A stereological method is described for estimating the distribution of grain-boundary types in polycrystalline materials on the basis of observations from a single planar section. The grain-boundary distribution is expressed in terms of five macroscopically observable parameters that include: three parameters that describe the lattice misorientation across the boundary and two parameters that describe the orientation of the grain-boundary plane normal. The grain-boundary distribution is derived from measurements of grain orientations and the orientations of the lines formed where grain boundaries intersect the plane of observation. Tests of the method on simulated observations illustrate that the distribution of boundaries in a material with cubic symmetry can be reliably determined with about 10º of resolution from the analysis of 5 ϫ 10 4 or more line segments. Furthermore, grain-boundary distributions directly observed from serial sections of a SrTiO 3 polycrystal are compared to those resulting from the stereological analysis of a single plane. The comparison shows that the stereological method provides a reasonable estimate of the measured distribution. The differences between the directly observed grain-boundary distribution and that derived from the stereological analysis are consistent with the results from the simulation.
Recent advances both in experimental instrumentation and computing power have made it possible to interrogate the distribution of internal interfaces in polycrystals and the three dimensional structure of the grain boundary network with an unprecedented level of detail. The purpose of this paper is to review techniques that can be used to study the mesoscopic crystallographic structure of grain boundary networks and to summarize current findings. Recent studies have shown that grain surfaces within dense polycrystals favor the same low energy planes that are found on equilibrium crystal shapes and growth forms of crystals in contact with another phase. In the materials for which comprehensive data exists, the distribution of grain boundaries is inversely correlated to the sum of the energies of the surfaces of the grains on either side of the boundary.
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