Joseph Pandur

Electronic and chemical phase identification in photoemission experiments using unsupervised machine learning

Vacuum ultraviolet photoemission spectroscopies are very information-rich experiments, but due to their surface sensitivity, data are often collected on an initially uncharacterized surface. Traditional raster-grid approaches for locating optimal measurement regions can be time-consuming. In this work, we introduce AAR...