X-Ray Powder Diffraction in Materials Engineering: Industrial Applications, Multimodal Integration, and Data-Driven Methodologies

Abstract

X-ray powder diffraction (XRPD) occupies a central place in the structural characterization toolbox of materials engineering, providing phase identification, lattice-parameter determination, and microstructural information within a single analytical framework. Over the past two decades, modern position-sensitive and area detectors have substantially reduced acquisition times and enabled second- to minute-scale measurements in selected laboratory and synchrotron configurations. During the same period, Rietveld refinement software has become increasingly accessible for quantitative phase analysis of multiphase materials, while Machine-Learning methods have opened new possibilities for automated pattern classification, adaptive measurement, and high-throughput experimentation. This review provides a critical and integrative account of these developments through four interconnected themes: the quantitative capabilities and limitations of laboratory and synchrotron XRPD; industrial applications in cement, pharmaceuticals, energy storage, catalysis, and mining; multimodal characterization strategies combining XRPD with Raman spectroscopy, X-ray fluorescence, electron microscopy, and pair distribution function analysis; and in situ, operando, and data-driven methodologies. Particular attention is given to amorphous-phase quantification, peak overlap in complex systems, uncertainty assessment, and the generalization limitations of current Machine-Learning approaches. Emerging opportunities include laboratory total scattering, diffraction computed tomography, adaptive data acquisition, and the integration of XRPD into autonomous materials discovery workflows.