Machine learning sifts through vast data from X-ray diffraction techniques to find new materials

Scientists from the University of Rochester say deep learning can supercharge a technique that is already the gold standard for characterizing new materials. In an npj Computational Materials paper, the interdisciplinary team describes models they developed to better leverage the massive amounts of data that X-ray diffraction experiments produce.