Analytische Chemie
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Isotope ratio applications are on the increase and a major part of which are delta measurements, because they are easier to perform than the determination of absolute isotope ratios while offering lower measurement uncertainties. Delta measurements use artefact-based scales and therefore scale conversions are required due to the lack of the scale defining standards. Such scale conversions often form the basis for comparing data being generated in numerous projects andtherefore need to be as accurate as possible. In practice, users are tempted to apply linear approximations, which are not sufficiently exact, because delta values are defined by nonlinear relationships. The bias of such approximations often is beyond typical measurement uncertainties and its extent can hardly be predicted. Therefore, exact calculations are advised. Here, the exact equations and the bias of the approximations are presented, and calculations are illustrated by real-world examples. Measurement uncertainty is indispensable in this context and therefore, its calculation is described as well for determining delta values but also for scale conversions. Approaches for obtaining a single delta measurement and for repeated measurements are presented. For the latter case, a new approach for calculating the measurement uncertainty is presented, which considers covariances between the isotope ratios.
Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis.
Der Bunsen-Kirchhoff-Preis 2022 wurde am 23.06.2022 anlässlich der analytica conference in München an Dr. Carlos Abad verliehen - in Anerkennung seiner exzellenten Entwicklungen im Bereich der continuum source atomic absorption spectrometry (CS-AAS).
Dr. Carlos Abad ist ein herausragender Experte auf dem Gebiet der Atom- und molekularen Absorptionsspektrometrie. insbesondere trug er maßgeblich zur substanziellen Weiterentwicklung von Echelle-Spektrometern für die CS-AAS bei. So gelang es, einen quantitativen Zugang zu Elementen wie Bor, Chlor, Fluor und Schwefel, mittels AAS zu erreichen. Erstmals demonstriert Dr. Carlos Abad am Beispiel eines Zr-Modifier, dass durch die Zeitauflösung der eingesetzten Echelle-Systeme mechanistische Untersuchungen zur Wirkung des Modifiers im Graphitrohrofen möglich sind.
Besonders hervorzuheben sind seine Arbeiten zum Einsatz der CS-AAS für die Analyse von Isotopen, die eine Genauigkeit aufweist, welche an die der Multikollektor-induktiv gekoppelten Plasma-Massenspektrometrie (MC-ICP-MS) heranreicht. Damit ergeben sich völlig neue Einsatzmöglichkeiten für technologisch hochrelevante Applikationen, wie z.B. die Untersuchung der Alterung von Lithium-Batterien oder die Lithium-Analyse in Blutserum.
A new method combining isotope dilution mass spectrometry (IDMS) and standard addition has been developed to determine the mass fractions w of different elements in complex matrices: (a) silicon in aqueous tetramethylammonium hydroxide (TMAH), (b) sulfur in biodiesel fuel, and (c) iron bound to transferrin in human serum. All measurements were carried out using inductively coupled plasma mass spectrometry (ICP–MS). The method requires the gravimetric preparation of several blends (bi)—each consisting of roughly the same masses (mx,i) of the sample solution (x) and my,i of a spike solution (y) plus different masses (mz,i) of a reference solution (z).
Only these masses and the isotope ratios (Rb,i) in the blends and reference and spike solutions have to be measured. The derivation of the underlying equations based on linear regression is presented and compared to a related concept reported by Pagliano and Meija. The uncertainties achievable, e.g., in the case of the Si blank in extremely pure TMAH of urel (w(Si)) = 90% (linear regression method, this work) and urel (w(Si)) = 150% (the method reported by Pagliano and Meija) seem to suggest better applicability of the new method in practical use due to the higher robustness of regression analysis.
In this study, we employed nitrogen microwave inductively coupled atmospheric-pressure plasma (MICAP) combined with quadrupole mass spectrometry (MS) and a liquid sample introduction system to analyze heavy metals in soils. The vanadium, cobalt, nickel, zinc, copper, chromium, arsenic, lead, and cadmium contents in seven reference and three environmental soil samples determined using MICAP-MS were within the uncertainty of the reference values, indicating that MICAP-MS is promising for soil analysis similar to the conventional inductively coupled plasma mass spectrometry (ICP-MS) technique. In addition, the limits of detection (LODs) and sensitivity of both techniques using N2 and Ar plasma were of the same order of magnitude. Furthermore, the performance of MICAP-MS under different N2 purity was investigated, and we found that the plasma formation and ionization efficiency were not influenced by the impurities in the gas. A prominent advantage of MICAP-MS is the low operating cost associated with gas consumption. In this work, MICAP-MS used nitrogen, which is cheaper than argon, and consumed 25% less gas than ICP-MS. Using low-purity N2 can further reduce the gas cost, making MICAP-MS more cost effective than ICP-MS. These results suggest that MICAP-MS is a promising alternative to ICP-MS for the analysis of heavy metals in the soil.
Within this work, the combination of a microdroplet generator and an ICP-ToF-MS for nanoparticle analysis is presented. For the size determination of platinum nanoparticles an on-line isotope dilution analysis approach was developed. The 194Pt/195Pt isotopic ratio was used for the characterization of the particles, while the 182W/183W isotopic ratio was monitored simultaneously for mass bias correction. The on-line ID-MDG-sp-ICP-ToF-MS approach was deployed for the size determination of three platinum nanoparticle samples (50 nm, 63 nm, 70 nm); for validation, complementary size characterization techniques (sp-ICP-ToF-MS and TEM) were used. The robustness of this technique was evidenced, by using sodium chloride concentrations up to 100 mg L−1 as a matrix component. Our new on-line ID MDG-sp-ICP-ToF-MS approach is a promising tool for the fast and reliable determination of nanoparticles' size in severe matrix concentrations, e.g., environmental samples.
