Full pattern analyses of small-angle X-ray and neutron scattering data with both discrete reflections and central diffuse scattering are presented. Data with both equatorial streaks and two- and four-point reflections can be fitted in elliptical coordinates with relatively few parameters.

The spatial correlation of vertically aligned Ni and CoNi alloy nanowires in an SrTiO₃ matrix has been analysed through the scattering around the Bragg reflections of the host matrix. The study demonstrates that off-Bragg scattering can be used in a selective and nondestructive way to study nano-objects inside a crystalline layer in nanocomposites and stacked nanostructures.

This work presents a novel method for the analysis of small-angle scattering data from a highly aligned domain structure based on a modification of the well known Porod law. The analysis approach allows the range of accessible length scales to be extended from 1 µm to up to 40 µm using a conventional small-angle neutron scattering setup.

This article describes the development of the scattering form factor for N aligned particles and N aligned particles inside a cylinder and its application to polyelectrolyte–surfactant complexes.

The statistics of continuous diffraction patterns are determined and used to improve analysis of the diffraction of imperfect crystals of photosystem II.

The use of multiple, oriented and singly referenced objects was evaluated as a means to overcome the low scattering cross section inherent in hard X-ray Fourier transform holography. It is shown that the image of each object can be restored as in the conventional single-object case.

Large and robust models of the most abundant space groups and symmetry elements are presented as an aid to visualization. In this way, space-group symmetry can be introduced to any audience in a readily understandable manner.

Two unsupervised machine learning approaches are presented to characterize structural variations in nanoparticle ensembles measured using X-ray single-particle imaging. The algorithms are applied to an experimental dataset where both discrete structural classes and continuous deformations caused by X-ray induced melting are classified.

In this study, we introduce TomoPyUI, a user-friendly interface for the TomoPy tomography data processing package, designed to streamline and enhance the management of synchrotron and neutron computed tomography data. TomoPyUI, operating within a Jupyter environment, incorporates GPU-accelerated algorithms and a structured data management system, significantly reducing computation times and improving workflow efficiency in the tomography processing pipeline.