Chemische Charakterisierung und Spurenanalytik
Filtern
Erscheinungsjahr
- 2022 (128) (entfernen)
Dokumenttyp
- Zeitschriftenartikel (48)
- Vortrag (44)
- Posterpräsentation (25)
- Sonstiges (3)
- Buchkapitel (2)
- Beitrag zu einem Tagungsband (2)
- Forschungsdatensatz (2)
- Preprint (1)
- Forschungsbericht (1)
Schlagworte
- BAMline (9)
- ICP-MS (8)
- Imaging (6)
- Laser ablation (6)
- PFAS (6)
- Process Analytical Technology (6)
- Synchrotron (6)
- Fluorine (5)
- Mass Spectrometry (5)
- Mass spectrometry (5)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (93)
- 1.1 Anorganische Spurenanalytik (32)
- 6 Materialchemie (28)
- 1.4 Prozessanalytik (18)
- 1.6 Anorganische Referenzmaterialien (17)
- 1.7 Organische Spuren- und Lebensmittelanalytik (16)
- 4 Material und Umwelt (13)
- 1.8 Umweltanalytik (12)
- 6.3 Strukturanalytik (12)
- 6.6 Physik und chemische Analytik der Polymere (11)
- 4.2 Material-Mikrobiom Wechselwirkungen (8)
- 1.5 Proteinanalytik (7)
- 1.3 Instrumentelle Analytik (6)
- 4.3 Schadstofftransfer und Umwelttechnologien (4)
- 3 Gefahrgutumschließungen; Energiespeicher (3)
- 3.1 Sicherheit von Gefahrgutverpackungen und Batterien (3)
- 6.1 Oberflächen- und Dünnschichtanalyse (3)
- 1.2 Biophotonik (2)
- 5 Werkstofftechnik (2)
- 5.1 Mikrostruktur Design und Degradation (2)
- 6.0 Abteilungsleitung und andere (2)
- 6.5 Synthese und Streuverfahren nanostrukturierter Materialien (2)
- 8 Zerstörungsfreie Prüfung (2)
- 8.0 Abteilungsleitung und andere (2)
- 8.6 Faseroptische Sensorik (2)
- P Präsident (2)
- P.0 Präsident und andere (2)
- S Qualitätsinfrastruktur (2)
- S.1 Qualität im Prüfwesen (2)
- VP Vizepräsident (2)
- VP.1 eScience (2)
- 1.0 Abteilungsleitung und andere (1)
- 4.1 Biologische Materialschädigung und Referenzorganismen (1)
- 6.7 Materialsynthese und Design (1)
- 7 Bauwerkssicherheit (1)
- 7.4 Baustofftechnologie (1)
Paper des Monats
- ja (1)
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.
Soil acts as a final sink for pollutants. Microplastics from different sources such as plastic mulching, littering, compost, sewage sludge, sedimentary deposition, and tyre abrasion are expected to be found in soil. However, representative and comprehensive information is missing on the sources, transport, and fate. Therefore, a reliable analysis method for microplastics in soils needs to be developed.
The presented work describes the development of a procedure for microplastics analysis in soils. A representative sampling based on the on-site conditions and a sample preparation method was established and comprised of a drying step, the separation of microplastic particles > 1 mm, and a density separation for particles < 1 mm. The detection of the large microplastic particles (> 1 mm) was conducted with Attenuated Total Reflection - Fourier Transform infrared Spectroscopy (ATR-FTIR) , while Thermal Extraction Desorption - Gas Chromatography / Mass Spectrometry (TED-GC/MS) was applied for particles < 1 mm, gaining information on the type of polymer and mass fraction. Based on the established method, 14 environmental soil samples ? with different exposure of microplastics from agriculture, industrial sites, roads, and floods were investigated.
Due to the arbitrary microplastic particle distribution among the samples for large microplastics, it was reasoned that the found particles were unrepresentative. In contrast, microplastic particles < 1 mm were discovered in a high mass in soil samples exposed to plastic mulching or fertilization with sewage sludge or compost (0 – 115 mg/kg). On average, microplastic contents detected in soil samples taken from a construction site and an inner-city lake were higher (13 – 238 mg/kg). As expected, microplastic content in soil sampled in proximity to roads was more pronounced in the upper soil layers. In contrast, very remote sampling sites, expectably uncontaminated, did not lead to the detection of microplastic regarding to thermoanalytical detection method.
In a proof of concept experiment several in vivo and in vitro ecotoxicological tests were applied to evaluate the effect of microplastics (tyre abrasion, polystyrene containing hexabromocyclododecane) in natural soils. In summary, while no effects of the examined probes could be detected on higher levels of biological organization after exposures to earthworm E. andrei, significant changes in several oxidative stress related biomarkers were observed.
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.
Aging Mechanisms of Lithium Batteries: How can we make batteries more durable and more sustainable in the future?
Lithium batteries are particularly susceptible to ageing processes. During each charging and discharging process in an electric battery, lithium ions are deposited in the electrodes of the cell like in the pores of a sponge. Over time, however, fractures and cracks occur in the filigree structures. The result: more and more lithium ions no longer fit into the hollow spaces of the „sponge“, instead they accumulate in heaps around the electrodes and hinder the movement of other ions. The performance of the battery decreases.
We present our new project, in which we are developing a fast and cost-effective method with which companies that produce lithium batteries can already assess the ageing behaviour of their batteries in the laboratory.
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.
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.
11 laser printers from 5 manufacturers were purchased in 2017 and tested for their UFP emissions. Size resolved sampling of the emitted particles was done with a 13 stage (30 nm to 10 µm) low pressure cascade impactor. The sampled particles were analysed for their chemical composition by thermal extraction (vaporization at 290°C) followed by GC-MS analysis. High boiling cyclic siloxanes (D10 to D16) were detected as constituents of UFP from laser printers. In comparison to measurements in 2008, aliphatic long-chain alkanes (C22 to C34) were detected additionally as chemical constituents of UFP from most of the tested printers and their amounts were higher than for cyclic siloxanes. Printers of one manufacturer showed very low UPF emissions compared to the other manufacturers.