Analytische Chemie
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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.
News from the BAMline
(2022)
Getting more efficient – The use of Bayesian optimization and Gaussian processes at the BAMline
(2022)
For more than 20 years, BAM is operating the BAMline at the synchrotron BESSY II in Berlin Adlershof. During this time, the complexity of the setup and the amount of data generated have multiplied. To increase the effectiveness and in preparation for BESSY III, algorithms from the field of machine learning are increasingly used.
In this paper, several examples in the areas of beamline alignment and measurement time optimization based on Bayesian optimization (BO) with Gaussian processes (GP) are presented. BO is a method for finding the global optimum of a function using a probabilistic model represented by a GP. The advantage of this method is that it can handle high-dimensional problems, does not depend on the initial estimate, and also provides uncertainty estimates.
After a short introduction to BO and GP, the first example is the automatic alignment of our double multilayer monochromator (DMM). To achieve optimal performance, up to three linear and two angular motor positions have to be optimized. To achieve this with a grid scan, at least 100^5 measurement points would be required. Assuming that all positions can be aligned independently, 100*5 points are still necessary. We show that with BO and GP less than 100 points are sufficient to achieve equal or better results.
The second example is the optimization of measurement time in XRF scanning. Here we will show the advantage of the BO GP approach over point-by-point scanning. As can be seen in Fig. 1, the number of points required and thus the measurement time can be reduced by a factor of 50, while the loss in image quality is acceptable. The advantages and limitations of this approach will be discussed.
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.
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.
After a general presentation of the beamline, specifically the workflow for ex-situ CT at BAMline is presented. Although being used in a broad variety of research fields the usual workflow for CT experiments is in most cases similar in terms of sample mounting, tomographic scan and reconstruction. Specific scanning schemes allow for a preview reconstruction carried out during the scan. A detailed description of the used hardware as well as the self-coded programs applied in the data pipeline will be given. This will be accompanied by a practical demonstration of the software involved in the entire process.
After a general presentation of the beamline, specifically the workflow for ex-situ CT at BAMline is presented. Although being used in a broad variety of research fields the usual workflow for CT experiments is in most cases similar in terms of sample mounting, tomographic scan and reconstruction. Specific scanning schemes allow for a preview reconstruction carried out during the scan. A detailed description of the used hardware as well as the self-coded programs applied in the data pipeline will be given. This will be accompanied by a practical demonstration of the software involved in the entire process.
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.
Synchrotron radiation sources with their unique properties in terms of intensity, polarization and adjustability offer a wide range of possibilities in materials research. A basic introduction about the creation and special properties of synchrotron radiation will be given. Examples of current work at BAMline, the high-energy measuring facility of the Federal Institute for Materials Research and Testing at the synchrotron BESSY, are used to illustrate the possibilities and limitations of existing measuring methods.
In this talk, the features of X-ray fluorescence analysis with synchrotron radiation will be presented. First, the basics of the origin of synchrotron radiation and X-ray fluorescence analysis and the experimental setup will be discussed. Then, examples of trace element detection, micrometer resolution, and application of the X-ray color camera will be shown.
Gold ist eines der sieben schon im Altertum bekannten Metalle und wurde wg. seines Glanzes und seiner Seltenheit von alters her als Tauschmittel und zur Herstellung von Schmuck benutzt. Außerdem ist es einfach bearbeitbar und weitestgehend gegen chemische Einflüsse resistent. Die Untersuchungen von Gold mit synchrotronstrahlungsangeregter Röntgenfluoreszenzanalyse sind zerstörungsfrei und geben Auskunft über die in der untersuchten Probe vorhandenen chemischen Elemente. Bei den hier vorgestellten Untersuchungen an der BAMline stehen Fragestellungen wie Herkunft, Herstellungsverfahren und Zusammengehörigkeit von Goldfunden im Vordergrund. Die verschiedenen Fragestellungen werden an einer Reihe von Beispielen erläutert die vom Wikingerschatz aus Hiddensee über die Himmelsscheibe von Nebra bis hin zu Funden aus Ägypten langen. Der Fund von Bernstorf wird ausführlich diskutiert.
