A study of stress, composition and grain interaction gradients in energy-dispersive X-ray stress analysis on materials with cubic symmetry

The influence of various combinations of residual stress, composition and grain interaction gradients in polycrystalline materials with cubic symmetry on X-ray stress analysis by energy-dispersive diffraction is discussed on the basis of simulations for ferritic and austenitic steel.

Accessing self-diffusion on nanosecond time and nanometre length scales with minute kinetic resolution

A new analysis framework to treat quasi-elastic neutron spectroscopy data recorded at discrete energy transfers has been developed. This new approach can be employed successfully for kinetic studies of diffusive dynamics.

Observation of quasi-Bragg scattering by Goebel mirrors

The first observation is reported of quasi-Bragg scattering from collimating Goebel mirrors in a real instrument.

TORO Indexer: a PyTorch-based indexing algorithm for kilohertz serial crystallography

Serial crystallography (SX) requires efficient processing of numerous diffraction patterns. TORO Indexer is a high-performance indexing solution that operates across various platforms such as GPUs, CPUs and TPUs, offering high processing speed without compromising indexing quality. Its design ensures easy integration into existing software, making it a useful tool for evolving SX techniques with ever-expanding data volumes.

Tracking copper nanofiller evolution in polysiloxane during processing into SiOC ceramic

The structural changes occurring during pyrolysis from pre-ceramic polymer to polymer-derived ceramic are traditionally challenging to characterize, and the inclusion of nanoparticle filler throughout the matrix complicates this further. In this work, the authors demonstrate the value of synchrotron X-ray scattering and pair distribution function analysis to track these structural changes with isolation of nanoparticle–matrix interactions at the local scale.

Qu­antitative selection of sample structures in small-angle scattering using Bayesian methods

A Bayesian method is proposed for quantitatively selecting a mathematical model of a sample for small-angle scattering. The performance of this method is evaluated through numerical experiments on artificial data for a sample containing a mixture of multiple spherical particles.

Patching-based deep-learning model for the inpainting of Bragg coherent diffraction patterns affected by detector gaps

Large pixel detectors exhibit gaps which affect data analysis because of missing data, e.g. for coherent diffraction imaging (CDI). A patching-based deep-learning algorithm is proposed, which allows the missing data to be estimated for arbitrary detector dimensions when applied to Bragg CDI, thus reducing the gap-induced artifacts in the reconstructions.

Accurate space-group prediction from composition

All available crystallographic information is used to train classification models for crystal systems, Bravais lattice, point groups and space groups. Reasonably accurate results can be achieved in space-group prediction if the classes used to train the models comprise more than 100 entries.

X-ray tensor tomography for small-grained polycrystals with strong texture

The article reports an investigation and comparison of different algorithms from small-angle X-ray scattering tensor tomography for reconstructing the anisotropic scattering density of samples with fast directional variation. The different methods are tested using wide-angle scattering data from an as-drawn steel wire.

Determination of α lamellae orientation in a β-Ti alloy using electron backscatter diffraction

A combination of electron backscatter diffraction and small-angle X-ray scattering analyses was employed to index all main axes and faces of an α lath not only in the cubic coordinate system of the parent β phase but also in the hexagonal system of the α phase.

Updating direct methods II. Reduction of the structural complexity when triplet invariants are estimated via the Patterson map

A recently published probabilistic theory estimates triplet invariants by using the Patterson peaks as prior information. This paper is the first experimental test: it is shown that the new estimates are so accurate that they may be applied to macromolecules. Structural complexity and atomic data resolution are no longer critical limits.

Approaches and challenges in whole-nanoparticle refinements from neutron total-scattering data

Data reduction and analysis approaches targeting whole-nanoparticle atomistic refinements from neutron total-scattering data are discussed. Refinements performed using the reverse Monte Carlo method are illustrated with the structural characterization of doped ceria nanoparticles.

Quality assessment of the wide-angle detection option planned at the high-intensity/extended Q-range SANS diffractometer KWS-2 combining experiments and McStas simulations

The performance of the wide-angle neutron scattering option on pinhole small-angle scattering instruments to measure data over a wide angular range with variable resolution can be assessed by comparison with the McStas simulation of ideal experimental conditions on the instrument.

Inferring effective electrostatic interaction of charge-stabilized colloids from scattering using deep learning

A deep learning approach has been developed for analyzing small-angle scattering data, effectively addressing the potential inversion problem in colloids. The method is validated using both simulation results and experimental spectra of charged silica suspensions and is shown to outperform existing approaches in accuracy and efficiency. This study highlights the potential of deep learning in soft-matter research.

A simple protocol for determining the zone axis direction from selected-area electron diffraction spot patterns of cubic materials

Reexamination of the well known R_n ratio method for indexing electron diffraction zone axis patterns of materials with cubic symmetry has revealed some unrecognized potential for zone axis direction analysis and, in some cases, unambiguous identification of the Bravais lattice. A protocol has been developed which allows the identification of experimental spot patterns for the 15 most common zone axis directions.