Chemische Charakterisierung und Spurenanalytik
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Eingeladener Vortrag
- nein (98)
Messergebnisse in der chemischen Analyse müssen vergleichbar sein. Dies wird durch die metrologische Rückführbarkeit (traceability) auf SI realisiert. In der Chemie dienen Reinststoffe als Primärnormale, deren Reinheit mit einer Unsicherheit von < 0.01% ermittelt werden soll. Ein eleganter Weg, die Reinheit eines realen Materials mit hoher Präzision zu bestimmen, ist, alle Verunreinigungen zu messen, diese aufzusummieren und von der idealen Reinheit von 100 Prozent abzuziehen. Die metallischen Verunreinigungen in Metallen lassen sich mittels hochauflösender Massenspektrometer ermitteln. Eine weit größere Herausforderung ist die Bestimmung von Nichtmetallen wie Sauerstoff, Wasserstoff und Stickstoff im Metall, zumal diese auch oft die Hauptverunreinigung darstellen. Für die quantitative Bestimmung von Verunreinigungen wurden mit Standards dotierte Pulverpresslinge und mit H, O und N dotierte, gesinterte Materialien auf ihre Eignung als Kalibrierstandards für die GD-OES und GD-MS untersucht. Dabei kamen unterschiedliche Plasmabedingungen (pulsed/ continuous mode; verschiedene Plasmagase) zum Einsatz. Ein Überblick über analytische Kenngrößen und Grenzen der verwendeten Kalibrierstrategien wird gegeben.
Digital holographic cytometry (DHC) is a state-of-the-art quantitative Phase imaging (QPI) method that permits time-lapse imaging of cells without induced cellular toxicity. DHC platforms equipped with semi-automated image segmentation and analysis software packages for assessing cell behavior are commercially available. In this study we investigate the possible uptake of nanoprobes in macrophages in vitro over time.
Single-particle inductively coupled plasma mass spectrometry (sp-ICP-MS) has become an effective tool for the detection and quantification of inorganic nanoparticles (NPs). While sizing of NPs suspended in water is relatively straightforward by sp-ICP-MS, accurate mass quantification of NPs in complex media, such as consumer products and natural systems still remains a challenge. When NPs are suspended in a complex medium, the matrix may affect the analyte sensitivity and lead to inaccurate NP sizing. Here, we investigate the use of an online microdroplet calibration system to size NPs in a single step. In this setup, microdroplets—which are used as the calibrant to determine elemental sensitivities—and nebulized NP-containing solutions are introduced concurrently into the ICP via a dual-inlet sample introduction system. Because calibrant microdroplets and analyte NPs experience the same plasma conditions, both the microdroplets and the NPs are subjected to the same matrix-related signal enhancement or suppression. In this way, the microdroplet calibration standards are automatically matrix matched with the NP-containing solution. The online microdroplet calibration system is combined with an ICP-TOFMS instrument for simultaneous measurement of multiple elements in microdroplets and NPs. We investigate the ability of online microdroplet calibration to compensate for matrix effects through a series of experiments, in which Ag and Au NPs are measured with variable plasma-sampling positions, varying concentrations of HCl and HNO3, varying concentrations of single element solutions, and high concentrations of a salt matrix, i.e. phosphate buffered saline (PBS). Through these experiments, we demonstrate that the online microdroplet calibration strategy provides a matrix-independent mass quantification of analyte NPs in the presence of several established types of matrix effects, including acid effects, space-charge effects, and ionisation suppression. In results presented here, we focus on the size determination of the NPs.
Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is nowadays an established multi-elemental analysis and mapping technique. It was shown that LA-ICP-MS can visualize the elemental distribution within tissue thin sections or cell samples. Quantification is possible by using appropriate matrix-matched calibration samples. Besides naturally occurring elements and metals from contrast agents, biomolecules using metal-tagged antibodies were detected in different bio-medical samples. By combining the results with findings from histology, magnetic resonance imaging (MRI) and other techniques disease related changes like alterations of the extracellular matrix can be investigated.
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.
Two mixtures of polystyrene nanoparticles (PS-NPs) with comparable core sizes (20 nm and 50 nm) 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 and can obviouly improve separation resolution.