The climate and energy crisis are extreme challenges. One possible solution could be hydrogen technology. Safety is a big concern. Steel used for pipelines and storage is under permanent stress from low temperatures and high pressures. The content of different alloyed metals determines the performance of the steel. Nitrogen microwave inductively coupled atmosphere pressure plasma mass spectrometry (N2-MICAP-MS) is a promising method for trace metal analysis in steel. Nitrogen is cheap and can be generated on site. It has fewer interferences than argon. Additionally, MICAP-MS is very matrix tolerant, proving the matrix-matched calibration expendable. Safety in technology and chemistry is the mission of BAM. Providing reference methods and materials can create trust in future technologies like hydrogen.
Thirteen laboratories participated in an international interlaboratory comparison for the determination of 87Sr/86Sr isotope ratios in four cement reference materials (RM) using the conventional method for 87Sr/86Sr isotope ratios analyses. Sample dissolution and Sr isolation via ion exchange chromatography were required since the cement samples were distributed as powders. Analytical preparation included the use of various digestion methods including mixed mineral acids, microwave/acid, bomb/acid digestion or borate fusion, followed by Sr separation using ion exchange chromatography. In this study, we evaluated whether any statistically significant differences were attributable to instrumental differences (i.e., MC-ICP-MS and MC-TIMS), or to laboratory-specific techniques (different sample preparation techniques, Sr isolation and the procedures for correcting the data outputs). To evaluate these effects, consensus values for cement RMs and associated standard uncertainties were estimated by fitting a linear, Gaussian mixed effects model using the R function “lmer” defined in package “lme4”. No statistically significant effects (SSE) attributable to instrumental differences regardless of whether the materials are considered together or separately were evident. There were SSE attributable to differences between laboratories for three cement RMs when the individual cements were considered separately. Since consideration or disregard for such differences does not induce significant changes in the estimate of the consensus values for the 87Sr/86Sr isotope ratios in cement RMs, these effects can safely be neglected when calculating the best estimates for the true values of 87Sr/86Sr isotope ratios in these RMs.
Near-infrared (NIR) spectroscopy is a promising candidate for low-cost, nondestructive, and high-throughput mass quantification of micro¬plastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermo-analytical approaches commonly used for this type of analysis. This study shows how the application of NIR spectroscopy for mass quantification of microplastics can be extended to smaller analyte levels by combining it with a simple and rapid microplastic enrichment protocol. For this purpose, the widely used flotation of microplastics in a NaCl solution, accelerated by centrifugation, was chosen which allowed to remove up to 99 % of the matrix at recovery rates of 83–104 %. The spectroscopic measurements took place directly on the stainless-steel filters used to collect the extracted particles to reduce sample handling to a minimum. Partial least squares regression (PLSR) models were used to identify and quantify the extracted microplastics in the mass range of 1–10 mg. The simple and fast extraction procedure was systematically optimized to meet the requirements for the quantification of microplastics from common PE-, PP-, and PS-based packaging materials with a particle size < 1 mm found in compost or soils with high natural organic matter content (> 10 % determined by loss on ignition). Microplastics could be detected in model samples at a mass fraction of 1 mg g-1. The detectable microplastic mass fraction is about an order of magnitude lower compared to previous studies using NIR spectroscopy without additional enrichment. To emphasize the cost-effectiveness of the method, it was implemented using some of the cheapest and most compact NIR spectrometers available.
Integrierte und vernetzte Systeme und Prozesse – Eine Perspektive für die smarte Laborinfrastruktur
(2022)
Chemie- und Pharmaunternehmen müssen neue Wege gehen, um in einem sich wandelnden Umfeld erfolgreich zu überleben, und gleichzeitig flexiblere Wege der Produkt- und Prozessentwicklung finden, um ihre Produkte schneller auf den Markt zu bringen - vor allem hochwertige High-End-Produkte wie Feinchemikalien oder Arzneimittel. Dazu gehört auch das Potenzial der digitalen Technologien, um ein umfassenderes Wissensmanagement zu ermöglichen.
Eine wichtige Wissensquelle sind analytische Labors, die Unternehmensweit aktiv sind – von F&E bis zur Produktion. Die ganzheitliche Einbindung von analytischen Labors und ein unternehmensweites Daten- und Wissensmanagement sind wichtige Bausteine zur Integration und Vernetzung aller Systeme und Prozesse. Das Potenzial von Daten aus der Produktion mit ihren Kontextinformationen wird heute oft noch nicht konsequent für ein umfassendes Verständnis der Produktion genutzt.
Dieser Beitrag skizziert anhand von Beispielen einen möglichen ganzheitlicheren Ansatz zur Digitalisierung und zum Einsatz maschineller Verfahren in der Produktion von Spezialchemikalien und Pharmazeutika durch die Einführung integrierter und vernetzter Systeme und Prozesse.
Chemical and pharmaceutical companies need to find new ways to survive successfully in a changing environment, while finding more flexible ways of product and process development to bring their products to market faster - especially high-value, high-end products such as fine chemicals or pharmaceuticals. This is complicated by changes in value chains along a potential circular economy.
One current approach is flexible and modular chemical production units that use multi-purpose equipment to produce various high-value products with short downtimes between campaigns and can shorten time-to-market for new products. Online NMR spectroscopy will play an important role for plant automation and quality control, as the method brings very high linearity, matrix independence and thus works almost calibration-free. Moreover, these properties ideally enable automated and machine-aided data analysis for the above-mentioned applications.
Using examples, this presentation will outline a possible more holistic approach to digitalization and the use of machine-based processes in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
Das europäische Projekt MefHySto befasst sich mit dem Bedarf an großmaßstäblichen Energiespeichern, die für eine Umstellung der Energieversorgung auf erneuerbare Energien erforderlich sind. Eine solche Speicherung ist entscheidend, um Energie zu Spitzenzeiten zu liefern, wenn die erneuerbaren Energiequellen schwanken. Eine mögliche Lösung für die Energiespeicherung ist der großtechnische Einsatz von Wasserstoff. Die messtechnische Rückführbarkeit in der Energieinfrastruktur für die Wasserstoffspeicherung ist dann von entscheidender Bedeutung und eine bessere Kenntnis der chemischen und physikalischen Eigenschaften von Wasserstoff sowie rückführbare Messungen und validierte Techniken unverzichtbar.
