This presentation focuses on the application of machine learning techniques, specifically deep reinforcement learning, to improve the process of X-ray reflectivity (XRR) measurements. Our study demonstrates how machine learning can be utilized to dynamically adjust measurement angles and integration times, adapting these parameters after acquisition of each new datapoint to optimize the...
Grazing-incidence Wide Angle X-ray scattering (GIWAXS) is a key technique for characterizing surface structures of thin films. The method can be used for in-situ experiments monitoring growth and crystallization effects in real-time, but it produces large amounts of data, frequently exceeding the capabilities of traditional data processing methods.
Feature detection in multidimensional X-ray...
Solving inverse problems is the basis of the analysis of scattering experiments. The difficulty stems from the fact that the real-space structure has to be retrieved from reciprocal space information. With respect to thin films and interfaces, grazing incidence small- angle X-ray scattering (GISAXS) is a powerful tool for accessing their nanoscale structure formation. GISAXS allows for...
