Chemische Charakterisierung und Spurenanalytik
Filtern
Dokumenttyp
- Vortrag (16)
- Zeitschriftenartikel (5)
- Posterpräsentation (1)
Sprache
- Englisch (15)
- Deutsch (6)
- Mehrsprachig (1)
Schlagworte
- XRF (22) (entfernen)
Organisationseinheit der BAM
- 6 Materialchemie (18)
- 6.3 Strukturanalytik (18)
- 1 Analytische Chemie; Referenzmaterialien (4)
- 1.4 Prozessanalytik (4)
- 1.1 Anorganische Spurenanalytik (3)
- 1.7 Organische Spuren- und Lebensmittelanalytik (3)
- 1.8 Umweltanalytik (3)
- 4 Material und Umwelt (2)
- 4.0 Abteilungsleitung und andere (1)
- 4.1 Biologische Materialschädigung und Referenzorganismen (1)
Eingeladener Vortrag
- nein (16)
Synchrotron radiation X-ray fluorescence spectroscopy, in conjunction with atomic absorption and Raman spectroscopy, was used to analyze a set of top brand tattoo inks to investigate the presence of toxic elements and hazardous substances. The Cr, Cu, and Pb contents were found to be above the maximum allowed levels established by the Council of Europe through the resolution ResAP(2008)1 on requirements and criteria for the safety of tattoos and permanent makeup. Raman analysis has revealed the presence of a set of prohibited substances mentioned in ResAP(2008)1, among which are the pigments Blue 15, Green 7, and Violet 23. Other pigments that were identified in white, black, red, and yellow inks are the Pigment White 6, Carbon Black, Pigment Red 8, and a diazo yellow, respectively. The present results show the importance of regulating tattoo ink composition.
Gegenstand der vorzustellenden Arbeiten ist die Prüfung der Umweltbeständigkeit und -verträglichkeit von Materialien und Produkten hinsichtlich der Emission von potenziellen Schadstoffen in die Umwelt. Hierzu werden chemisch-physikalische Einflüsse (Bewitterung) und mikrobielle Beanspruchungen an Modellmaterialien evaluiert. So werden die Freisetzungsraten von Schadstoffen in Abhängigkeit der Beanspruchung beschrieben. Als Modellmaterialien kommen die Polymere Polystyrol (PS) und Polypropylen (PP) zum Einsatz, die jeweils mit polybromierten Flammschutzmitteln (PBFSM) versehen sind. Synergistische Effekte der Bewitterungsparameter und der mikrobiologischen Beanspruchung sollen dabei ebenso betrachtet werden, wie die gezielte Alterung. Auch findet eine Beschreibung des Verhaltens der ausgetragenen Schadstoffe in den Umweltkompartimenten Boden oder Wasser statt. Hier sind mit Hilfe der zu entwickelnden Screening- und non-Target-Analyseverfahren die Transformation und der Metabolismus durch Mikroorganismen zu beschreiben. Auch soll mit Hilfe der RFA und der LA-ICP-MS die Abreicherung der PBFSM in den Modellmaterialien beschrieben werden. Aus den Ergebnissen sollen Korrelationen zwischen den künstlichen Alterungsverfahren und realen Szenarien abgeleitet werden.
In addition to previously reported results on the accelerated weathering of polystyrene samples (PS) containing 1 wt.% hexabromocyclododecane (HBCD), we present the first results of our investigations of polypropylene samples (PP) containing 0.1 wt.% BDE-209. All studied polymer samples were exposed to a defined weathering schedule in a climate chamber in accordance to regulation EN ISO 4892-3:2006. For the determination of BDE-209 in the collected raining water the samples were prepared in accordance to a validated protocol. Before the analyses each sample was spiked with isotopically labeled BDE-209. Subsequently the samples were extracted with isooctane. The obtained extracts were concentrated, and the resulting solutions were analyzed by GC/MS. Additionally, the total bromine content was monitored for the weathered and untreated samples using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and X-ray fluorescence analysis (XRF) as a non-destructive and rapid method. In general, the resulting data from the accelerated weathering will be compared to those from the natural weathering experiments. Here, the surfaces of the test pieces were analyzed by LA-ICP-MS and XRF as well. Moreover, soil bed tests were conducted in a well characterized model soil. This soil (boulder-clay, sand with 12 % loam, particle size in total 0.2-4 mm) is filled in a free-draining basin inside of an air-conditioned cellar. In this manner, TOC, water capacity and humidity are recorded parameters. To induce a leaching process from the samples by the raining water, the target water content is calculated to 8%. The actual humidity is measured by a tensiometer, assuring the duration of the raining period. A defined humidity is a fundamental parameter for a biological activity in the soil. The test polymers were placed up to the half in the soil. Microbial activity of the soil is monitored by a reference polymer (polyurethane) and should induce the release of HBCD and BDE-209 out of the test materials. These released analytes will be captured by passive samplers (silicone tubes) placed in a distinct distance to the polymer samples in the soil. The soil bed experiments are complementary to the weathering experiments due to the biological activity in the soil.
