Chemische Charakterisierung und Spurenanalytik
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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.
The structure and composition of ancient gold objects retain information about their long history of manufacture, from the exploitation of the ore to the finishing touches, as well as evidence of their use, deposition, and degradation. By developing an efficient analytical strategy, it is possible to retrieve that information. This chapter sets the necessary foundation 131to explore fully the analytical results presented in the following chapters of this volume. The techniques employed in the analyses of the Egyptian jewellery are described and the analytical parameters provided. For more established techniques, only brief introductions are presented, while more recent developments are presented in greater detail.
X-ray fluorescence imaging is a well-established tool in materials characterization. In this work, we present the adaption of coded aperture imaging to full-field X-ray fluorescence imaging at the synchrotron. Coded aperture imaging has its origins in astrophysics, and has several advantages: Coded apertures are relatively easy to fabricate, achromatic, allow a high photon throughput, and high angular acceptance. Coded aperture imaging is a two-step-process, consisting of the measurement process and a reconstruction step. Different programs have been written, for the raytracing/forward projection and the reconstruction. Experiments with coded aperture in combination with a Color X-ray Camera and an energy-dispersive area detector, have been conducted at the BAMline. Measured samples were successfully reconstructed, and gave a 9.1-fold increase in count rate compared to a polycapillary optic.
Our aim is to develop a simple and inexpensive method for full field X-ray fluorescence imaging.We combine an energydispersive array detector with a coded aperture to obtain high resolut ion images. To obtain the information from the recorded image a reconstruction step is necessary. The reconstruction methods we have developed, were tested on simulated data and then applied to experimental data. The first tests were carried out at the BAMline @BESSY II. This method enables the simultaneous detection of multiple elements,which is important e.g. in the field of catalysis.
News from the BAMline
(2022)
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.
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.
Confocal Micro X-ray fluorescence analysis (μXRF) is a powerful method for the destruction-free investigation of the elemental composition of various samples in three dimensions. Quantitative results rely heavily on the transmission properties of polycapillary optics, used in confocal setups.
Different models for the functional correlation between energy and transmission of a polycapillary half-lens are compared with experimental data, established with a monochromatic confocal laboratory setup [1], as well as Monte-Carlo-Simulations [2]. The effect of the different approaches on quantitative results are compared using well known SRMs, ranging from thick samples to thin layers and structured materials.
Along with this the basic principles for quantitative evaluations of XRF spectra taken with confocal setups are presented, and compared with experimental results.
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.
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 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.
Bundling analytical capacities to understand phase formation in recycling of functional materials
(2019)
Transitioning from combustion engine-driven transportation to e-mobility demands a paradigm shift – from a system geared to maximize energy efficiency (i.e. fuel consumption) to a system that may be constrained by the availability of high technology (critical) metals required for electrical energy storage systems and drives. In the wake of these developments efforts in securing new resources of these metals from recycling of end-of-life products are increasing steadily.
Recycling of Li-Ion batteries has recently been evaluated. The results pinpoint to a critical need for understanding slag Formation and its dependence on metal components like Mn under extreme conditions. This will allow researchers to predict optimal Operation setting and to react quickly to changing market demands (which may be Li or Co at one point but may also shift to Ni or rare earth elements (REE)). The long-term goal is to control the formation of specific phases in slags allowing for a Maximum yield of elements of interest and optimal recovery in the separation processes that follows. The combination of data on the physical micro structure and local chemistry of the multi-Phase products during and after processing will help to understand and derive thermodynamic and kinetic data on its formation.
In this paper we are giving an overview on the analytical challenges and approaches to provide robust data on local element concentration and species (especially Mn which is a common component of next generation Li-ion batteries cathodes), spanning the dimensions from the nanometer scale to the bulk material. The complementary interactions of X-rays and electrons make them ideal probes to collect Interface and “in-depth” information. Before- and -after studies as well as in situ structural changes and Phase (trans)formation, changes in elemental and elemental species (e.g. oxidation state) distribution may be tracked by X-ray diffraction (XRD), X-ray fluorescence microscopy and X-ray Absorption spectroscopy. The application of such advanced analytical tools will not only provide essential clues during early lab-based experiments towards the development of new recycling technologies, but may also be deployed for on-line and in-line monitoring of industrial processes.
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.
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. Zusätzlich werden die modernen Messmethoden vorgestellt, die am Synchrotron heutzutage zur Verfügung stehen.
The Color X-ray Camera CXC or SLcam® is an energy-resolving X-ray camera capable of energy- and space-resolved measurements. It consists of a high-speed CCD detector coupled to a polycapil-lary optic that conducts the X-ray photons from the probe to distinct pixels onto the detector. The camera is capable of fast acquisition of spatially and energy resolved fluorescence images. A dedicated software enables the acquisition and the online processing of the spectral data for all 69696 pixels, leading to a real-time visualization of the elements distribution in a sample. It was developed in a joint project with BAM, IFG Berlin and PN Sensors. In this contribution we will mainly discuss the use of the CXC at our beamline, the BAMline at BESSY II and imaging applications of the CXC from different areas, like biology and archaeometry. Additionally new developments for the use of the detector without optics, like wavelength dispersive detection or 1shot-XANES, will be presented.
X-ray absorption fine structure spectroscopy (XAFS) is a frequently employed technique in order to investigate structural composition and change of chemical compounds such as catalytic species. These structural properties are essential (i) to understand underlying reaction mechanism and (ii) to further improve the design of efficient catalysts.
This investigation is based on a newly developed XAFS setup comprising both time- and lateral-resolved XAFS information simultaneously in a single-shot (S2XAFS). The primary broadband beam is generated by a filter/X-ray-mirror combination (bandpass). The transmitted beam through the sample is diffracted by a convexly bent Si (111) crystal, producing a divergent beam. This, in turn, is collected by an area sensitive detector with a theta to 2 theta geometry. This facile, stable and scanningless setup was tested at the BAMline @ BESSY-II (Berlin, Germany).
This contribution focuses on further experimental optimizations allowing the characterization of supported vanadium oxide (VOx) based catalysts at the lower hard X-ray regime (5 to 6 keV). First S2XAFS measurements of these catalysts are presented herein. Supported VOx catalysts show promising results in the oxidation of methane to formaldehyde.
S2XAFS allows determining the structural composition of the metal (i.e. vanadium) based on a fast and smart setup. It is therefore an ideal tool to identify crucial roles of chemical compounds in catalytic reactions.
XAFS@BAMline
(2018)
X-ray Absorption fine structure spectroscopy (XAFS) is a frequently employed technique in order to investigate structural composition and Change of chemical compounds such as catalytic species or corrosion processes. These structural properties are essential (i) to understand underlying reaction mechanism and (ii) to further improve the design of materials.
While XAFS measurements are usually performed with ionization Chambers or simple fluorescence detectors, we at BAMline specialize in measurements with innovative set-ups that meet Specialrequirements such as time resolution, (3D-) spatial Resolution or demanding sample environments.
This contribution presents various available XAFS configurations with their corresponding applications. In particular, these comprise single -shot XAFS for time- resolved measurements, grazing-exit XAFS with energy and a spatially resolved detector for the characterization of thin films and an in situ grazing incidence Setup for the characterization of corrosion layers.
Additionally,the possibility of analyzing Minute samples in total-reflection geometry is demonstrated.