Screening of one-bead-one-peptide libraries is a powerful analytical tool for the identification of protein ligands. However, the traditional peptide screening procedure involves tedious steps such as manual selection, sequencing, and characterization. We present a high-throughput “all in one chip” system, allowing the screening of a high number of resin beads in short time. Here, beads of a combinatorial one-bead one compound peptide library are immobilized on an in-house produced chip, on which every bead has a well-defined position. The chip is then incubated with a fluorophore-labeled protein, identifying suitable peptides by a high-resolution fluorescence scan. The screening is followed by MALDI-MS experiments directly on the respective glass chip. To circumvent the need for peptide fragmentation normally used for peptide de novo sequencing, which can result in incomplete sequence information, an approach based on ladder sequencing has been used. This allows the peptide sequence identification by fragmentation-free MS with almost 100 % accuracy. For this purpose, a software tool was developed automatically translating MALDI-MS spectra into the corresponding peptide sequences.
Si isotope fractionation during BIF formation – inferences from a modern Archean ocean analogue
(2019)
Silica-rich sedimentary rocks like cherts and BIFS, typical for the Archean, have been used to reconstruct temperatures and other properties of the early oceans through the study of their Si isotope variations. Precambrian cherts and BIFS span a δ30Si range of ~7‰, with BIFs being about 2‰ lower in δ30Si than cherts. These lower δ30Si signatures have been attributed to represent contributions from different input sources such as hydrothermal fluids, variable continental weathering regimes or sorption onto Fe oxides/hydroxides [e.g. 2 and references therein]. In this study, fluids and BIF-like sediments have been investigated for their Si isotope compositions in Paulina Lake (PL), a hydrothermally-influenced crater lake in the Newberry Caldera, Oregon, USA. PL lake sediments are rich in silica (~65wt% SiO2) and are composed of up to 22.5wt% Fe2O3, which is comparable to Archean BIFs and thus serve as a modern Archean ocean analogue. We compared our analyses with East Lake (EL), the twin Newberry crater lake without hydrothermal input. Dissolved Si in EL has an average δ30Si signature of +1.55±0.16‰ (1sd) and sediments an average δ30Si signature of +0.18±0.28‰ (1sd). Dissolved Si in PL has an average δ30Si signature of +2.02±0.15‰ (1sd), whereas the sediments show a large range in δ30Si values between +0.59‰ and -1.24‰. PL sediments show a trend towards more negative δ30Si with increasing Fe2O3 contents. The magnitude of Si isotope fractionation thus appears to depend on the presence of Fe. This fractionation induced by interaction with Fe precipitation is defined here as the offset in δ30Si between PL and EL sediments at comparable depths (Δ30SiPL-EL). The resulting Δ30SiPL-EL values range between +0.69 and -1.42‰ and increase with increasing Fe2O3 content in the sediments. Our results are the first to quantify the magnitude of Fe-induced δ30Si fractionation observed in a natural analogue of the Archean ocean and can explain the lighter δ30Si signatures found in BIFs.
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 are not only found in food products (chicken and eggs) but also in the environment (manure, soil or 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 and to predict TPs of MON. 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 methods such as Fenton reaction, photochemical and hydrolysis experiments as well as metabolism tests with microsomes. 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.
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.
Die NMR-Spektroskopie stellt heutzutage eine der wichtigsten Analysenmethoden in der organischen Chemie dar. Während der Großteil aller Untersuchungen qualitativ mit dem Ziel der Stoffidentifikation und Strukturaufklärung erfolgt, erlangt die quantitative NMR-Spektroskopie (qNMR) zunehmend an Bedeutung in Forschung und Industrie. Der entscheidende Vorteil gegenüber anderen Analysenmethoden liegt in der direkten Proportionalität der Signalfläche zur Anzahl Kernspins im Messvolumen. Dies erlaubt eine kalibrationsfreie Relativquantifizierung. Zur Absolutquantifizierung reicht die Zugabe einer definierten Menge eines vom Analyten unabhängigen NMR-Standards aus.