Glow discharge optical emission spectroscopy (GD-OES) is a technique for the analysis of solids such as metals, semiconductors, and ceramics. A low-pressure glow discharge plasma is applied in this system, which ‘sputters’ and promotes the sample atoms to a higher energy state. When the atoms return to their ground state, they emit light with characteristic wavelengths, which a spectrometer can detect. Thus, GD-OES combines the advantages of ICP-OES with solid sampling techniques, which enables it to determine the bulk elemental composition and depth profiles. However, direct solid sampling methods such as glow-discharge spectroscopy require reference materials for calibration due to the strong matrix effect.
Reference materials are essential when the accuracy and reliability of measurement results need to be guaranteed to generate confidence in the analysis. These materials are frequently used to determine measurement uncertainty, validate methods, suitability testing, and quality assurance. In addition, they guarantee that measurement results can be compared to recognized reference values. Unfortunately, the availability of certified reference materials suited to calibrate all elements in different matrix materials is limited. Therefore various calibration strategies and the preparation of traceable matrix-matched calibration standards will be discussed.
Machine learning is an essential component of the growing field of data science. Through statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. Therefore, it was tried in our work to combine GD-OES with machine learning strategies to establish a new and robust calibration model, which can be used to identify the elemental composition and concentration of metals from a single spectrum. For this purpose, copper reference materials from different manufacturers, which contain various impurity elements, were investigated using GD-OES. The obtained spectra information are evaluated with different algorithms (e.g., gradient boosting and artificial neural networks), and the results are compared and discussed in detail.
Introduction: The influence of copper, iron and zinc concentrations on the formation of ß-amyloid plaques and neurofibrillary tangles in Alzheimer’s disease (AD) is widely discussed in the community. The results from human and animal studies so far are mixed with some studies showing a correlation and others not. From a number of studies, it is known that disease state and isotopic composition of essential elements can be coupled.
Aim: The aim of the study was to identify changes in element content and isotopic composition in two transgenic mouse models used in AD research compared to their genetic WT relatives and to establish whether element content and isotopic signature between different laboratories is comparable.
Methods: ß-amyloid (5xFAD) and tau overexpressing (L66) mice together with their matching wild-types were bred at dedicated facilities in accordance with the European Communities Council Directive (63/2010/EU). Serum and brain were sampled after sacrifice and the samples distributed among the participants of the study. The tissues were acid digested for total element determination and high-precision isotope ratio determination. Element content was determined by either sector-field or quadrupole-based inductively coupled plasma mass spectrometry (ICPMS). For the determination of isotope ratios multi-collector ICPMS was used.
Results: Total copper content was significantly higher for L66 and their matched WT compared to 5xFAD and WT. Brains of L66 mice contained more Fe in brain than their WT, Zn and Cu were not significantly different between L66 and WT. Whereas 5xFAD mice had a slightly lower Cu and slightly higher Zn concentration in brain compared to WT. The isotopic signature in brain of L66 mice for Fe was different from their controls, whereas Zn isotope ratios were influenced in 5xFAD mice compared to their WT . The Cu isotopic ratio did not seem to be influenced in either strain. In serum, the shifts were less pronounced.
Conclusion: Even though neither Tau-protein nor amyloid precursor protein are known to be metal-dependent / -containing proteins, the overexpression of both influences the Fe, Cu and Zn metabolism in brain and to some extent also in serum as can be seen not only using total element determination but probably more clearly studying the isotopic signature of Fe, Cu and Zn.
Investigation of degradation of the aluminum current collector in lithium-ion batteries by GD-OES
(2022)
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
The use of renewable energy sources, electromobility, and portable
electronics relies on lithium-ion batteries (LIBs). However, one
detrimental effect, which can result in significant performance loss,
is the corrosion of the current collectors caused by the aging
mechanisms, especially in high-energy-density batteries
Glow discharge optical emission spectroscopy (GD-OES) provides
depth profile analysis through sputtering using argon plasma, which
enables the analysis of the corrosion behavior at different depths of
the cathodes.
IRWG strategy update
(2022)
Due to the fast growth of industry and the use of metal-containing compounds such as sewage sludge in agricultural fields, soil pollution associated with heavy metals presents a terrifying threat to the environment. Throughout the world, there are already 5 million sites of soil contaminated by heavy metals1. Some heavy metals pollutants can influence food chain safety and food quality, which in turn affects human health. According to the German Federal Soil Protection and Contaminated Site Ordinance (BBodSchV) 13 heavy metals such as arsenic (As), lead (Pb) and cadmium (Cd) are classified as heavily toxic to human health2. Therefore, elemental analysis and precise quantification of the heavy metals in soil are of great importance.
Inductively coupled plasma mass spectrometry (ICP-MS) emerged as a powerful technique for trace analysis of soil due to its multi-element capability, high sensitivity and low sample consumption. However, despite its success and widespread use, ICP-MS has several persistent drawbacks, such as high argon gas consumption, argon-based polyatomic interferences and the need for complicated RF-power generators. Unlike argon-based ICP, the nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) uses nitrogen as plasma gas, which eliminates high operating costs associated with argon-gas consumption as well as the argon-based interferences3. For the first time, the applicability of MICAP-MS for elemental analysis of environmental soils is investigated in this work. For this purpose, 7 reference- and 3 random soil samples containing vanadium (V), cobalt (Co), zink (Zn), copper (Cu), chrome (Cr), mercury (Hg), As, Pb and Cd are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated using ICP-MS. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Moreover, the performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared.
