Experimental determination of a representative texture and insight into the range of significant neighboring grain interactions via orientation and misorientation statistics

The mechanical response of polycrystalline metallic materials is heavily influenced by the orientations of their grains. To predict polycrystalline behavior more accurately, crystal plasticity models account for grain orientations and also, sometimes, for interactions between neighboring grains. However, these models often lack sound experimental input or validation. Furthermore, experimental studies themselves rarely tackle simply the concept of representativity in terms of texture; neither do they try to analyze up to what range neighbor interactions appear to be significant. In this article, we address both aforementioned issues in a single and easily implementable framework by performing extensive statistical analyses of discrete raw orientation and misorientation data respectively, obtained by means of electron back-scattered diffraction on thousand-grain microstructures. First, we show that the analysis of orientation statistics helps determine whether an experimental dataset can be considered as a microstructurally representative volume element in terms of texture. Second, we explain how the statistical processing of misorientations can shed some light on the range of neighbors that have a significant weight in the misorientation distributions and possibly on the grain interactions.