Combining Machine Learning With X-ray Absorption Spectroscopy For Rapid Material Characterization

LLNL scientists have developed a new approach that combines machine learning with X-ray absorption spectroscopy to rapidly predict the structure and chemical composition of heterogeneous materials. This approach offers new insights into the local atomic structure of these materials and represents a critical step in establishing an automated framework for rapid characterization.