Boron isotope fractionation in soil-plant systems and its influence on biogeochemical cycling
(2022)
Boron (B) is an essential mineral nutrient for higher plants. Although B plant nutrition is well studied, the B isotope fractionation at the soil-plant interface, within plant metabolism, and its influence on biogeochemical cycling is not fully understood. Boron concentrations and isotope variations (δ11B) of the dicotyledonous plants of Chenopodium album and Brassica napus and their growing soils along a climatic gradient were analyzed to decipher these unresolved issues of the B behavior. The boron concentrations and δ11B values show an increasing trend from roots to leaves for both plants, while a decreasing trend from flower to shell and to seed for Brassica napus. A large boron isotope fractionation occurs within the plants with median Δ11Bleaf-root ≈ +20‰, which is related to different boron transporters and transportation ways. Formation of borate dimerized rhamnogalacturonan II in cell and B(OH)3 transportation in xylem lead to heavier δ11B values from root to stem and leaf while B(OH)4 transportation in phloem lead to lighter δ11B values from flower to shell and seed. Although samples cover a distinct transect with systematically different climatic conditions, Δδ11B within the individual plant compartments and between the bulk plants and the soil available B do not show any systematic variation.
This suggests that B uptake from the soil into Chenopodium album and Brassica napus occurs without a distinct isotope fractionation at the soil-plant interface (median Δ11Bbulkplant-soil = 0.2‰) and plants are able to regulate boron uptake. Both the observed large B fractionation within plant and low or absent B isotope fractionation at the soil-plant interface may have profound implications for the biological and geological B cycle. If this observed boron behavior also exists in other plants, their litters would be an important source for exporting 11B-rich biological material from continental ecosystems via rivers to the global oceans. This may be helpful for the explanation of ocean B cycle and the increasing δ11B values over the Cenozoic.
Compact NMR Spectroscopy in the field: A Versatile Tool for Automated Continuous-Flow Production
(2022)
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 downtimes 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. 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. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
Im Rahmen des EU-Projekts „CONSENS – Integrated Control and Sensing“ wurde ein vollautomatisiertes, gemäß Atmosphère-Explosibles(ATEX)-Regeln zertifiziertes Analysatormodul auf Basis eines kommerziellen Benchtop-Kernspinresonanzspektrometers (Engl. nuclear magnetic resonance, NMR) entwickelt und im Umfeld einer modularen containerbasierten Produktionsanlage validiert. Auf Basis der gewonnenen Daten konnten sowohl eine iterative Optimierung der Prozessparameter erfolgen als auch Referenzdaten für die Kalibrierung eines Nahinfrarot-Spektrometers gewonnen werden.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products.
NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further Process Analytical Technology (PAT) applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated. Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals.
At the end of the article, ideas for solutions are discussed in order to speed up the implementation of new special products from the point of view of process analytics and to network the existing process chains more closely.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products.
NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further Process Analytical Technology (PAT) applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated. Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals.
Chemical and pharmaceutical companies need to find new ways to survive successfully in a changing environment, while finding more flexible ways of product and process development to bring their products to market faster - especially high-value, high-end products such as fine chemicals or pharmaceuticals. This is complicated by changes in value chains along a potential circular economy.
One current approach is flexible and modular chemical production units that use multi-purpose equipment to produce various high-value products with short downtimes between campaigns and can shorten time-to-market for new products. Online NMR spectroscopy will play an important role for plant automation and quality control, as the method brings very high linearity, matrix independence and thus works almost calibration-free. Moreover, these properties ideally enable automated and machine-aided data analysis for the above-mentioned applications.
Using examples, this presentation will outline a possible more holistic approach to digitalization and the use of machine-based processes in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
Modular production involving benchtop NMR Current Application Examples Driven by Digitalization
(2022)
The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI, ENPRO, or MTP naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.
Modular production involving benchtop NMR Current Application Examples Driven by Digitalization
(2022)
The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI, ENPRO, or MTP naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.
Compact NMR Spectroscopy in the field: A Versatile PAT Tool for Production of Specialty Chemicals
(2022)
Companies of chemical industry find themselves more often in a rapidly changing environment, e.g., due to variability of raw material quality or energy costs and efficiency. Process optimization and new process concepts become more and more important. For example, flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds like exothermic reactions with high heat dissipation.
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. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as explosion safety, field communication, and robust evaluation of sensor data. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis approach, which can even serve as reliable reference method for further calibration-dependent PAT applications (e.g., NIR spectroscopy). Based on experiences from these field studies an improved analyzer enclosure setup was developed and built, including the option of a secondary method besides NMR spectroscopy. Integrated control systems allow for a flexible implementation based on the available automation infrastructure at the chemical plant or pilot plant setup. In the future, fully integrated and intelligently interconnecting “smart” PAT systems and processes have the potential speed up the setup of production equipment for chemicals and pharmaceuticals and therefore help to reduce the time-to-market.
Compact NMR Spectroscopy in the field: A Versatile PAT Tool for Production of Specialty Chemicals
(2022)
Chemical companies must find new paths to successfully survive in a changing environment, especially by utilizing the potential of digital technologies. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products.
Therefore, fully automated process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. A commercially available benchtop NMR spectrometer was integrated to the full requirements of chemical production environment such as explosion safety, field communication, and robust evaluation of sensor data. It was used for direct loop advanced process control and real-time optimization of the process. Field studies in modular and conventional production plants show promising results gaining process knowledge. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, fully integrated and interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
Compact NMR Spectroscopy in the field: A Versatile PAT Tool for Production of Specialty Chemicals
(2022)
Chemical companies must find new paths to successfully survive in a changing environment, especially by utilizing the potential of digital technologies. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products.
