Eventi 2019

X-ray diffraction-X-ray fluorescence (XRD-XRF) data sets obtained from surface scans of synthetic samples have been analyzed using different data clustering algorithms, to propose a methodology for automatic crystallographic and chemical classification of surfaces.

Three data clustering strategies have been evaluated, namely hierarchical, k-means, and density-based clustering; all of them have been applied to the distance matrix calculated from the single XRD and XRF data sets as well as the combined distance matrix.