Chemische Charakterisierung und Spurenanalytik
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- 2019 (208) (entfernen)
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- Isotope analysis (9)
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- Online NMR Spectroscopy (9)
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Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (158)
- 1.1 Anorganische Spurenanalytik (46)
- 6 Materialchemie (40)
- 1.4 Prozessanalytik (38)
- 1.6 Anorganische Referenzmaterialien (28)
- 1.7 Organische Spuren- und Lebensmittelanalytik (28)
- 1.8 Umweltanalytik (28)
- 6.6 Physik und chemische Analytik der Polymere (21)
- 6.3 Strukturanalytik (18)
- 1.9 Chemische und optische Sensorik (13)
- 4 Material und Umwelt (13)
- P Präsident (13)
- P.0 Präsident und andere (12)
- 4.5 Kunst- und Kulturgutanalyse (6)
- 4.2 Material-Mikrobiom Wechselwirkungen (4)
- S Qualitätsinfrastruktur (4)
- 1.5 Proteinanalytik (3)
- 4.1 Biologische Materialschädigung und Referenzorganismen (3)
- S.1 Qualität im Prüfwesen (3)
- 1.3 Instrumentelle Analytik (2)
- 4.3 Schadstofftransfer und Umwelttechnologien (2)
- 7 Bauwerkssicherheit (2)
- 8 Zerstörungsfreie Prüfung (2)
- PST Präsidiale Stabsstelle (2)
- 1.0 Abteilungsleitung und andere (1)
- 1.2 Biophotonik (1)
- 4.0 Abteilungsleitung und andere (1)
- 5 Werkstofftechnik (1)
- 5.6 Glas (1)
- 6.1 Oberflächen- und Dünnschichtanalyse (1)
- 7.0 Abteilungsleitung und andere (1)
- 7.5 Technische Eigenschaften von Polymerwerkstoffen (1)
- 8.0 Abteilungsleitung und andere (1)
- 8.5 Röntgenbildgebung (1)
- 9 Komponentensicherheit (1)
- 9.0 Abteilungsleitung und andere (1)
- 9.4 Integrität von Schweißverbindungen (1)
- S.2 Digitalisierung der Qualitätsinfrastruktur (1)
Eingeladener Vortrag
- nein (98)
Reliable simulation of polymers on an atomistic length scale requires a realistic representation of the cured material. A molecular modelling method for the curing of epoxy systems is presented, which is developed with respect to efficiency while maintaining a well equilibrated system. The main criterion for bond formation is the distance between reactive groups and no specific reaction probability is prescribed. The molecular modelling is studied for three different mixing ratios with respect to the curing evolution of reactive Groups and the final curing stage. For the first time, the evolution of reactive groups during the curing process predicted by the molecular modelling is validated with near-infrared spectroscopy data, showing a good agreement between simulation results and experimental measurements. With the proposed method, deeper insights into the curing mechanism of epoxy systems can be gained and it allows us to provide reliable input data for molecular Dynamics simulations of material properties.
In this study, a method for the determination of tire and road wear particle (TRWP) contents in particulate samples from road Environment was developed. Zn was identified as the most suitable elemental marker for TRWP, due to its high concentration in tire tread and the possibility of separation from other Zn sources. The mean concentration of 21 tire samples was 8.7 ± 2.0 mg Zn/g. Before quantification in samples from road environment, TRWP were separated from the particulate matrix by density separation. Method development was conducted using shredded tread particles (TP) as a surrogate for TRWP.
Recovery of TP from spiked sediment was 95 ± 17% in a concentration range of 2 - 200 mg TP/g. TP determination was not affected by other Zn containing solids or spiked Zn-salts. By adjusting the density of the separation solution to 1.9 g/cm3, more than 90% of total TRWP were separated from the sample matrix. TRWP concentrations in particulate matter collected in two road runoff treatment Systems ranged from 0.38 to 150 mg TRWP/g. Differences in quantified TRWP contents of the two Systems indicate changes in particle dynamics due to ageing and aggregation processes. The developed method allows TRWP determination in road runoff and in environments that are influenced by road traffic. The validated separation procedure can also be applied for TRWP characterization in future studies.