Therefore, fully automated process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. A commercially available benchtop NMR spectrometer was integrated to the full requirements of chemical production environment such as explosion safety, field communication, and robust evaluation of sensor data. It was used for direct loop advanced process control and real-time optimization of the process. Field studies in modular and conventional production plants show promising results gaining process knowledge. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, fully integrated and interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
Binary photoluminescent semiconductor nanocrystals (quantum dots, QDs) are one of the best studied fluorescent nanomaterials, and their unique optoelectronic properties paved the road to many applications in (bio)nanophotonics, optoelectronics, and photovoltaics. However, concerns related to their toxic constituents like cadmium or lead and the emerging interest in greener chemistry synthesis approaches hamper their future applicability. Interesting alternatives for some applications like biosensing or bioimaging are heavy-metal-free ternary QDs like AgInS2 (AIS), CuInS2 (CIS), and quaternary QDs such as AIS-ZnS (ZAIS). In this context, we explored the effect of ligand denticity on the organic-to-aqueous phase transfer of oleylamine-stabilized ZAIS QDs with the hydrophilic ligands mercaptopropionic acid (MPA), dihydrolipoic acid (DHLA), and 3-mercapto-2,2-bis(mercaptomethyl)propanoic acid (3MPA), bearing mono-, bi-, and trialkyl thiol groups. Spectroscopic studies of the resulting water-dispersible ZAIS QDs revealed a considerable influence of ligand denticity and ligand-to-QD ratio on the spectral position and width (FWHM; full width at half-maximum) of the photoluminescence (PL) bands, the PL quantum yields (PL QY), and the PL decay kinetics. Thiol capping and phase transfer resulted in a loss in PL by at least a factor of 2. The ligand-induced PL quenching observed particularly for ligands bearing two or three thiol groups was attributed to the facilitated formation of surface-bound disulfides. The best colloidal stability under high dilution conditions was observed for 3MPA.
The influence of solvent polarity and surface ligand rigidification on the SWIR emission profile of gold nanoclusters with an anistropic surface was investigated. A strong enhancement of the SWIR emission band at 1200 nm was observed when measuring in different local environments: in solution, in polymer composites, and in solids. SWIR in vivo imaging of mice assisted by deep learning after intravenous administration of these gold nanoclusters provides high definition pseudo-3D views of vascular blood vessels.
Fluorescent semiconductor nanocrystals, also known as quantum dots (QDs), enabled many advancements in biotechnology, photovoltaics, photocatalysis, quantum computing and display devices. The high versatility of this nanomaterial is based on their unique size-tunable photoluminescence properties, which can be adjusted from the visible to the near-infrared range. In contrast to other nanomaterials, QDs made the transition from a laboratory curiosity to the utilization in commercial products, like the QLED television screen or in smartphone displays. The best investigated QDs are composed of heavy metals like cadmium or lead, which is not the best choice in terms of toxicity and environmental pollution. A more promising material is Indium Phosphide (InP), which is also currently used by Samsung, Sony and co. in the QLED displays.
In this contribution, I would like to give you a sneak peek behind the curtains of nanomaterial synthesis and show how this material is produced, how to stabilize their structural properties, and assess their toxicity in environmentally relevant conditions. Furthermore, I would like to present a synthesis method to accomplish the last open challenge in display technology of a blue luminescent LED based on QDs by introducing a new element to the InP QDs.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.
Light-emitting nanoparticles like semiconductor nanocrystals (termed quantum dots, QDs) are promising candidates for biosensing and bioimaging applications based on their bright and stable photoluminescent properties. As high-quality QDs are often synthesized in organic solvents, strategies needed to be developed to render them water-dispersible without affecting their optical properties and prevent changes in postmodification steps like the biofunctionalization with antibodies or DNA. Despite a large number of studies on suitable surface modification procedures, the preparation of water-soluble QDs for nanobiotechnology applications still presents a challenge. To highlight the advantages of surface silanization, we systematically explored the influence of the core/multishell architecture of CdSe/CdS/ZnS QDs and the silanization conditions on the optical properties of the resulting silanized QDs. Our results show that the optical properties of silica-coated CdSe/CdS/ZnS QDs are best preserved in the presence of a thick CdS (6 monolayers (ML)) intermediate shell, providing a high photoluminescence quantum yield (PL QY), and a relatively thick ZnS (4.5 ML) external shell, effectively shielding the QDs from the chemical changes during silica coating. In addition to the QD core/shell architecture, other critical parameters of the silica-coating process, that can have an influence on the optical properties of the QD, include the choice of the surfactant and its concentration used for silica coating. The highest PL QY of about 46% was obtained by a microemulsion silica-coating procedure with the surfactant Brij L4, making these water-dispersible QDs to wellsuited optical reporters in future applications like fluorescence immunoassays, biomedicine, and bioimaging.
Atomically precise gold nanoclusters are a fascinating class of nanomaterials that exhibit molecule-like properties and have outstanding photoluminescence (PL). Their ultrasmall size, molecular chemistry, and biocompatibility make them extremely appealing for selective biomolecule labeling in investigations of biological mechanisms at the cellular and anatomical levels. In this work, we report a simple route to incorporate a preformed Au25 nanocluster into a model bovine serum albumin (BSA) protein. A new approach combining small-angle X-ray scattering and molecular modeling provides a clear localization of a single Au25 within the protein to a cysteine residue on the gold nanocluster surface.
Attaching Au25 to BSA strikingly modifies the PL properties with enhancement and a redshift in the second near-infrared (NIR-II) window. This study paves the way to conrol the design of selective sensitive probes in biomolecules through a ligand-based strategy to enable the optical detection of biomolecules in a cellular environment by live imaging.
This paper discusses the feasibility of a novel strategy based on the combination of bioprinting nano-doping technology and laser ablation-inductively coupled plasma time-of-flight mass spectrometry analysis for the preparation and characterization of gelatin- based multi-element calibration standards suitable for quantitative imaging. To achieve this, lanthanide up-conversion nanoparticles were added to a gelatin matrix to produce the bioprinted calibration standards. The features of this bioprinting approach were com- pared with manual cryosectioning standard preparation, in terms of throughput, between batch repeatability and elemental signal homogeneity at 5 μm spatial resolution. By using bioprinting, the between batch variability for three independent standards of the same concentration of 89 Y (range 0–600 mg/kg) was reduced to 5% compared to up to 27% for cryosectioning. On this basis, the relative standard deviation ( RSD ) obtained between three independent calibration slopes measured within 1 day also reduced from 16% (using cryosectioning ) to 5% (using bioprinting), supporting the use of a single standard preparation replicate for each of the concentrations to achieve good calibration performance using bioprinting. This helped reduce the analysis time by approximately 3-fold. With cryosectioning each standard was prepared and sectioned individually, whereas using bio-printing it was possible to have up to six different standards printed simultaneously, reducing the preparation time from approximately 2 h to under 20 min (by approxi- mately 6-fold). The bio-printed calibration standards were found stable for a period of 2 months when stored at ambient temperature and in the dark.
pH and oxygen are amongst the most important and frequently measured analytes in the life and material sciences, indicating, e.g., diseases and corrosion processes. This includes the optical monitoring of pH in living cells for studying cellular internalization pathways, such as phagocytosis, endocytosis, and receptor ligand internalization with the aid of molecular and nanoscale fluorescent sensors. Nanoparticle (NP)-based sensors, that are labeled or stained with a multitude of sensor dyes, have several advantages as compare to conventional molecular probes like enhanced brightness, i.e., amplified signals, ease of designing ratiometric systems by combining analyte sensitive and inert reference dyes, and increased photostability. Moreover, this can enable the use of hydrophobic dyes in aqueous environments. Versatile templates and carriers for the fabrication of nanosensors by the staining and/or labelling with different fluorophores and sensor molecules or surface functionalized NP like silica (SiO2-NP) and polystyrene (PS-NP) particles provide. Here we present the design of a versatile platform of color emissive nanosensors and stimuli-responsive microparticles for the measurement of pH, oxygen, and other targets utilizing both types of matrices and sets of spectrally distinguishable sensor and reference dyes and their characterization and demonstrate the applicability of representative sensor particle for cellular studies.
Das Ziel der vorliegenden Arbeit war die rekombinante Herstellung der AnFAO in E. coli, welche ursprünglich von A. niger produziert wird, und deren anschließende Anwendung in der Entwick-lung eines Fumonisin- Biosensors für die Lebensmittelanalytik. In Bezug auf die aktuell steigen-den Lebensmittel- und Rohstoffpreise ist die Entwicklung eines Schnelltestsystems zur Detektion von Kontaminationen mit Mykotoxinen besonders gefragt, da zusätzliche Verluste und Kosten verhindert werden können. Für die Herstellung der AnFAO als MBP-Fusionsprotein und Biotin-Fusionsprotein mit zusätzlichem 6x His-Tag wurden die pET-MBP-AnFAO und pRSET-BH6-An-FAO Expressionsvektoren erfolgreich konstruiert. Die lösliche Expression im Cytoplasma wurde von MBP-AnFAO erreicht, wobei die Expression von BH6-AnFAO in inclusion bodies erfolgte und keine Aktivität des Enzyms nachgewiesen wurde. Die Enzymaktivität von MBP-AnFAO wurde im optischen Assay und amperometrisch durch die Detektion von H2O2 ermittelt. Im optischen Assay wurde die maximale spezifische Aktivität von 2,45 U/mg bei 45 °C, einer Enzymkonzentration von 3 μM und 50 μM FB1 erreicht. Generell wurden mit FB1 als Enzymsubstrat höhere Fluoreszenzsig-nale und dementsprechend höhere Enzymaktivitäten als für FB2 beobachtet. Es wurde ein linearer Zusammenhang der Enzymaktivitäten mit der Substratkonzentration beobachtet. Außerdem wurde ein Anstieg der H2O2-Konzentration mit zunehmender Inkubationszeit (bis zu 60 Minuten) erkannt. Des Weiteren wurde der Einfluss des MBP-Fusionsproteins auf die Enzymaktivität des AnFAO untersucht. Dabei wurde anhand von wesentlich geringeren Aktivitäten für AnFAO allein ein eventueller Einfluss des MBP auf dessen Aktivität festgestellt. Ein elektrochemischer Aufbau wurde zur Entwicklung eines Fumonisin- Sensors genutzt. Dazu wurde nachgewiesen, dass FB1 von rekombinant hergestelltem MBP-AnFAO unter Bildung von NH3 und H2O2 zu weniger toxi-schem FB1, dem FPy1, oxidiert werden kann. An der PB/Kohlenstoff-Elektrode, welche sensitiver gegenüber H2O2 und stabiler als die CoPC/Kohlenstoff Elektrode war, wurde die Reduktion des enzymatisch gebildeten H2O2 gemessen. Die Erstellung einer FB1- Kalibriergerade mit FB1- Lösun-gen verschiedener Konzentrationen zeigte, dass das Enzym auch in immobilisierter Form in der Lage ist unterschiedliche Konzentrationen an FB1 zu desaminieren. Dazu gehört auch der Kon-zentrationsbereich unterhalb des festgelegten Grenzwertes von 2,7 μmol/kg für Fumonisin. Die amperometrischen Kurven hierfür wurden an der PB/Kohlenstoff-Elektrode erfolgreich aufge-nommen. Störungen des H2O2- Redoxstroms durch das Enzym, der Enzymsubstrate und der Ne-benprodukte während der amperometrischen Messung wurden ausgeschlossen. Sowohl im opti-schen als auch im amperometrischen Assay wurde ausschließlich das enzymatisch gebildete H2O2 bestimmt.