Trotz dieser Vorteile findet sich die qNMR bislang nur vereinzelt in Normen und Standardverfahren wieder. Zahlreiche Ringversuche in Metrologie und Industrie demonstrieren die Leistungsfähigkeit moderner NMR-Spektrometer und stärken das Vertrauen in die Methode. Die Entwicklung von Validierungskonzepten, sowie die kommerzielle Verfügbarkeit geeigneter zertifizierter Referenzmaterialien erleichtern die Anwendung, insbesondere im zumeist stark regulierten industriellen Umfeld.
Neben etablierten Hochfeld-NMR Spektrometern hat sich in den letzten Jahren ein stark wachsender Markt für kompakte Benchtop-NMR Geräte auf Permanentmagnetbasis entwickelt. Die geringeren Anschaffungs- und Betriebskosten, sowie die einfache Bedienbarkeit erlaubt es auch kleineren Unternehmen in diese Analysenmethode einzusteigen. Weiterhin besteht die Möglichkeit diese mobilen Systeme näher an die Produktion zu bringen, welches von der klassischen Qualitätskontrolle bis hin zur Online-Prozesskontrolle als vollautomatisierter Analysator reicht. Die geringere Feldstärke der Systeme erfordert hier oft den Einsatz modellbasierter Ansätze zur Spektrenauswertung (z.B. Indirect Hard Modeling).
Dieser Beitrag gibt eine Übersicht über aktuelle Anwendungen und Entwicklungen der qNMR von der universellen, hochgenauen Labormethode bis hin zur robusten Anwendung als Online-Analysator im Feld.
Um in einem veränderten Umfeld erfolgreich bestehen zu können, müssen Chemie-unternehmen neue Pfade beschreiten. Dazu gehört insbesondere das Potential digi-taler Technologien. Mit flexiblen, modularen chemischen Vielzweck-Produktionsanlagen lassen sich häufig wechselnde Produkte mit kürzeren Vorlauf- und Stillstandzeiten zwischen den Kampagnen und dennoch hoher Qualität realisie-ren. Intensivierte, kontinuierliche Produktionsanlagen erlauben auch den Umgang mit schwierig zu handhabenden Substanzen.
Grundvoraussetzung für solche Konzepte ist eine hochautomatisierte "chemische" Prozesskontrolle zusammen mit Echtzeit-Qualitätskotrolle, die "chemische" Informati-onen über den Prozess bereitstellt. In einem Anwendungsbeispiel wurde eine phar-mazeutische Lithiierungsreaktion aus einer modularen Pilot-Anlage betrachtet und dabei die Vorzüge eines vollautomatischen NMR-Sensors untersucht. Dazu wurde ein kommerziell erhältliches Benchtop-NMR-Spektrometer mit Permanentmagnet auf die industriellen Anforderungen, wie Explosionsschutz, Feldkommunikation und voll-automatischer, robuster Datenauswertung angepasst. Der NMR-Sensor konnte schließlich erfolgreich im vollautomatischen Betrieb nach fortschrittlichen Regelkon-zepten und für die Echtzeitoptimierung der Anlage getestet werden. Die NMR-Spektroskopie erwies sich als hervorragende Online-Methode und konnte zusammen mit einer modularen Datenauswertung sehr flexibel genutzt werden. Die Methode konnte überdies als zuverlässige Referenzmethode zur Kalibrierung konventioneller Online-Analytik eingesetzt werden.
Zukünftig werden voll integrierte und intelligent vernetzte "smarte" Sensoren und Pro-zesse eine kontinuierliche Produktion von Chemikalien und Pharmazeutika mit ver-tretbaren Qualitätskosten möglich machen.
Increasing numbers of implant revisions are a current clinical issue. Interactions of the endoprosthesis biomaterial with the body affect implantation time by wear processes, i.e. corrosion and abrasion. Previously, cobalt-chrome implants were shown to cause high levels of cobalt ions being deposited in the bone matrix. To determine a poten- tial functional role of these ions on bone homeostasis, we have developed a non-destructive dual analysis of highly sensitive elemental analysis by synchrotron XRF directly in undecalcified histological bone thin sections (4 μm). In this study, samples from 28 bone samples from hip endoprosthesis carriers (Surface Replacement Arthroplasty, metal-on-metal bearing) with an implant lifetime of 17–1750 days were used. Results were compared to age- matched control specimens. The histological analysis identified areas of bone cell activity and assigned them for XRF measurements. Co-Cr wear particles were identified in the bone marrow. In addition, Co ions were highly enriched in the mineralized bone matrix. The cobalt deposits were not homogeneously distributed, and areas of high signal intensity were identified. Co was distinctly deposited in the newly formed osteoid layer, but also within deeper layers of the bone matrix, whereby the Co concentration increased with higher degrees of bone matrix mineralization. In the current study, we determined cobalt accumulations in the bone matrix and showed for the first time via synchrotron XRF with a high spatial resolution direct on histological slides, that cobalt deposits in the mineralized bone matrix in a mineral-specific way that is dependent upon the implant lifetime.
Carrier gas hot extraction (CGHE) is a commonly applied technique for determination of hydrogen in weld joints using a thermal conductivity detector (TCD) for hydrogen measurement. The CGHE is based on the accelerated hydrogen effusion due to thermal activation at elevated temperatures. The ISO 3690 standard suggests different specimen geometries as well as necessary minimum extraction time vs. temperature. They have the biggest influence on precise hydrogen determination. The present study summarizes the results and experience of numerous test runs with different specimen temperatures, geometries (ISO 3690 type B and small cylindrical samples), and factors that additionally influence hydrogen determination. They are namely specimen surface (polished/as-welded), limited TCD sensitivity vs. specimen volume, temperature measurement vs. effects of PI-furnace controller, as well as errors due to insufficient data assessment. Summarized, the temperature is the driving force of the CGHE. Two different methods are suggested to increase the heating rate up to the desired extraction temperature without changing the experimental equipment. Suggestions are made to improve the reliability of hydrogen determination depended on the hydrogen signal stability during extraction accompanied by Evaluation of the recorded data. Generally, independent temperature measurement with dummy specimens is useful for further data analysis, especially if this data is used for calculation of trapping kinetics by thermal desorption analysis (TDA).
Xenobiotics and their reactive metabolites are conjugated with native biomolecules such as glutathione and glucoside during phase II metabolism. Toxic metabolites are usually detoxified during this step. On the other hand, these reactive species have a potential health impact by disrupting many enzymatic functions. Thus, it is crucial to understand phase II conjugation reactions of xenobiotics in order to address their fate and possible toxicity mechanisms.
Additionally, conventional methods (in vivo and in vitro) have limitation due to matrix complexity and time-consuming. Hence, developing fast and matrix-free alternative method is highly demandable. In this work, oxidative phase I metabolites and reactive species of chlorpyrifos (insecticide) and fluopyram (fungicide) were electrochemically produced by using a boron-doped diamond electrode coupled online to electrospray mass spectrometry (ESI-MS). Reactive species of the substrates were trapped by biomolecules (glutathione and glucoside) and phase II conjugative metabolites were identified using liquid chromatography (LC)-MS/MS, and/or Triple time of flight (TripleTOF)-MS. Glutathione conjugates and glucosylation of chlorpyrifos, trichloropyridinol, oxon, and monohydroxyl fluopyram were identified successfully. Glutathione and glucoside were conjugated with chlorpyrifos, trichloropyridinol, and oxon by losing a neutral HCl. In the case of fluopyram, its monohydroxyl metabolite was actively conjugated with both glutathione and glucoside. In summary, seven bioconjugates of CPF and its metabolites and two bioconjugates of fluopyram metabolites were identified using electrochemistry (EC)/MS for the first time in this work. The work could be used as an alternative approach to identify glutathione and glucosylation conjugation reactions of other organic compounds too. It is important, especially to predict phase II conjugation within a short time and matrix-free environment.
A goal of this work is to extend the model, which was initially developed for laser induced plasmas, to plasmas used in chemical reactors, in particular, the inductively-coupled-RF discharge plasma. The model predicts equilibrium chemical compositions of reaction mixtures as functions of plasma temperature and stoichiometry of reactants. The mixtures investigated are BCl3/H2/Ar and BF3/H2/Ar where Ar serves as the plasma-forming gas and H2 as a binding agent which binds the active species Cl and F and Cl- and F-containing intermediates to produce gaseous B and its condensate. An additional goal is to obtain information about intermediate reaction products for different ratios of BCl3/H2 and BF3/H2 and at different temperatures and different Ar flow rates.
