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With the increased availability of high intensity time-of-flight neutron and synchrotron X-ray scattering sources that can access wide ranges of momentum transfer, the pair distribution function method has become a standard analysis technique for studying disorder of local coordination spheres and at intermediate atomic separations. In some cases, rational modeling of the total scattering data (Bragg and diffuse) becomes intractable with least-squares approaches and necessitates reverse Monte Carlo (RMC) simulations using large supercells. However, the extraction of meaningful information from the resulting atomistic ensembles is challenging, especially at intermediate length scales. We use representational analysis to describe displacements of atoms in RMC ensembles from an ideal crystallographic structure. Rewriting the displacements in terms of a local basis that is descriptive of the ideal crystallographic symmetry provides a robust approach to characterizing medium-range order (and disorder) and symmetry breaking in complex and disordered crystalline materials. This method enables the extraction of statistically relevant displacement modes (orientation, amplitude, and distribution) of the crystalline disorder and provides directly meaningful information in a symmetry-adapted basis set that is most descriptive of the crystal chemistry and physics.
Diffuse scattering is a rich source of information about disorder in crystalline materials, which can be modelled using atomistic techniques such as Monte Carlo and molecular dynamics simulations. Modern X-ray and neutron scattering instruments can r
We explore data reduction and correction steps and processed data reproducibility in the emerging single crystal total scattering based technique of three-dimensional differential atomic pair distribution function (3D-$Delta$PDF) analysis. All steps
Machine learning has emerged as a powerful tool for the analysis of mesoscopic and atomically resolved images and spectroscopy in electron and scanning probe microscopy, with the applications ranging from feature extraction to information compression
In this paper we investigated the most important family of proton conducting oxides, i.e. cerates, by means of pair distribution function analysis (PDF) obtained from total neutron scattering data. The results clearly demonstrates that the local stru
X-ray and neutron powder diffraction data as a function of temperature are analyzed for the colossal dielectric constant material CaCu3Ti4O12. The local structure is studied using atomic pair distribution function analysis. No evidence is found for e