TY - CONF A1 - Cakir, Cafer Tufan A1 - de Oliveira Guilherme Buzanich, Ana A1 - Reinholz, Uwe A1 - Emmerling, Franziska A1 - Streli, C. A1 - Radtke, Martin T1 - Bayesian optimization for depth resolved analysis of complex alloys with grazing exit XANES N2 - Compositionally complex alloys (CCAs) are a new class of alloys containing at least 5 elements with concentrations between 5 and 35 atomic percent. Due to their adjustable composition, which enables modifications of mechanical properties (such as hardness, strength and ductility etc) and their stability at high temperatures, CCAs have been the focus of various studies [1,2]. Especially the corrosion behavior of CCAs has been a wide research interest. However, there are only few studies that deals with the degradation process on such materials, which is highly relevant for the safety aspect for future component design. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Since the grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect notable information regarding the high temperature oxidation, we consider it as a useful method to investigate how CCAs behave in corrosive environments. The main idea of grazing geometry is to enhance the fluorescence signal of the surface. This enables highly sensitive surface analyses of thin protective film on surface in sub-micrometer scale [3]. When compared to a conventional CCD-based camera, the advantage and most important feature of the detector system (Color X-Ray Camera (CXC)) is that each pixel is an energy sensitive detector. The position and area sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states. In this contribution, we address the feasibility of our setup and new optimization procedure (Bayesian Optimization and Gaussian Regression). The results of a conceptual study regarding layer properties of the reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer) and CrCoNi (Cr-Oxide (>1µm) layer on CrCoNi substrate) medium entropy alloy. T2 - European Conference on X-ray Spectrometry. EXRS 2022 CY - Bruges, Belgium DA - 26.06.2022 KW - GEXRF KW - High entropy alloys KW - XANES KW - Grazing exit KW - High entropy materials KW - XAS KW - Optimization PY - 2022 AN - OPUS4-56272 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -