Adam Herron, Jared Thomas, Shawn Coleman, Douglas Spearot, and Eric Homer, Brigham Young University
Engineering
For many years, x-ray diffraction and electron diffraction have served as effective means to understand and classify the molecular structure of many materials. Diffraction, as a physical phenomenon, is well known and theoretical diffraction simulation is relatively simple for perfect crystalline structures of known orientation. Prior methods of diffraction simulation, however, are insufficient to predict experimental diffraction patterns of unknown crystal structures or of crystal structures with high defect density. Recent advancements in computing capability and development of atomistic simulation software have greatly enhanced our ability to predict material properties and behaviors under various conditions. Atomistic simulation has become an extremely useful tool in the analysis of dynamic chemical and mechanical systems. It can only be truly effective, however, when it models a real-world application, can be interpreted coherently, and can accurately predict future conditions. Thus, we are developing new tools that bridge the gap between electron diffraction through real materials and simulated diffraction through atomistic simulations. We present a method of generating Kikuchi Diffraction Patterns from atomistic simulation data with no a priori knowledge of the crystal structure or crystallographic orientation. Our research was inspired by the recent work of Coleman et. al. 2013 and builds on their methods of calculating diffraction intensity at discrete locations in the reciprocal domain. We improve on their method by introducing an integration of the structure factor to ensure complete capture of diffraction intensity peaks while maintaining a relatively low density of sample points. This allows us to significantly reduce the required computation time on the analysis of atomistic simulation data. We use this diffraction data to generate simulated Kikuchi Diffraction Patterns.