Chemische Charakterisierung und Spurenanalytik
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Eingeladener Vortrag
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How to write your thesis
(2019)
The knowledge of transformation pathways and identification of transformation products (TPs) of veterinary drugs is important for health, food and environmental matters. Monensin (MON) is an ionophore antibiotic widely used to cure and prevent coccidiosis by chicken especially in broiler farming. Residues can be found in food products (chicken and eggs) and in the environment (manure, soil, water). Several transformation processes can alter the parent compound MON, ranging from biotransformation in living organism to biotic/abiotic and microbial processes in environmental matters.
The main objective of this work was to investigate the potential of electrochemistry (EC) to simulate oxidative transformation processes of MON and to predict TPs. An electrochemical reactor was used consisting of a flow-through cell with a glassy carbon working electrode. Derived TPs were analyzed by online coupling of EC and high-resolution mass spectrometry (HRMS) and LC/HRMS offline measurements. Among the generated TPs already known as well as unknown TPs of MON could be found.
Additionally, MON was subjected also to other transformation experiments like metabolism tests with rat microsomes or the pH-dependent hydrolysis. As a result, different targeted and suspected TPs could be identified by analysis with LC/HRMS.
An overview of detected/identified TPs from this study will be presented in comparison to literature known metabolites and TPs.
19th and 20th centuries glass paint layers consist of a colour body and a colourless lead silicate flux, in which borax or boric acid was added as further component to improve the paint ability and to reduce the firing temperature for multiple layers of paint. Model glasses were used in laboratory tests to investigate the stability of glass paints with additions of boron oxide. To determine boron in paint layers, a LIBS-system with pulsed NdYAG-laser was used.
Laser-induced plasmas are widely used in many areas of science and technology; examples include spectrochemical analysis, thin film deposition, material processing, and even jet propulsion. Several topics will be addressed. First, general phenomenology of laser-induced plasmas will be discussed. Then, a chemical model will be presented based on a coupled solution of Navier-Stokes, state, radiative transfer, material transport, and chemical (Guldberg-Waage) equations. Results of computer simulations for several chemical systems will be shown and compared to experimental observations obtained by optical imaging, spectroscopy, and tomography. The latter diagnostic tools will also be briefly discussed.
In the recent decade, metal pyrithione complexes have become important biocides for antifouling purposes in shipping. The analysis of metal pyrithione complexes and their degradation products/species in environmental samples is challenging because they exhibit fast UV degradation, transmetalation, and ligand substitution and are known to be prone to spontaneous species transformation within a chromatographic system. The environmental properties of the pyrithione species, e.g., toxicity to target and non-target organisms, are differing strongly, and it is therefore inevitable to identify as well as quantify all species separately. To cope with the separation of metal pyrithione species with minimum species transformation during analysis, a capillary electrophoresis (CE)–based method was developed. The hyphenation of CE with selective electrospray ionization- and inductively coupled plasma–mass spectrometry (ESI-, ICP-MS) provided complementary molecular and elemental information for the identification and quantification of pyrithione species. To study speciation of pyrithiones, a leaching experiment of several commercial antifouling paints containing zinc pyrithione in ultrapure and river water was conducted. Only the two species pyrithione (HPT) and dipyrithione ((PT)2) were found in the leaching media, in concentrations between 0.086 and 2.4 μM (HPT) and between 0.062 and 0.59 μM ((PT)2), depending on the paint and leaching medium. The limits of detection were 20 nM (HPT) and 10 nM ((PT)2). The results show that complementary CE-MS is a suitable tool for mechanistical studies concerning species transformation (e.g., degradation) and the identification of target species of metal pyrithione complexes in real surface water matrices, laying the ground for future environmental studies.
Arraying of single cells for mass spectrometric analysis is a considerable bioanalytical challenge. In this study, we employ a novel single cell arraying technology for quantitative analysis and isotopic fingerprinting by laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS). The single cell arraying approach is based on a piezo-acoustic microarrayer with software for automated optical detection of cells within the piezo dispense capillary (PDC) prior to arraying. Using optimized parameters, single cell occupancy of >99%, high throughput (up to 550 cells per hour), and a high cell recovery of >66% is achieved. LA-ICP-TOF-MS is employed to detect naturally occurring isotopes in the whole mass range as fingerprints of individual cells. Moreover, precise quantitative determination of metal-containing cell dyes is possible down to contents of ∼100 ag using calibration standards which were produced using the same arrayer.