The 18O/16O ratio of cherts (δ18Ochert) increases nearly monotonically by ~15‰ from the Archean to present. Two end-member explanations have emerged: cooling seawater temperature (TSW) and increasing seawater δ18O (δ18Osw). Yet despite decades of work, there is no consensus, leading some to view the δ18Ochert record as pervasively altered.
Here, we demonstrate that cherts are a robust archive of diagenetic temperatures, despite metamorphism and exposure to meteoric fluids, and show that the timing and temperature of quartz precipitation and thus δ18Ochert are determined by the kinetics of silica diagenesis. A diagenetic model shows that δ18Ochert is influenced by heat flow through the sediment column. Heat flow has decreased over time as planetary heat is dissipated, and reasonable Archean-modern heat flow changes account for ~5‰ of the increase in δ18Ochert, obviating the need for extreme TSW or δ18Osw reconstructions. The seawater oxygen isotope budget is also influenced by solid Earth cooling, with a recent reconstruction placing Archean δ18OSW 5 to 10‰ lower than today. Together, this provides an internally consistent view of the δ18Ochert record as driven by solid Earth cooling over billion-year timescales that is compatible with Precambrian glaciations and biological.
A solvothermal method was used to prepare a series of Yb3+/Tm3+/Ca2+ co-doped NaYF4 nanoparticles with different Ca2+ contents. Strong upconversion blue fluorescence could be observed under 980 nm laser excitation of the samples. The effect of different Ca2+ contents on the luminescence intensity was investigated, and it was found that the UV-vis upconversion luminescence increased and then decreased with an increasing Ca2+ concentration during the increase of the Ca2+ content from 0 mol% to 25 mol%, reaching the strongest fluorescence at 15 mol%, which was up to about 28 times stronger than that without Ca2+ doping. Furthermore, the mechanism was investigated, and it was found that the doping of Ca2+ disrupted the symmetry of the crystal field, resulting in a significant enhancement of the overall fluorescence. Applied to fluorescence intensity ratio thermometry, the absolute and relative sensitivities are as high as 0.0418 K−1 and 2.31% K−1, respectively, with a minimum temperature resolution of 0.0129 K.
The reliable identification and quantitation of phosphorylated amino acids, peptides and proteins is one of the key challenges in contemporary bioanalytical research, an area of particular interest when attempting to diagnose and treat diseases at an early stage. We have developed a synthetic probe for targeting phosphorylated amino acids, based on core–shell submicron-sized particles consisting of a silica core, coated with a molecularly imprinted polymer (MIP) shell. The MIP layer contains a fluorescent probe crosslinker which binds selectively to phosphorylated tyrosine (pY) moieties with a significant imprinting factor (IF) and responds with a "light-up” fluorescence signal. The bead-based ratiometric detection scheme has been successfully transferred to a microfluidic chip format and its applicability to rapid assays has been exemplarily shown by discriminating a pY-terminating oligopeptide against its nonphosphorylated counterpart. Such miniaturised devices could lead to an automated pY or pY N-terminated peptide measurement system in the future. The setup combines a modular microfluidic system for amino acid derivatisation, extraction (by micropillar co-flow) and selective adsorption and detection with the fluorescent MIP core–shell particle probes. A miniaturised optical assembly for low-light fluorescence measurements was also developed, based on miniaturised opto-electronic parts and optical fibres. The emission from the MIP particles upon binding of pY or pY N-terminated peptides could be monitored in real-time.
High polarity analyte(s) in aqueous media: determination of L-PFOA and L-PFOS in ground water
(2022)
The CCQM-K156 comparison was coordinated by TUBITAK UME on behalf of the Organic Analysis Working Group (OAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) for National Measurement Institutes (NMIs) and Designated Institutes (DIs) which provide measurement services in organic analysis under the 'Comité International des Poids et Mesures' Mutual Recognition Arrangement (CIPM MRA).
Perfluoro alkyl substances (PFAS) such as PFOS and PFOA have been used in numerous industrial applications and products. Because of their high stability and resistance to biodegradation, atmospheric photooxidation, direct photolysis and hydrolysis, they are extremely persistent in the environment. The European Union (EU) Water Framework Directive lists PFOS as a priority hazardous substance that poses a significant risk to the aquatic environment. The use of PFOS-containing Aqueous Film-Forming Foams (AFFFs) has been banned since June 2011 in the EU. As relatively water-soluble, effectively non-degradable compounds, PFOS and PFOA migrate to ground water. They are not removed in the conventional drinking water treatment, and therefore cause health risks in polluted areas. The EU Drinking Water Directive and the European Commission has proposed a limit value of 100 ng/L for the sum of 20 PFAS, including PFOS and PFOA.
This study provides the means for assessing measurement capabilities for determination of high polarity measurands in a procedure that requires extraction, clean-up, analytical separation and detection. Successful participation in CCQM-K156 demonstrates measurement capabilities in determining mass fraction of organic compounds, with a molecular mass of 200 g/mol to 700 g/mol, having high polarity pKow -2, in a mass fraction range from 0.5 ng/kg to 500 ng/kg in aqueous media.
Nine NMIs and DIs participated in the CCQM-K156 key comparison. Seven institutes reported their results. SPE was applied in the sample pre-treatment and LC-MS was applied for detection. All participating laboratories applied isotope dilution mass spectrometry (IDMS) techniques for quantification. Participants established the metrological traceability of their results using certified reference materials (CRMs) from NMIs with stated traceability; where commercially available high purity materials were used the purity was determined in-house. The CCQM-K156 results for L-PFOA and L-PFOS range from 2.75 ng/kg to 5.50 ng/kg with a % RSD of 19.5 % for L-PFOA and from 2.04 ng/kg to 4.45 ng/kg with a % RSD of 21.3 % for L-PFOS. The KCRV was assigned using a Hierarchical Bayesian Random Effects Model (HB REM) estimator from the values reported by six of the participants. One participant result of L-PFOS and one result of L-PFOA were excluded from the KCRV for technical reasons. The KCRV was 4.9 ng/kg ± 0.4 ng/kg for L-PFOA and 3.8 ng/kg ± 0.4 ng/kg for L-PFOS. The six institutes that were included in the assignment of consensus KCRV all agreed within their standard uncertainties.
