Phys.org  July 16, 2024 Understanding and interpreting dynamics of functional materials in situ is a challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. Although X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. A team of engineers in the US (Argonne National Laboratory, University of Chicago) developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. They demonstrated how […]