Chemische Charakterisierung und Spurenanalytik
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Eingeladener Vortrag
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In this talk an overview about artificial intelligence/machine learning applications @BAMline is given. In the first part, the use of neural networks for the quantification of XRF measurements and the decoding of coded-aperture measurements are shown. Then it is shown how Gaussian processes and Bayesian statistics can be used to achieve an optimal alignment of the set-up and in general for optimization of measurements.
Gold is one of the seven metals already known in antiquity and was used from time immemorial as a medium of exchange and for the production of jewelry because of its luster and rarity. In addition, it is easy to work and largely resistant to chemical influences. Investigations of gold using synchrotron radiation excited X-ray fluorescence analysis are non-destructive and provide information about the chemical elements present in the sample under investigation. The investigations presented here at BAMline focus on questions such as the origin, manufacturing process, and association of gold findings. The different questions are explained by a number of examples ranging from the Viking treasure from Hiddensee to the Nebra Sky Disk and finds from Egypt. The find from Bernstorf is discussed in detail. A Bayesian treatment of the authenticity is shown.
n this study, two green synthesis routes were used for the synthesis of Ag/ZnO nanoparticles, using cassava starch as a simple and low-cost effective fuel and Aloe vera as a reducing and stabilizing agent. The Ag/ZnO nanoparticles were characterized and used for bacterial dis-
infection of lake water contaminated with Escherichia coli (E. coli). Characterization indicated the formation of a face-centered cubic structure of metallic silver nanoparticles with no insertion of Ag into the ZnO hexagonal wurtzite structure. Physicochemical and bacteriological analyses described in “Standard Methods for the Examination of Water and Wastewater” were used to evaluate the efficiency of the treatment. In comparison to pure ZnO, the synthesized Ag/ZnO nanoparticles showed high efficiencies against Escherichia coli (E. coli) and general coliforms present in the lake
water. These pathogens were absent after treatment using Ag/ZnO nanoparticles. The results indicate that Ag/ZnO nanoparticles synthesized via green chemistry are a promising candidate for the treatment of wastewaters contaminated by bacteria, due to their facile preparation, low-cost synthesis,and disinfection efficiency.
Fire-gilding is a historic technique for the application of golden layers on a number of different base materials utilizing a gold amalgam. This technique leaves a significant amount of Hg in the golden layer, giving archeometrists a reliable indicator to identify firegildings.
Recent findings on presumably fire-gilded objects have shown in several cases significantly lower Hg content than previously studied objects. This prompted a synchrotron-based X-ray fluorescence investigation into the Hg distribution along the material–gilding interface, as well as a series of measurements regarding the Hg content development in fire-gilded samples during artificial aging. This work presents findings on laboratory-prepared fire-gildings, indicating an Hg enrichment at the interface of firegilded silver samples. Notably, such an enrichment is missing in fire-gilded copper samples. Further, it is confirmed that fire-gilded layers typically do not undercut an Hg bulk content of 5%. In this light, it seems improbable that ancient samples that contain <5% Hg are fire-gilded. The results presented in this study might lead to a non-destructive method to identify the Hg enrichment at the interface. This might be obtained by a combination of different non-destructive measurements and might also work unambiguously in samples in which the gold top layer is altered.
EXAFS analysis of pure elements, binary and ternary equiatomic refractory alloys within the Nb-Zr-Ti-Hf- Ta system is performed at the Nb and Zr K-edges to analyze the evolution of the chemical local environ- ment and the lattice distortion. A good mixing of the elements is found at the atomic scale. For some compounds, a distribution of distances between the central atom and its neighbors suggests a distortion of the structure. Finally, analysis of the Debye-Waller parameters shows some correlation with the lat- tice distortion parameter δ², and allows to quantify experimentally the static disorder in medium entropy alloys.
The vanadium redox flow battery (VRFB) is currently a potential candidate for stationary energy storage. A major challenge is the unintended vanadium transport through the separator, which results in a fade of capacity. To overcome this issue, it is necessary to understand the transport processes in the membrane on a more fundamental level. In this work, the vanadium species distribution in Nafion™ 117 after cyclization was investigated. Two membranes, one from a charged VRFB and another from a discharged VRFB, were analyzed using ultraviolet–visible spectroscopy (UV/VIS) and X-ray absorption near edge structure spectroscopy (XANES). Little difference between the two membranes was recognizable according to the UV/VIS results. In comparison, the XANES results showed that the membrane from the charged VRFB contains more V3+ than VO2+, whereas for the discharged case, more VO2+ is present in the membrane.
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.
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.
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.