Gold ist eines der sieben bereits in der Antike bekannten Metalle und wurde wegen seines Glanzes und seiner Seltenheit seit jeher als Tauschmittel und zur Herstellung von Schmuck verwendet. Außerdem ist es leicht zu bearbeiten und weitgehend resistent gegen chemische Einflüsse.
Die Analyse von Gold mit der durch Synchrotronstrahlung angeregten Röntgenfluoreszenzanalyse ist zerstörungsfrei und liefert Informationen über die in der untersuchten Probe vorhandenen chemischen Elemente.
Im Mittelpunkt der hier vorgestellten Untersuchungen an der BAMline stehen Fragen nach der Herkunft, dem Herstellungsprozess und der Zugehörigkeit von Goldfunden. Die verschiedenen Fragestellungen werden anhand einer Reihe von Beispielen erläutert, die vom Wikingerschatz von Hiddensee über die Himmelsscheibe von Nebra bis hin zu Funden aus Ägypten reichen. Darüber hinaus werden die heute am Synchrotron verfügbaren modernen Messmethoden vorgestellt.
To gain insight into the possible origin of the gold used in the production of tesserae containing gold leaf less than 0.5 μm thick placed between two layers of glass, we propose a non-destructive synchrotron radiation (SR) XRF protocol based on sequential analysis under optimised analytical conditions. Using this protocol, trace element analysis is achieved with detection limits of 1–6 mg/kg. As Pt and Au have adjacent fluorescence energies, we tested the most challenging situation, when Pt is present in very low concentrations in gold. Data obtained by double-dispersive XRF (D2XRF) and μXRF for fourth–ninth-century mosaics decorating nine Eastern and Western religious buildings show that the Eastern and Western tesserae are made from different alloys.
However, these alloys are identical to those used to make gold leaf for gilding, because plastic deformation requires the use of gold alloys with high ductility and malleability. Although trace element composition of gold used in the concerned period is only available for coins, by comparing the amounts of Pt contained in the tesserae and in the coins we show that Roman tesserae are made from Roman gold, as described in the documentary sources. We observe for the Byzantine period the use of a Byzantine gold and of gold supposedly from different stages of recycling, and we suggest the use of Umayyad and Abbasid gold for the production of Islamic tesserae.
This contribution provides an overview of the BAMline synchrotron radiation beamline, which specializes in hard X-ray spectroscopy techniques for materials research. The BAMline offers X-ray absorption spectroscopy (XAS), x-ray fluorescence spectroscopy (XRF), and tomography to study materials' electronic structure, chemical composition, and structure. Key capabilities include standard and dispersive XAS for electronic structure, micro-XRF for elemental mapping, coded aperture imaging, and depth-resolved grazing exit XAS. The BAMline enables in situ characterization during materials synthesis and functions for energy, catalysis, corrosion, biology, and cultural heritage applications.
Ongoing developments like the implementation of machine learning techniques for experiment optimization and data analysis will be discussed. For instance, Bayesian optimization is being used to improve beamline alignment and scanning. An outlook to the future, where the BAMline will continue pioneering dynamic and multi-scale characterization, aided by advanced data science methods, to provide unique insights into materials research, will be given.
In this work, we describe the use of artificial neural networks for the quantification of X-ray fluorescence measurements. The training data were generated using Monte Carlo simulation, which avoided the use of adapted reference materials. The extension of the available data set by means of an ANN to generate additional data was demonstrated. Particular emphasis was put on the comparability of simulated and experimental data and how the influence of deviations can be reduced. The search for the optimal hyperparameter, manual and automatic, is also described. For the presented case, we were able to train a network with a mean absolute error of 0.1 weight percent for the synthetic data and 0.7 weight percent for a set of experimental data obtained with certified reference materials.
In X-ray fluorescence (XRF), a sample is excited with X-rays, and the resulting characteristic radiation is detected to detect elements quantitatively and qualitatively. Quantification is traditionally done in several steps:
1. Normalization of the data
2. Determination of the existing elements
3. Fit of the measured spectrum
4. Calculation of concentrations with fundamental parameters / MC simulations / standard based
The problem with standard based procedures is the availability of corresponding standards. The problem with the calculations is that the measured intensities for XRF measurements are matrix-dependent. Calculations must, therefore, be performed iteratively (= time consuming) in order to determine the chemical composition.
First experiments with gold samples have shown the feasibility of machine learning based quantification in principle. A large number of compositions were simulated (> 10000) and analyzed with a deep learning network. For first experiments, an ANN (Artificial Neural Network) with 3 hidden layers and 33x33x33 neurons was used. This network learned the mapping of spectra to concentrations using supervised learning by multidimensional regression. The input layer was formed by the normalized spectrum, and the output layer directly yielded the searched values. The applicability for real samples was shown by measurements on certified reference materials.
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.
Various applications for artificial intelligence in the context of spectroscopy will be presented. in particular, examples from BAMline will be presented. After a short introduction to synchrotron radiation, artificial intelligence algorithms for the quantification of X-ray fluorescence measurement are discussed. In the second example, information retrieval by natural language processing is discussed.