Machine Learning Boosts Search For New Materials

Scientists from the University of Rochester have developed deep learning models to better leverage the massive amounts of data produced by X-ray diffraction experiments. This project, funded by the US Department of Energy and the National Science Foundation, improves upon previous attempts to develop machine learning models for X-ray diffraction analysis by training and evaluating the models with synthetic data. The project holds particular promise for high-energy-density experiments, as it can help scientists discover ways to create new materials and learn about the formation of stars and planets.