Unsupervised Learning of Dislocation Motion
Rather than analyze diffraction data with a physics-based X-ray model to try to extract structural information chosen a priori, a team comprised of researchers from CHEXS, Cornell, and NIST used the unsupervised learning technique, locally linear embedding (LLE), to condense X-ray data down to critical microstructural (dislocation configuration) evolution information.