X-ray and neutron scattering on disordered nanosize clusters: a case   study of lead-zirconate-titanate solid solutions
  Defects and defect models of solids are reviewed. A numerical method able to treat non-periodical solids possessing several simultaneous defect types is given for simulating scattering in nanosize clusters. The approach takes particle size, shape, and defects into account and isolates element specific signals. Examples illustrating how laboratory scale facilities can be used to extract crucial information about defects are given. As a case study a statistical approximation model for lead-zirconate-titanate (PZT) is introduced. PZT is a material possessing several defect types, including substitutional, displacement and surface defects. Spatial composition variation is taken into account by introducing a model in which the edge lengths of each cell depend on the distribution of Zr and Ti ions in the cluster. Spatially varying edge lengths and angles are referred to as microstrain. The Pb, Zr and Ti cation positions were adjusted by bond-valence sum (BVS) model to fullfil nominal valence requirement. The model is applied to compute the scattering from ellipsoid shaped PZT clusters and to simulate the structural changes as a function of average composition. Two-phase co-existence range, the so called morphotropic phase boundary (MPB) composition is given correctly. To make a comparison with commonly used x-ray and neutron diffraction data selected Bragg reflection intensities and line shapes were simulated. Examples of the effect of size and shape of the scattering clusters on diffraction patterns are given and the particle dimensions, computed through Scherrer equation, are compared with the exact cluster dimensions. Scattering from two types of 180 degree domains in spherical particles, one type assigned to Ti-rich PZT and the second to the MPB and Zr rich PZT, is computed. We show how the method can be used for modelling polarization reversal. 
Johannes Frantti and Yukari Fujioka
cond-mat.dis-nn cond-mat.mtrl-sci