TY - THES A1 - Kulow, Anicó T1 - Spatial Resolved Dispersive X-Ray Absorption Spectroscopy and Coded Aperture X-Ray Fluorescence Imaging N2 - One aim of this work was the development of a new setup for time- and laterally resolved XAFS measurements, based on the pronciple of dispersive XAFS. This setup is scanning free, stable, inexpensive, and straightforward to adjust for probing different elements. The second part of this work describes the impelemntation of a method for full-field X-ray fluorescence imaging with coded apertures. Expensive and complicated X-ray otpics, that are usually used for full-field imaging, are replaced with a coded aperture that consists of many pinholes drilled in an X-ray opaque material. Coded apertures are inexpensive to fabricate, energy independent and easy to use. The working principle is the same as with a pinhole camera, but the multiple holes allow a higher photon flux compared to a single pinhole or even a polycalippary optic, thus alowwing the reduction of measurement time. KW - X-ray fluorescence imaging KW - Coded Apertures KW - X-ray absorption spectroscopy KW - Synchrotron PY - 2021 SP - 1 EP - 175 CY - Berlin AN - OPUS4-52054 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - THES A1 - Cakir, Cafer Tufan T1 - Optimization of depth resolved X-ray absorption spectroscopy in grazing emission mode for characterizing compositionally complex alloys N2 - Layered materials are fundamental to technological advancements, offering distinct properties that differentiate them from bulk materials. In electronics, for instance, thin-film transistors (TFTs) are used to enhance charge transport and flexibility, thereby improving device performance. In the same way, thin-film photovoltaic devices used in renewable energy use strategic layering to absorb light more efficiently and separate electron-hole pairs more effectively, which leads to higher energy conversion efficiency. In recent decades, the development of new alloys has highlighted the importance of layered materials in another context. Compositionally complex alloys, for example, form multiple oxide layers on their surfaces when they oxidize. Studying these corrosion layers is crucial for understanding material-environment interactions. Typical surface analysis techniques, including X-ray photoelectron spectroscopy (XPS), secondary ion mass spectrometry (SIMS), and Meitner-Auger electron spectroscopy (MAES), provide valuable insights but are constrained by their requirements for high Vacuum conditions and their limited depth analysis. In contrast, X-ray absorption near-edge structure (XANES) spectroscopy presents a versatile and advantageous alternative. It operates effectively under ambient conditions and allows time-resolved measurements, enhancing the analysis of materials in real-time as they undergo structural and compositional changes. This adaptability broadens the scope for material analysis, allowing for a more comprehensive understanding of dynamic processes. Grazing Emission X-ray Fluorescence (GEXRF) spectroscopy stands out as a nondestructive, depth-resolved, element-specific characterization technique important for collecting depth-resolved information at the nanometer scale. Its ability to collect in-Depth resolved information based on the grazing emission angle of the fluorescence Radiation makes it ideal for investigating thin films, corrosion layers, and interfaces within layered materials. The integration of XANES in emission mode with GEXRF enables detailed exploration of the chemical states of the analyzed atom and provides depth-resolved information. This study discusses grazing emission X-ray absorption near-edge structure spectroscopy (GEXANES), a novel layer analysis technique that is created by integrating these two methods. This study also innovatively combines machine learning with GEXANES spectroscopy to reduce experimental times. By using active learning, a subset of machine learning, it refines the data acquisition process, enabling more efficient and streamlined methods. The application of active learning in this context illustrates the potential of data-driven approaches to transform experimental methodologies, particularly in resource-limited environments such as synchrotron facilities, thereby accelerating scientific research and discovery. KW - Angle resolved XRF KW - GEXRF KW - BO KW - Active Learning KW - XRF PY - 2025 DO - https://doi.org/10.34726/hss.2025.101302 SP - 1 EP - 129 CY - Technische Univeristät Wien AN - OPUS4-63793 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -