Chemische Charakterisierung und Spurenanalytik
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Mehrere Aspekte wurden im Hinblick auf die Standardisierung eines geeigneten Verfahrens für die Analyse sehr flüchtiger organischer Verbindungen (VVOCs) untersucht. Die Verwendung gasförmiger Standards ist notwendig und es wurde ein stabiles Standardgasgemisch aus 60 Substanzen erfolgreich erzeugt und auf Stabilität und Reaktivität überprüft. Die Eignungsuntersuchung verschiedener Chromatographiesäulen ergab, dass PLOT-Säulen (Porous Layer Open Tubular) für die VVOC-Analytik gut geeignet sind. Für die 60 Analyten wurden Wiederfindungsraten auf mehreren Adsorbenzien und deren Kombinationen bestimmt. Dabei zeigte eine Kombination aus einem graphitierten Ruß und einem Kohlenstoff-Molekularsieb hervorragende Ergebnisse für alle Zielkomponenten. Nachteilig an Kohlenstoff-Molekularsieben ist, dass sie Wasser adsorbieren, was die Analyse beeinträchtigen kann. Zur Wasserentfernung wurden verschiedene Optionen wie das Trockenspülen oder der Einsatz eines Trocknungssystems untersucht.
Die passive Probenahme von VOC (Volatile Organic Compounds) mit Tenax® TA und Thermodesorption GC/MS Analytik ist eine einfache, kosteneffiziente und repräsentative Methode zur Bestimmung der VOC-Konzentrationen in der Innenraumluft. In der Theorie ist die Stoffaufnahme in den Passivsammler nur abhängig vom Diffusionskoeffizienten der Substanz in Luft und der Geometrie des Sammlers (ideale Adsorption). Um sie zu charakterisieren, wird die Aufnahmerate (UR), definiert als Quotient der Massenaufnahme und dem Produkt aus Konzentration und Expositionszeit, verwendet. Viele effektive Aufnahmeraten (UR,eff) unterscheiden sich beträchtlich von idealen (theoretischen) Werten (UR,id). Literaturwerte sind in nationalen und internationalen Normen lediglich für bestimmte Expositionszeiten vorgegeben, während detaillierte Informationen über den zugehörigen Konzentrationsbereich fehlen. Außerdem ist die Anzahl der insgesamt in der Literatur beschriebenen Substanzen begrenzt. Das Ziel der vorgestellten Studie ist es diesen Fundus an Aufnahmeraten zu begutachten und zu prüfen und ihn durch die Bestimmung eigener qualitätsgesicherter Laborwerte zu ergänzen. Die bestimmten Aufnahmeraten werden als akkurat bezüglich ihrer relativen Standardabweichung und Vergleichbarkeit zu Literaturwerten betrachtet und können für Expositionszeiten von 7 Tagen bei Konzentrationen von 50 100 µg/m³ (ca. 100 300 ppm min) empfohlen werden. Die Sieben Tage Aufnahmeraten aus ISO16017 2 und ASTM D6196 sind nicht generell für diesen Zweck geeignet, wie exemplarisch für Benzol gezeigt wurde.
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.
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.
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
The prerequisites for a successful energy transition and the economic use of hydrogen as a clean green energy carrier and for H2 readiness are a rapid market ramp-up and the establishment of the required value chains. Reliable quality and safety standards for innovative technologies are the prerequisite for ensuring supply security, for environmental compatibility and sustainable climate protection, for building trust in these technologies and thus enable product and process innovations.
With the Competence Centre "H2Safety@BAM", BAM is creating the safety-related prere-quisites for the successful implementation of hydrogen technologies at national as well as European level. BAM uses decades of experience in dealing with hydrogen technologies to develop the necessary quality and safety standards.
The presentation will draw a bow from the typical basic tasks of BAM in the field of competence "Sensors, analytics and certified reference materials", such as maintenance and dissemination of the national gas composition standards for calorific value determination as Designated Institute for Metrology in Chemistry within the framework of the Metre Convention, to the further development of measurement and sensor technology for these tasks. For the certification of reference materials, a mostly slow and time-consuming but solid reference analysis is common. With hydrogen and its special properties, completely new requirements are added. In addition, fast and simple online analysis is required for process control, for example to register quality changes, e.g., during load changes or refuelling processes.
ML@BAMLINE
(2021)
In this talk I’ll describe the use of artificial neural networks (ANN) for quantifying X-ray fluorescence (XRF) measurements. The main idea of this talk is to give an overview of the process needed to generate a model that can then be applied to a specific problem.
In XRF, a sample is excited with X-rays and the resulting characteristic radiation is detected to determine elements quantitatively and qualitatively. This is traditionally done in several time-consuming steps. I’ll show the possibilities and problems of using a neural network to realise a "one-click" quantification. This includes generating training data using Monte Carlo simulation and augmenting the existing data set with an ANN to generate more data. The search for the optimal hyperparameters, manually and automatically, is also described. For the case presented, we were able to train a network with a mean absolute error of 0.1% by weight for the synthetic data and 0.7% by weight for a set of experimental data obtained with certified reference materials.