Enabling single-observation decomposition of multi-phase X-ray diffraction patterns via generative deep learning (opens in new tab)

Powder X-ray diffraction (PXRD) is a vital technique for the structural characterization of crystalline compounds. However, this analysis is challenged by practically encountered multi-phase systems, whose mixed PXRD patterns necessitate prior phase decomposition. Traditional approaches require multiple mixture samples or prior knowledge of the constituent phases, limiting their applicability in complex or high-throughput scenarios. Here we show that multi-phase PXRD patterns from a single ob...