Various applications for artificial intelligence in the context of spectroscopy will be presented. in particular, examples from bamline will be featured. 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 reviewed. As a last example the reconstruction of measurements with the X-ray color camera and coded apertures is presented.
Trace elements are chemical elements whose concentration in a material is very low. The exact definition depends on the application and varies for example between 100 micrograms per gram in analytical chemistry and 1000 micrograms per gram in geology. The ability to detect trace elements fast and quantitatively is of great importance in many areas of science and technology. With its high brilliance and flexibility in the excitation conditions, synchrotron radiation is an ideal tool for detecting traces even in small sample quantities. In this contribution I will report about the use of X-ray fluorescence(XRF)for qualitative and quantitative element sensitiveanalysis. In addition to the fundamentals of XRF and its quantification methods, the advantages and problems of different geometries like e.g. microXRF, Total Reflection X-ray Fluorescence (TXRF)or Double Dispersive XRF (D²XRF) will be discussed. Practical examples from BAMline from the research fields of medicine, geology and archaeometry will complete the lecture.
In recent years, we have come to appreciate the astounding intricacy of the processes leading to the formation of minerals from ions in aqueous solutions. The original, and rather naive, ‘textbook’ image of these phenomena, stemming from the adaptation of classical nucleation and growth theories, has increased in complexity due to the discovery of a variety of precursor and intermediate species. These include solute clusters (e.g. prenucleation clusters, PNCs), liquid(-like) phases, as well as amorphous and nanocrystalline solids etc.. Does it, however, mean that all the minerals grow through intermediate phases, following a non-classical pathway?
In general, the precursor or intermediate species constitute different, often short-lived, points along the pathway from dissolved ions to the final solids (typically crystals in this context). In this regard synchrotron-based scattering (SAXS/WAXS/total scattering) appears to be the perfect tool to follow in situ and in a time-resolved manner the crystallization pathway because of the temporal and spatial length scales that can be directly accessed with these techniques. In this presentation we show how we used scattering to probe the crystallisation mechanisms of calcium sulfate, This system contains minerals that are widespread in diverse natural environments, but they are also important in various industrial settings. Our data demonstrate that calcium sulfate precipitation involves formation and aggregation of sub-3 nm anisotropic primary species. The actual crystallisation and formation of imperfect single crystals of calcium sulfate phases, takes place from the inside of the in itial aggregates. Hence, calcium sulfate follows a non-classical pathway.
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.
Synchrotron radiation sources with their unique properties in terms of intensity, polarization and adjustability offer a wide range of possibilities in materials research. A basic introduction about the creation and special properties of synchrotron radiation will be given. Examples of current work at BAMline, the high-energy measuring facility of the Federal Institute for Materials Research and Testing at the synchrotron BESSY, are used to illustrate the possibilities and limitations of existing measuring methods. It will be shown how the formation of corrosion layers can be tracked, how the abrasion of implants leads to the introduction of heavy metals into the surrounding bone matrix and how the detection of smallest impurities in gold is possible by optimizing the measuring conditions. Finally, an outlook at the hardware and software developments to be expected in the coming years is given.
What exactly does a postdoc do at a research institute? What scientific questions does he or she want to address? What is their daily work routine? During our regular Lab Tours, female postdocs provide insight into their jobs. They also tell us about their career path: How did they get there? And what do they envision for their professional future?
This time, Dr. Ana Guilherme Buzanich, a scientist from the Structure Analysis division at the Bundesanstalt für Materialforschung und -prüfung (BAM), will give an overview of her Research areas. She works at the electron storage ring BESSY-II where she conducts experiments at two hard X-ray beamlines (BAMline and µSpot). The tour includes a guided visit of the research facility.