In the last decades, significant efforts have been made to investigate possible cytotoxic effects of metallic nanoparticles (NPs). Methodologies enabling precise information regarding uptake and intracellular distribution of NPs at the single cell level remain to be established. Mass cytometry (MC) has been developed for high-dimensional single cell analyses and is a promising tool to quantify NP−cell interactions. Here, we aim to establish a new MC-based quantification procedure to receive absolute numbers of NPs per single cell by using a calibration that considers the specific transmission efficiency (TE) of suspended NPs. The current MC-quantification strategy accept TE values of complementary metal solutions. In this study, we demonstrate the different transmission behavior of 50 nm silver NPs (AgNP) and silver nitrate solution. We have used identical AgNPs for calibration as for in vitro-differentiated macrophages (THP-1 cell line) in a time- and dose-dependent manner. Our quantification relies on silver intensities measuring AgNPs in the same detection mode as the cells. Results were comparable with the TE quantification strategy using AgNPs but differed when using ionic silver. Furthermore, intact and digested cell aliquots were measured to investigate the impact of MC sample processing on the amount of AgNPs/cell. Taken together, we have provided a MC-specific calibration procedure to precisely calculate absolute numbers of NPs per single cell. Combined with its unique feature of multiplexing up to 50 parameters, MC provides much more information on the single cell level than single cell-inductively coupled plasma mass spectrometry (SC-ICP-MS) and, therefore, offers new opportunities in nanotoxicology.
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.
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.
Metastasis is the main cause of death from colorectal cancer (CRC). About 20% of stage II CRC patients develop metastasis during the course of disease. We performed metabolic profiling of plasma samples from non-metastasized and metachronously metastasized stage II CRC patients to assess the potential of plasma metabolites to serve as biomarkers for stratification of stage II CRC patients according to metastasis risk. We compared the metabolic profiles of plasma samples prospectively obtained prior to metastasis formation from non-metastasized vs. metachronously metastasized stage II CRC patients of the German population-based case–control multicenter DACHS study retrospectively. Plasma samples were analyzed from stage II CRC patients for whom follow-up data including the information on metachronous metastasis were available. To identify metabolites distinguishing non-metastasized from metachronously metastasized stage II CRC patients robust supervised classifications using decision trees and support vector machines were performed and verified by 10-fold cross-validation, by nested cross-validation and by traditional validation using training and test sets. We found that metabolic profiles distinguish non-metastasized from metachronously metastasized stage II CRC patients. Classification models from decision trees and support vector machines with 10-fold cross-validation gave average accuracy of 0.75 (sensitivity 0.79, specificity 0.7) and 0.82 (sensitivity 0.85, specificity 0.77), respectively, correctly predicting metachronous metastasis in stage II CRC patients. Taken together, plasma metabolic profiles distinguished non-metastasized and metachronously metastasized stage II CRC patients. The classification models consisting of few metabolites stratify non-invasively stage II CRC patients according to their risk for metachronous metastasis.
Accelerating chemical process development and manufacturing along with quick adaption to changing customer needs means consequent transformation of former batch to continuous (modular) manufacturing processes. These are justified by an improved process control through smaller volumes, better heat transfer, and faster dynamics of the examined reaction systems.
As an example, for such modular process units we present the design and validation of an integrated nuclear magnetic resonance (NMR) micro mixer tailor‐made for a desired chemical reaction based on computational modelling. The micro mixer represents an integrated modular production unit as an example for the most important class of continuous reactors. The quantitative online NMR sensor represents a smart process analytical field device providing rapid and non‐invasive chemical composition information without need for calibration. We describe the custom design through computational fluid dynamics (CFD) for the demands of the NMR sensor as well as for the given reaction conditions. The system was validated with an esterification reaction as an example for a chemical reaction process.
Systems utilizing such an online NMR analyser benefits through short development and set‐up times based on “modular” spectral models. Such models can simply be built upon pure component NMR spectra within minutes to a few hours (i.e., assignment of the NMR signals to the components) instead of tedious DoE calibrations runs. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). The approach was validated for typical industrial reactions, such as hydrogenations or lithiations.
This work wants to show the benefit of NMR spectroscopy as online analytical technique in industrial applications for improving process understanding and efficiency. Especially development and set‐up times based on “modular” data analysis models will enable new production concepts, which are currently discussed with respect to digitization of process industry.
PANIC is the ideal forum for such discussions in the application of NMR spectroscopy and its data analysis to the everyday problems in process industry.
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.
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.