The formation of transformation products (TPs) from contaminants and residues is becoming an increasing focus of scientific community. All organic compounds can form different TPs, thus demonstrating the complexity and interdisciplinarity of this topic. The properties of TPs could stand in relation to the unchanged substance or be more harmful and persistent. To get important information about the generated TPs, methods are needed to simulate natural and manmade transformation processes. Current tools are based on metabolism studies, photochemical methods, electrochemical methods, and Fenton's reagent. Finally, most transformation processes are based on redox reactions. This review aims to compare these methods for structurally different compounds. The groups of pesticides, pharmaceuticals, brominated flame retardants, and mycotoxins were selected as important residues/contaminants relating to their worldwide occurrence and impact to health, food, and environmental safety issues. Thus, there is an increasing need for investigation of transformation processes and identification of TPs by fast and reliable methods.
Prozessindustrie Gemeinsam Digital – Forschungsbedarf für die Digitalisierung der Prozessindustrie
(2019)
Die Digitale Transformation durchdringt weite Teile der Industrie mit einer zunehmenden Vernetzung und Digitalisierung entlang der Wertschöpfungskette.
Basierend auf dem Whitepaper der DECHEMA „Digitalisierung in der Chemieindustrie“ entsteht die Vision eines gläsernen Apparates mit einem zeitlich, räumlich und methodisch dichtem Monitoring der Betriebszustände, das eine daten- und modellbasierte Optimierung transienter oder instationärer Prozesse (das heißt An-/Abfahren, Laständerungen, etc.) erlaubt. Auch der nicht bestimmungsmäßige Betrieb von Apparaten oder Modulen wird zuverlässig erkannt. Basis ist hier die Implementierung von innovativer Messtechnik und neuartigen Sensoren in Kombination mit der Anwendung datengetriebener oder rigoroser Modelle zur Prozesssimulation und -kontrolle.
Anlagen, die auf diesem Konzept basieren, lassen sich sicher an Stabilitäts- bzw. Kapazitätsgrenzen und mit höherem Durchsatz betreiben. Trotz schwankender Rohstoffqualitäten kann eine gleichbleibende Zielqualität der Produkte mit rentablen Qualitätssicherungskosten garantiert werden. Dazu ist eine Vernetzung über weitere Branchen (Softwareingenieure, MSR-Technik, Betreiber, Hersteller) notwendig. Sie ergänzt komplementär die ENPRO-Initiative mit Themen der modularen Anlagenplanung und -konstruktion und modular verteilter Intelligenz. Ein Digitalisierungsbedarf besteht auch für bereits vorhandenen Anlagenbestand bzw. zukünftig nicht modular gestalteter Produktionsapparate der chemischen Industrie, um auch dort einen wesentlichen Beitrag zur Ressourcen- und Energieeffizienz zu leisten.
We have applied laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) with subcellular resolution as an elemental mass microscope to investigate the distributions of Ag nanoparticles (NP) in a 3-dimentional multicellular spheroid (MCS) model. The production of MCS has been optimized by changing the seeding cell number (500 to 40,000 cells) and the growth period (1 to 10 days). Incubations of MCS with Ag nanoparticle suspensions were performed with a concentration of 5 µg mL-1 for 24 hours. Thin-sections of the Eosin stained MCS were analysed by elemental mass microscopy using LA-ICP-MS to image distributions of 109Ag, 31P, 63Cu, 66Zn and 79Br. A calibration using NP suspensions was applied to convert the measured Ag intensity into the number of particles being present in each measurement pixel. The numbers of NP determined ranged from 30 up to 4,000 particles in an enrichment zone. The particle distribution was clearly correlated to 31P, 66Zn and 79Br and was localized in an outer rim of proliferating cells (confirmed by DAPI) with a width of about two-single cell diameters. For the highest seeding cell number NPs were only detected in this outer rim, whereas small molecules as for instance 79Br and 109Ag ions were detected in the core of the MCS as well. Aniline blue staining demonstrated that this outer rim was rich in collagen structures in which fibroblast cells were embedded and a thin-membrane was visible which separated the core from the biological active cell layer functioning as biological barriers for NP transport. In this presentation, we will show the possibility using this 3-dimensional model for toxicological and medical applications.
