darfix – data analysis for dark-field X-ray microscopy

Abstract

A Python package for the analysis of dark-field X-ray microscopy (DFXM) and rocking curve imaging (RCI) data is presented. DFXM is a non-destructive diffraction imaging technique that provides three-dimensional maps of lattice strain and orientation. The darfix package enables fast processing and visualization of these data, providing the user with the essential tools to extract information from the acquired images in a fast and intuitive manner. These data processing and visualization tools can be either imported as library components or accessed through a graphical user interface as an Orange add-on. In the latter case, the different analysis modules can be easily chained to define computational workflows. Operations on larger-than-memory image sets are supported through the implementation of online versions of the data processing algorithms, effectively trading performance for feasibility when the computing resources are limited. The software can automatically extract the relevant instrument angle settings from the input files' metadata. The currently available input file format is EDF and in future releases HDF5 will be incorporated.

Simulations of dislocation contrast in dark-field X-ray microscopy

“…The COM map has regularly been used to map domains, e.g. using the darfix data analysis software developed specifically for the handling of DFXM data at ESRF (Garriga Ferrer et al, 2023). We here propose that this procedure may also be relevant for identifying dislocations.…”

Heterogeneous Antiferroelectric Ordering in NaNbO3–SrSnO3 Ceramics Revealed by Direct Superstructure Imaging

“…The reconstructed maps of the ε ̅ 33 and FWHM (Full-Width at Half-Maximum relative to the positional variance of the superstructure Q-vector) were generated via the Gaussian moments approach using the Darfix library. 17 The main codes used herein are available at https://github.com/leosdo/ DFXM-superstructure. Further details on the sample preparation method and dielectric characterization for the ceramic pellets employed in this work are described in the literature.…”

“…The selected grains were then positioned such that their diffracted intensity was maximized, i.e ., at the thickest portion of the diffracting grain. The reconstructed maps of the ε̅ 33 and FWHM (Full-Width at Half-Maximum relative to the positional variance of the superstructure Q -vector) were generated via the Gaussian moments approach using the Darfix library . The main codes used herein are available at .…”