The use of convolutional neural networks can revolutionize XRD analysis by significantly reducing processing times. Demonstration against synthetic and real mineral mixture data provide a first assessment of the accuracy of such methods.

A deep neural network approach to the identification and quantification of powder X-ray diffraction patterns was applied and proved successful for the quantitative description of complex mineralogical assemblages consisting of up to four minerals with different structures, including different space groups, for which data augmentation is not straightforward.

A Bayesian approach to formulation of a search–match strategy for powder phase identification is proposed. Even for a simple exponential model of prior probabilities the approach provides good agreement with known results for several testing examples.

Microinclusions in diamond reveal geochemical signatures from the Earth's deep mantle. A methodology is developed for non-destructive, high-throughput in situ characterization of mineral inclusions using synchrotron X-ray microtomography, radiography and diffraction at GSECARS, Sector 13 of the Advanced Photon Source.

The synthesis and structure refinement of a dense zeolite with a one-dimensional channel system is reported.

A U L_III-edge X-ray absorption spectroscopic investigation of U^VI interactions with minor cement minerals, ettringite and hydro­talcite, is reported. The study is supplemented by ²⁷Al magic angle scattering nuclear magnetic resonance spectroscopy, X-ray diffraction and geochemical modelling.

The impurity phase in high-purity CeB₆ is unequivocally identified by first determining its space group, using an iterative convergent-beam electron diffraction approach, and following this with an atomic structure confirmation by quantitative convergent-beam electron diffraction and high-angle annular dark-field scanning transmission electron microscopy.

PolyCleaver is an automated Python-based pipeline for modeling ionic mineral interfaces with polyatomic anions, providing new insights into potential catalytic properties and broadening the exploration of synthetic pathways in complex mineral systems.

Two recently developed three-dimensional electron diffraction methods have shown great potential for phase identification and structure determination of polycrystalline powder materials. Their combination with powder X-ray diffraction makes them powerful techniques for phase identification in multiphase samples and the determination of very complex structures from nano- and micron-sized crystals.

The XRD pattern of a deleterious phase in the photocatalyst based on Cd_1 − xZn_xS/Zn(OH)₂ contains two relatively intensive asymmetric peaks with d-spacings of 2.72 and 1.56 Å. To identify this phase, the XRD patterns were calculated for three models: sheet-like β-Zn(OH)₂, sheet-like hydrozincite, Zn₅(CO₃)₂(OH)₆, and turbostratic hydrozincite. Simulations revealed the formation of a nanocrystalline turbostratic hydrozincite-like phase.