Data analysis KW - X-ray fluorescence PY - 2024 AN - OPUS4-62032 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas T1 - Deconvolution in High-Field- and Benchtop-NMR applications N2 - Numerical "sum integration" is the typical way to extract signal area from NMR spectra for quantitative evaluation, however, in complex situations of peak overlaps or crowded spectra this can be impractical. Deconvolution methods based on linefitting and optimization allow for a more accurate extraction of signal features from the spectrum in these cases. The increasing number of benchtop NMR applications showing lower signal dispersion and therefore more often complex spectral patterns foster the development and application of model-based spectra evaluation methods. This includes techniques like Indirect Hard Modeling (IHM), Quantum-Mechanical Spectra Analysis (QMSA), Chemometric modeling like PLS-R or MCR, as well as Machine-learning approaches using Neural Networks. This presentation gives an overview and introduction into deconvolution methods in the context of high-field and benchtop-NMR applications in complex spectra and process monitoring. T2 - CCQM OAWG/PAWG Advances in qNMR Workshop CY - Sèvres, France DA - 08.04.2025 KW - NMR Spectroscopy KW - Process Analytical Technology KW - Deconvolution KW - Benchtop-NMR PY - 2025 AN - OPUS4-62956 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meyer, Klas T1 - Process Monitoring with Compact NMR spectroscopy: Applications from Lab to Field N2 - The use of compact NMR instruments based on permanent magnets has been increasing in recent years. Their affordability, portability, and ease of operation without the need for trained staff make them particularly interesting for quality control application in industrial production. Recent developments by instrument manufacturers, such as multi-nuclei options or extended interfacing, have made these systems even more versatile. However, the application of NMR spectroscopy as an online PAT tool remains rare, despite its significant potential for process optimization and control. A key challenge in exploiting this potential is the integration of lab instruments into the harsh environment of a chemical plant. Additionally, advancements in automation and data evaluation are key tasks to ensure robust, unattended operation with minimal maintenance requirements. In this presentation, we showcase examples of using NMR spectroscopy for process monitoring at the lab scale, the development of open-source software tools for NMR data evaluation (PyIHM, within the Python package KLASSEZ), and a successful example of field integration, running an automated laboratory instrument in the environment of a industrial production plant. T2 - Quantitative NMR Methods for Reaction and Process Monitoring (NMRPM) CY - Kaiserslautern, Germany DA - 31.03.2025 KW - Compact NMR spectroscopy KW - Process Monitoring KW - Downstream processing KW - Indirect Hard Modeling KW - Field integration PY - 2025 AN - OPUS4-62850 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Paul, Andrea T1 - Kombinierte Bestimmung von Wasserstoff in Gasgemischen mittels Raman- und NMR-Spektroskopie N2 - Vorgestellt wird die Nutzung von Online tauglichen Raman- und NMR-Spektrometern zur Quantifizierung des Wasserstoffmolanteils in gravimetrisch hergestellten Primärgasstandards unter Labor-Bedingungen. Es zeigte sich, dass Matrixeffekte insbesondere bei der Raman-Spektroskopie vernachlässigbar sind für die Quantifizierung von H2. Aufgrund der leichten Handhabbarkeit und der geringen Messunsicherheiten ergibt sich eine potenzielle Anwendung von Raman- und NMR-Spektroskopie unter Feldbedingungen als Online-Messeinheit im Bereich 5-100 cmol/mol Wasserstoff. T2 - 19. PAT Erfahrungsaustauschtreffen CY - Basel, Switzerland DA - 17.09.2024 KW - Raman KW - NMR KW - Wasserstoff PY - 2024 AN - OPUS4-62035 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lozano-Martín, D. A1 - Tuma, Dirk A1 - Kipphardt, Heinrich A1 - Khanipour, Peyman A1 - Chamorro, C. R. T1 - Thermodynamic characterization of the (H2 + C3H8) system significant for the hydrogen economy: Experimental (p, rho, T) determination and equation-of-state modelling N2 - For the gradual introduction of hydrogen in the energy market, the study of the properties of mixtures of hydrogen with typical components of natural gas (NG) and liquefied petroleum gas (LPG) is of great importance. This work aims to provide accurate experimental (p, rho, T) data for three hydrogen-propane mixtures with nominal compositions (amount of substance, mol/mol) of (0.95 H2 + 0.05 C3H8), (0.90 H2 + 0.10 C3H8), and (0.83 H2 + 0.17 C3H8), at temperatures of 250, 275, 300, 325, 350, and 375 K, and pressures up to 20 MPa. A single-sinker densimeter was used to determine the density of the mixtures. Experimental density data were compared to the densities calculated from two reference equations of state: the GERG-2008 and the AGA8-DC92. Relative deviations from the GERG-2008 EoS are systematically larger than those from the AGA8-DC92. They are within the ±0.5% band for the mixture with 5% of propane, but deviations are higher than 0.5% for the mixtures with 10% and 17% of propane, especially at low temperatures and high pressures. Finally, the sets of new experimental data have been processed by the application of two different statistical equations of state: the virial equation of state, through the second and third virial coefficients, B(T, x) and C(T, x), and the PC-SAFT equation of state. KW - Hydrogen-containing gas mixture KW - Density data KW - Equation of state KW - Virial coefficients PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-570056 DO - https://doi.org/10.1016/j.ijhydene.2022.11.170 SN - 0360-3199 VL - 48 IS - 23 SP - 8645 EP - 8667 PB - Elsevier B. V. CY - Amsterdam AN - OPUS4-57005 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lozano-Martín, Daniel A1 - Kipphardt, Heinrich A1 - Khanipour, Peyman A1 - Tuma, Dirk A1 - Horrillo, Alfonso A1 - Chamorro, César R. T1 - Impact of hydrogen addition, up to 20 % (mol/mol), on the thermodynamic (p, ρ, T) properties of a reference high-calorific natural gas mixture with significant ethane and propane content N2 - Injecting hydrogen into the natural gas grid supports gradual decarbonization. To check the accuracy of equations of state for hydrogen-enriched natural gas mixtures, precise density data from well-characterized reference mixtures are essential. In a prior study, we provided experimental measurements for a natural gas constituted mainly of methane and for two derived hydrogen-enriched mixtures. In the present study, being the second and final part of our investigation, density measurements for a high-calorific natural gas with significant ethane and propane content, along with two hydrogen-enriched variants (10 and 20 mol-% hydrogen) are provided. The mixtures are gravimetrically prepared following ISO 6142-1. Density measurements, conducted with a single-sinker densimeter at temperatures from (260–350) K and pressures up to 20 MPa, are compared with three equations of state: AGA8-DC92, GERG-2008, and an improved GERG-2008. Results indicate that all models perform better for methane-dominant mixtures than for those containing heavier hydrocarbons. KW - Hydrogen-enriched natural gas KW - High-pressure density KW - Reference equation of state PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-633371 DO - https://doi.org/10.1016/j.ijhydene.2025.05.173 SN - 0360-3199 VL - 140 SP - 256 EP - 271 PB - Elsevier BV CY - Amsterdam AN - OPUS4-63337 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -