Chemische Charakterisierung und Spurenanalytik
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Eingeladener Vortrag
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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.
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.
A harmonization of sampling, sample preparation and detection is pivotal in order to obtain comparable data on microplastics (MP) in the environment. This paper develops and proposes a suitable sampling concept for waterbodies that considers different plastic specific properties and influencing factors in the environment.
Both artificial water including defined MP fractions and the discharge of a wastewater treatment plant were used to verify the derived sampling procedure, sample preparation and the subsequent analysis of MP using thermal extraction-desorption gas chromatography - mass spectrometry (TED-GC-MS).
A major finding of this paper is that an application of various particle size classes greatly improves the practical handling of the sampling equipment. Size classes also enable the TED-GC-MS to provide any data on the MP size distribution, a substantial sampling property affecting both the necessary sampling volume and the optimal sampling depth.
In the artificial water with defined MP fractions, the recovery rates ranged from 80 to 110%, depending on the different MP types and MP size classes. In the treated wastewater, we found both Polyethylene and polystyrene in different size classes and quantities.
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.
Boron (B) is an essential micronutrient for plant growth. Lack of valid methods for pretreatment and measurement of δ11B in plant restrict applications of it in the biosphere. Dry ashing, one step cation exchange and micro-sublimation were combined to separate and purify boron (B) in plant tissues. The low procedure blank, high B recovery and the accurate δ11B values of the plant reference materials demonstrate that this method is suitable and valid for B pretreatment and δ11B measurement in plant samples by MC-ICP-MS. Based on this method, the δ11B in different plants (Brassica napus, Chenopodium album L, moss, lichen, and Nostoc commune) was analyzed. For Brassica napus, δ11B increased gradually from root to leaf, and then decreased to rapeseed. For the same parts, the δ11B increased from the lower parts to the higher parts. This variation may be due to the B(OH)3 transporter of NIP6;1 and the incorporation of B into the cell. The reason for lower δ11B values in shell and rapeseed compared to those in leaves presumably is to the preferred Transport of borate in the phloem. The largest δ11B fractionation between leaf and root in Brassica napus and Chenopodium album L was +24.2‰ and +26.6‰, respectively. The large variation and fractionation of δ11B within plants indicates that δ11B is a good tracer to study the B translocation mechanisms and metabolism within plants. The δ11B in Nostoc commune, lichen, and moss showed variations of -4.1‰ to +21.5‰, −9.4‰ to +7.3‰, and −18.3‰ to +11. 9‰, respectively. In the same site, δ11B in different plants ranked Nostoc commune>moss>lichen and δ11B in mosses growing in different environment ranked soil>tree>rock. Rain and soil available B are the main B sources for these plants. The δ11B in Nostoc commune, lichen, and moss may be a useful tracer to study the atmospheric B input. In the future, plants culture experiments under certain environments and studies from molecular level are necessary to decipher the variation of δ11B and fractionation mechanisms within plants.
Extraction, chromatographic separation, and quantification of low-concentration organic compounds in complex matrices are core challenges for reference material producers and providers of calibration services. Evidence of successful participation in formal, relevant international comparisons is needed to document measurement capability claims made by national metrology institutes (NMIs) and designated institutes (DIs). To enable NMIs and DIs to update or establish their claims, in 2014 the Organic Analysis Working Group (OAWG) initiated CCQM-K95.1 "Low-Polarity Analytes in a Botanical Matrix: Polycyclic Aromatic Hydrocarbons (PAHs) in Tea". This was a follow-on comparison from CCQM-K95 which was completed in 2014.
The polycyclic aromatic hydrocarbons (PAHs) benz[a]anthracene (BaA) and benzo[a]pyrene (BaP) are considered priority pollutants by U.S. Environmental Protection Agency and are regulated contaminants in food, pose chromatographic separation challenges, and for which exist well-characterized measurement procedures and standard materials. BaA and BaP in a smoked tea were therefore selected as representative target measurands for CCQM-K95.1. Ten NMIs participated in CCQM-K95.1. The consensus summary mass fractions for the two PAHs are in the range of (50 to 70) ng/g with relative standard deviations of (6 to 10) %.
Successful participation in CCQM K95.1 demonstrates the following measurement capabilities in determining mass fraction of organic compounds, with molar mass of 100 g/mol to 500 g/mol and having polarity pKow −2, in a botanical matrix ranging in mass fraction from 10 ng/g to 1000 ng/g: (1) value assignment of primary reference standards (if in-house purity assessment carried out), (2) value assignment of single and/or multi-component organic solutions, (3) extraction of analytes of interest from the matrix, (4) cleanup and separation of analytes of interest from interfering matrix or extract components, and (5) separation and quantification using gas chromatography or liquid chromatography.
Solutions of organic analytes of known mass fraction are typically used to calibrate the measurement processes used to determine these compounds in matrix samples. Appropriate value assignments and uncertainty calculations for calibration solutions are critical for accurate measurements. Evidence of successful participation in formal, relevant international comparisons is needed to document measurement capability claims (CMCs) made by national metrology institutes (NMIs) and designated institutes (DIs). To enable NMIs and DIs to update or establish their claims, in 2015 the Organic Analysis Working Group (OAWG) sponsored CCQM-K131 "Low-Polarity Analytes in a Multicomponent Organic Solution: Polycyclic Aromatic Hydrocarbons (PAHs) in Acetonitrile".
Polycyclic aromatic hydrocarbons (PAHs) result from combustion sources and are ubiquitous in environmental samples. The PAH congeners, benz[a]anthracene (BaA), benzo[a]pyrene (BaP), and naphthalene (Nap) were selected as the target analytes for CCQM-K131. These targets span the volatility range of PAHs found in environmental samples and include potentially problematic chromatographic separations. Nineteen NMIs participated in CCQM-K131. The consensus summary mass fractions for the three PAHs are in the range of (5 to 25) μg/g with relative standard deviations of (2.5 to 3.5) %.
Successful participation in CCQM-K131 demonstrates the following measurement capabilities in determining mass fraction of organic compounds of moderate to insignificant volatility, molar mass of 100 g/mol up to 500 g/mol, and polarity pKow < −2 in a multicomponent organic solution ranging in mass fraction from 100 ng/g to 100 μg/g: (1) value assignment of primary reference standards (if in-house purity assessment carried out), (2) value assignment of single and/or multi-component organic solutions, and (3) separation and quantification using gas chromatography or liquid chromatography.
Recent recommendations by the Food and Drug Administration1 and the European Medicines Agency2 are to limit the clinical use of linear gadolinium-based contrast agents (GBCAs) due to convincing evidence of deposition in tissues. Macrocyclic GBCA continued to be considered safe, provided that patients have normal renal function. To date, given the low sensitivity of conventional MRI, there has been a debate about the signal increase following the injections of a macrocyclic GBCA.
In this paper, we describe the labelling of antibodies by gold nanoparticles (AuNPs) with diameters of 10 and 60 nm with detection by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Additionally, the AuNPs labelling strategy is compared with commercially available labelling reagents based on MeCAT (metal coded affinity tagging). Proof of principle experiments based on dot blot experiments were performed. The two labelling methods investigated were compared by sensitivity and limit of detection (LOD). The absolute LODs achieved were in the range of tens of picograms for AuNP labelling compared to a few hundred picograms by the MeCAT labelling.