Complementarity of molecular and elemental mass spectrometric imaging of Gadovist™ in mouse tissues
(2019)
Drug biodistribution analyses can be considered a key issue in pharmaceutical discovery and development. Here, mass spectrometric imaging can be employed as a powerful tool to investigate distributions of drug compounds in biologically and medically relevant tissue sections. Both matrix-assisted laser desorption ionization–mass spectrometric imaging as molecular method and laser ablation inductively coupled plasma–mass spectrometric imaging as elemental detection method were applied to determine drug distributions in tissue thin sections. Several mouse organs including the heart, kidney, liver, and brain were analyzed with regard to distribution of Gadovist™, a gadolinium-based contrast agent already approved for clinical investigation. This work demonstrated the successful detection and localization of Gadovist™ in several organs. Furthermore, the results gave evidence that gadolinium-based contrast agents in general can be well analyzed by mass spectrometric imaging methods. In conclusion, the combined application of molecular and elemental mass spectrometry could complement each other and thus confirm analytical results or provide additional information.
The successful off-line coupling of asymmetrical flow field flow fractionation (AF4) and capillary electrophoresis (CE) for separation of nanoparticles (NPs) with different surface coatings was shown. We could successfully demonstrate that, in a certain NP size range, hyphenation of both techniques significantly improved the separation of differently coated NPs. Three mixtures of polystyrene nanoparticles (PS-NPs) with comparable core sizes but different coatings (no coating/carboxyl-coated) were studied. Separation in either method resulted in non-baseline resolved or non-separated peaks. In contrast, two-dimensional off-line coupling of AF4 and CE resulted in clearly separated regions in their 2 D plots in case of 20 and 50 nm particle mixtures, whereas the 100 nm NP mixture could not be separated at all. Various factors affecting the separation like hydrodynamic diameter or SDS concentration were discussed.
Synchrotron radiation X-ray fluorescence spectroscopy, in conjunction with atomic absorption and Raman spectroscopy, was used to analyze a set of top brand tattoo inks to investigate the presence of toxic elements and hazardous substances. The Cr, Cu, and Pb contents were found to be above the maximum allowed levels established by the Council of Europe through the resolution ResAP(2008)1 on requirements and criteria for the safety of tattoos and permanent makeup. Raman analysis has revealed the presence of a set of prohibited substances mentioned in ResAP(2008)1, among which are the pigments Blue 15, Green 7, and Violet 23. Other pigments that were identified in white, black, red, and yellow inks are the Pigment White 6, Carbon Black, Pigment Red 8, and a diazo yellow, respectively. The present results show the importance of regulating tattoo ink composition.
Correlating the photoluminescence (PL) properties of nanomaterials like semiconductor nanocrystals (QDs) and upconversion nanocrystals (UCNPs) assessed in ensemble studies and at the single particle level is increasingly relevant for applications of these nanomaterials in the life sciences like bioimaging studies or their use as reporters in microfluidic assays. Here we present a comparison of the spectroscopic properties of ensembles and single emitters for QDs like II/VI QDs and cadmium-free AIS/ZnS QDs as well as different UCNPs. The overall goal of this study was to derive particle architectures well suited for spectroscopic and microscopic applications.
Metal tags find application in a multitude of biomedical systems and the combination with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) offers an opportunity for multiplexing. To lay the foundation for an increase of the signal intensities in such processes, we herein present a general approach for efficient functionalization of a well-defined metal oxido cluster [Bi6O4(OH)(4)(SO3CF3)(6)(CH3CN)(6)].2 CH3CN (1), which can be realized by selecting 7mer peptide sequences via combinatorial means from large one-bead one-compound peptide libraries. Selective cluster-binding peptide sequences (CBS) for 1 were discriminated from non-binders by treatment with H2S gas to form the reduction product Bi2S3, clearly visible to the naked eye. Interactions were further confirmed by NMR experiments. Extension of a binding peptide with a maleimide linker (Mal) introduces the possibility to covalently attach thiol-bearing moieties such as biological probes and for their analysis the presence of the cluster instead of mononuclear entities should lead to an increase of signal intensities in LA-ICP-MS measurements. To prove this, CBS-Mal was covalently bound onto thiol-presenting glass substrates, which then captured 1 effectively, so that LA-ICP-MS measurements demonstrated drastic signal amplification compared to single lanthanide tags.
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.
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.
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).
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 down-times 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.
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 down-times 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.
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 down-times 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.
Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short down-times 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.
The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control and gives also an overview on direct dissolution studies of API cocrystals.