It is found that the desired components B and B2 appear at appreciable concentrations of >0.1% and ~0.01% respectively only at temperatures above 3000 K. It is also established that the effect of charged species on the reaction products is miniscule for temperatures below 5000 K. The expected yield of boron as a function of the original mole fraction H2/BCl3 and H2/BF3 is calculated. The mole fractions are varied in the range 0.1-1000 and the temperature in the range 1000-10000 K. It is shown that the yield of boron increases with increasing the molar ratio H2/BCl3 and H2/BF3 up to ~100 in the temperature range 2000-5000 K. At higher temperatures, T>5000 K, the boron concentration reaches its maximum and does not depend on the concentration of hydrogen; all molecules dissociate and chemical reactions proceed only between charged particles (mostly elemental ions) and electrons. The calculated plasma parameters and composition are compared with experimental data obtained by optical emission spectroscopy. The calculated plasma temperature and electron density are shown to be in good agreement with the measured ones.
High purity halides of III-VI group elements, especially chloride and fluorides, are used in gas phase technologies for obtaining high purity materials and coatings. The reduction of halides in hydrogen-halide mixtures can be achieved in various discharge plasmas, e.g. inductively coupled, ark, and even laser-induced plasmas. Existing models of such plasmas are not sufficiently accurate to predict a yield of the targeted compounds and to describe the plasma processes involved in formation of these compounds. Besides, a construction of costly plasma-chemical reactors can be alleviated by the prior modeling of plasma processes that may occur in such reactors.
A goal of this work is to extend the model, which was initially developed for laser induced Plasmas, to plasmas used in chemical reactors, in particular, the inductively-coupled-RF discharge Plasma. The model predicts equilibrium chemical compositions of reaction mixtures as functions of plasma temperature and stoichiometry of reactants. The mixtures investigated are BCl3/H2/Ar and BF3/H2/Ar where Ar serves as the plasma-forming gas and H2 as a binding agent which binds the active species Cl and F and Cl- and F-containing intermediates to produce gaseous B and its condensate. An additional goal is to obtain information about intermediate reaction products for different ratios of BCl3/H2 and BF3/H2 and at different temperatures and different Ar flow rates.
It is found that the desired components B and B2 appear at appreciable concentrations of >0.1% and ~0.01% respectively only at temperatures above 3000 K. It is also established that the effect of charged species on the reaction products is miniscule for temperatures below 5000 K. The expected yield of boron as a function of the original mole fraction H2/BCl3 and H2/BF3 is calculated. The mole fractions are varied in the range 0.1-1000 and the temperature in the range 1000-10000 K. It is shown that the yield of boron increases with increasing the molar ratio H2/BCl3 and H2/BF3 up to ~100 in the temperature range 2000-5000 K. At higher temperatures, T>5000 K, the boron concentration reaches its maximum and does not depend on the concentration of hydrogen; all molecules dissociate and chemical reactions proceed only between charged particles (mostly elemental ions) and electrons. The calculated plasma parameters and composition are compared with experimental data obtained by optical emission spectroscopy. The calculated plasma temperature and electron density are shown to be in good agreement with the measured ones.
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.
There is a need within the NMR community to progress forward in exploring new facets in which we can use analytical techniques to advance our understanding of various systems. One aspect the NMR community hasn’t fully encompassed is the validation process, which also involves setting reference standards, establishing a common language that directly relates to NMR, communication relating to validation, and much more.
This workshopcontribution starts with an overview on international metrology for qNMR spectroscopy. Since NMR is completely described by mathematical equations, the measurement unceartainty can directly be dreived from formula. Examples are presented. These are differentiated between type A and B evaluations. Finally the Expanded Unceartainty is defined. Since the user needs a risk-based unceartainty assessment, different "leagues" for routine, advanced, and high level needs are proposed to make clear, that no all sources of uncertainty have to be taken in considerention at practical levels.
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.
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.
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.
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.