Scalable machine learning framework for multiphase identification from powder X-ray diffraction
GALAXI decouples the identification task into independent one-versus-all binary classifiers that each specialize in recognizing a single phase, which remains robust to common experimental artifacts, including low impurity phase fractions, small crystallite size, peak shifts, sample displacement, and texture.