Convolutional neural networks are useful for classifying grazing-incidence small-angle X-ray scattering patterns. They are also useful for classifying real experimental data.

This paper presents an accurate numerical algorithm for simulating grazing-incidence small-angle X-ray scattering patterns of nanostructures using the multi-slice distorted-wave Born approximation. The method overcomes the typical challenge of requiring the users to manually specify a way to approximate their samples by utilizing properties of Fourier transforms to automate the computation.

Grazing-incidence small-angle X-ray scattering (GISAXS) has been used to structurally characterize model hard and soft gratings of nanotechnological interest. The different gratings exhibit GISAXS patterns with characteristic features that can be associated with their level of order along the direction of periodicity and the length of the lines.

BornAgain is a free and open-source multi-platform software framework for simulating and fitting X-ray and neutron reflectometry, off-specular scattering, and grazing-incidence small-angle scattering (GISAS). This paper concentrates on GISAS.

The multiple scattering effects present in grazing-incidence small-angle X-ray scattering (GISAXS) data and interference between them are addressed theoretically as well as experimentally with measurement of a series of patterns at different incident angles, referred to as `incident-angle-resolved GISAXS' (IAR-GISAXS). X-ray reflectivity, GISAXS and IAR-GISAXS of virus particles on Si-substrate supported-polystyrene films have been measured and all the data have been analyzed with appropriate formalisms.

The shallow incidence angles used in GISAXS lead to a very large footprint of the X-ray beam on the sample. Here it is shown that, despite these large footprints, GISAXS measurements of targets with sizes down to 4 µm × 4 µm are possible.

The electron density map of a block copolymer thin film having the hexagonally perforated layer (HPL) structure was directly obtained from the measured grazing-incidence small-angle X-ray scattering (GISAXS) pattern. In addition, X-ray reflectivity analysis has been performed, which when combined with the GISAXS results, provides full details of the HPL structure.

Calculations of intensity in grazing-incidence small-angle neutron scattering are made for colloidal structures near a solid/liquid interface.

A strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of supported, nanostructured soft-matter thin films using the distorted-wave Born approximation is introduced. The different scattering contributions of the nanostructure, surface roughness and background scattering are treated separately and are adjusted step by step. To minimize calculation efforts, 1D line cuts are chosen, in which the scattering is predominantly attributed to one of the contributions, and the parameters found are used in the subsequent steps. Hence, separate measurements of the bare substrate are beneficial.

The reconstruction of two-dimensional images of patterned thin films by using grazing-incidence small-angle scattering coupled with computed tomography measurements has been investigated.