Accelerating Material Characterization: Machine Learning Meets X-ray Absorption Spectroscopy

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 insights into the local atomic structure and can be used to establish an automated framework for characterizing complex materials.