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Asymmetrical Flow Field-Flow Fractionation (AF4), as a cleaning technique, was combined on-line with the multielemental analytical capabilities of an Inductively Coupled Plasma-Time of Flight-Mass Spectrometer (ICP-ToF-MS). In that manner, the heavy ionic matrix effect of untreated cells' samples can be significantly reduced. As a proof of concept, commercial baker's yeast cells were analysed.
Bisphenol A (BPA) is used in Polycarbonate, Polyacrylic resins, Polysulfones, Epoxy resins, and Polyetherimides. It is also used in recycled Polyvinyl chloride [1–3]. BPA has been classified as a substance of very high concern (SVHC) under REACH [4] due to its endocrine disrupting properties. The German competent authorities want to reduce the content of BPA in the environment. Possible substitutes for BPA are Bisphenol B (BPB), Bisphenol E (BPE),
Bisphenol F (BPF), or Bisphenol S (BPS), as they are similar in structure.
BPA-based materials have a wide area of application especially outside. These outdoor applications are exposed to different external influences, including physical, biological, mechanical and chemical influences. This results in damage and aging of the material with leaching or migration into the environment. There, the substance is transformed by various transformation processes. The emerging metabolites and transformation products (TPs) can have different properties than the parent substance. Understanding the fate and behavior of the emerging pollutants is very important.
Therefore, different transformation products of selected bisphenols will be generated and analyzed:
To investigate the fate of different bisphenols in water treatment plants technical transformation products [5] will be generated by chlorination, ozonization, the Fenton reaction, and UV-radiation.
For the investigation of the fate of Bisphenols in surface water global radiation will be simulated with UVA-lamps
Simulation of phase-I-metabolism with an electrochemical cell coupled to mass spectrometry (EC-MS).
Process analytical technology (PAT) is a cross-sectional technology and thus essential for future smart production. While in the past decades, the focus of process optimization strategies was on increasing efficiency, in the future, the focus will be on the sustainability of a production and its products. In addition, products will be increasingly personalized in order to match the property profile exactly to the intended use. PAT is able to provide context-sensitive information at the molecular level for process control. Spectroscopic sensors can determine inline and simultaneously both the chemical composition and its sub-microscopic morphology. The article will focus on the optical spectroscopy and therefore starts with a brief introduction on the basic concepts of molecular spectroscopy. In addition, the particularities of measuring liquids, surfaces, or particulate systems in PAT applications are described. This should enable the reader to select the appropriate method for the specific problem. Many examples from everyday industrial practice illustrate the applications. The areas covered are the manufacturing industry, process and pharmaceutical industry, food industry, as well as biotechnology and medical technology. Future will show that PAT is especially important for applications in the field of medicine (point of care) circular economy (recycling, water–wastewater, etc.). It is important to emphasize that sustainability in industrial production can only be successful with an inter- and transdisciplinary close exchange between the different disciplines.
Unternehmen der Prozessindustrie müssen neue Wege finden, um in einem sich wandelnden Umfeld erfolgreich zu überleben, und gleichzeitig flexiblere Wege der Produkt- und Prozessentwicklung finden, um ihre Produkte schneller auf den Markt zu bringen – insbesondere hochwertige, hochwertige Produkte wie Feinchemikalien oder Arzneimittel. Dies wird zukünftig durch Veränderungen in den Wertschöpfungsketten entlang einer potenziellen Kreislaufwirtschaft erschwert.
Anhand von Beispielen wird in diesem Vortrag ein möglicher ganzheitlicher Ansatz zur Digitalisierung und zum Einsatz maschineller Verfahren in der Produktion von Spezialchemikalien durch die Einführung integrierter und vernetzter Systeme und Prozesse skizziert.
Es wird auch auf die aktuelle Technologie-Roadmap „Prozess-Sensoren 2027+“ eingegangen, die Ende 2021 erschienen ist. Im Zentrum dieser Roadmaps stehen Sensoren zur Erfassung von physikalischen und chemischen Messgrößen mittels spezifischer und unspezifischer Messverfahren, die zur Steuerung und dem besseren Verständnis von Prozessen dienen. Die Roadmap fasst die gemeinsame Technologie- und Marktsicht von Anwendern, Herstellern und Forschungs¬einrichtungen im Bereich Prozess-Sensorik in der verfahrenstechnischen Industrie zusammen. Digitalisierung und Nachhaltigkeit sind übergreifende Kernthemen der künftigen Entwicklung.
Die BAM setzt in ihren analytischen Labors zunehmend Labor-Robotik ein, um gefähliche oder zeitraubende Routineaufgaben zu automatisieren. Durch Automation kann auch die Reproduzierbarkeit solcher Anwendungen erhöht werden.
Im Beitrag werden einige aktuelle Beispiele aus den Analytiklabors diskutiert, wie z. B. die Anwendung für die Herstellung und RFA-Analytik von Gläsern, eine Feinwäge-Robotik für 10-L-Gaszylinder im Rahmen der Herstellung von Primärnormalen oder die Automatisierung von Probenpräsentationen für optische Spektroskopie und chemical Imaging. Auch wird kurz auf den Einsatz von Speicherprogrammierbaren Steuerungen in der modularen Laborautomation und die Virtualisierung von analytischen Laborrechnern eingengangen.