A tape-driven liquid sample droplet delivery system for serial femtosecond crystallography is described.

The development of a new contrast software suite for small-angle neutron scattering (SANS) contrast variation (CV) experiments is reported. This new platform, integrated into the SASSIE-web framework, streamlines experiment planning, simulation and data analysis to improve the accessibility and efficiency of SANS CV studies for multi-component biological complexes.

For the first time quantum refinement has been performed with X-ray free-electron laser and microcrystal electron diffraction data for the dinuclear iron site in the R2a protein of ribonucleotide reductase. The method is shown to work well and can be used to determine the protonation state of the bridging solvent molecule and deduce photoreduction in two of the structures.

First-principles calculations on SiO2 and AlPO4 show that phase transitions reversing space-group chirality do not change the sign of optical rotation, clarifying the microscopic origin of this phenomenon.

This study introduces the novel Auto Diffraction Pipeline to generate large-scale synthetic 2D X-ray diffraction datasets from crystallographic information files. By training convolutional neural networks on these diverse datasets, the authors achieve rapid and automated classification across all seven crystal systems and 230 space groups.

The funding information for the article by Arakawa et al. [J. Appl. Cryst. (2025), 58, 886–896] is corrected.

We present results and practical considerations for the analysis of neutron spin echo data from vesicles with undulating membranes using a framework that was recently published [Granek et al. (2024). Eur. Phys. J. E 47, 12]. We show the importance of vesicle diffusion, size, lamellarity and osmotic pressure as well as the effects of membrane viscosity on the quantitative value for the bending rigidity.

The present study investigates the deformation behavior of high-strength steels and the associated evolution of material anisotropy. Particular focus is placed on the impact of crystallographic texture and intergranular strains on how residual stresses can be evaluated using X-ray diffraction and the associated assessment of weld seams in the automotive industry.

A reverse Monte Carlo/pair distribution function method was used to reconstruct the disordered 3D atomic structure of simulated AuPd nanoparticles at various stages of diffusional mixing.

A new carrier matrix for the high-viscosity injection of protein microcrystals during serial crystallography experiments is presented and characterized. Its suitability is validated by crystallographic data collection at the SACLA XFEL and further characterization at the ESRF synchrotron.

The effect of chromatic dispersion due to the difference between Si(111) double-crystal monochromator and sample Bragg angles in rocking curve imaging at a synchrotron has been evaluated. This previously unaccounted for mismatch leads to a change in the image size parallel to the scattering plane which must be considered for accurate determination of diffraction profiles, image resolution and lattice plane curvatures.

A new Python package, pygid, enables fast batch processing of X-ray scattering data, with a particular focus on grazing-incidence geometries.

A rapid scanning X-ray nanodiffraction method is demonstrated to efficiently assess local microstructural changes in polycrystalline micropillars during deformation, enabling real-time insights.

Six recurrent misconceptions in crystallography, some involving mineral and crystal optics, are analyzed and discussed. The explanation of these and similar misconceptions could serve as educational resources for teachers.

This study establishes a mathematical framework connecting symmetry operations with metrical restrictions through systematic analysis of symmetry operation representation matrices.

Anomalous diffraction analysis of hybrid perovskite thin films enables quantification of components in mixed compositions, as well as prospective investigation of superlattice ordering and spatial component distribution.

A simple modification to the bond valence site energy method is proposed to account for the asymmetrical coordination around post-transition metal cations in fluoride conductors due to the presence of electron lone pairs. A total of 136 structures from the Inorganic Crystal Structure Database are screened and several potential new conductors are suggested.

A full symmetry-mode decomposition analysis of PrNiO3 across its temperature-induced structural phase transitions allows identification of oxygen stretching and Jahn–Teller-like modes as the primary drivers of charge disproportionation at ∼130 K, concomitant with the metal–insulator transition. These distortions persist and evolve through the high-temperature orthorhombic to rhombohedral transition.

This article reports sub-Å structure determination of vacuum-sensitive organic samples in the solid state at room temperature by serial electron diffraction using formvar encapsulation for sample preservation.

A reconstruction procedure for patterns with incomplete information is reported. It is based on a modified Papoulis–Gerchberg algorithm. The modifications were introduced to guide the reconstruction procedure. The reconstruction algorithm could prove useful in specific experimental geometry setups.

We present a methodology based on wide-angle X-ray scattering for the quantitative assessment of interflake ordering in graphene oxide films, providing a structural parameter to characterize anisotropy in disordered 2D materials.

TransMagNet is a branch network model that predicts crystal systems and space groups directly from chemical compositions with high accuracy, providing a novel approach for materials design and discovery without relying on structural data.

This study shows that surface mechanical attrition treatment (SMAT) induces beneficial compressive residual stresses and subgrain refinement in atomic diffusion additive manufacturing (ADAM)-produced 17–4 PH stainless steel. Accurate residual stress evaluation critically depends on the appropriate selection of grain-interaction models, without which the performance predictions for additively manufactured components under high loading conditions may be compromised.

A split-crystal neutron interferometer allows longer arm separation and length. However, since the visibility of the interference is sensitive to seismic and acoustic noise, it is crucial to design and operate the interferometer acknowledging this problem. To aid in this process, we present a mathematical model that quantifies how time-dependent accelerations affect the phase and visibility of the interference fringes.

This study introduces Restrfcn, a transformer-based deep learning framework to accurately extract 3D nanofiber orientation parameters from complex wide-angle X-ray diffraction patterns, even with variable fiber sets. By optimizing the model via statistical hypothesis testing, the approach enables real-time analysis for high-throughput synchrotron experiments, advancing nanofiber composite characterization.