2, Capilano University, North Vancouver, British Columbia, Canada
The structural description of even the most basic amorphous materials are under considerable debate. In this work, an intuitive computational technique has been developed to construct 3D statistical density maps to directly visualize and identify local atomic structures from simple monatomic amorphous germanium (a-Ge) to complex multi-atom systems such as copper zirconium metallic glass. This approach clearly reveals structural differences between molecular dynamics and reverse monte carlo models of a-Ge as well as changes due to annealing. We show motifs in copper zirconium that are unresolvable through traditional tools such as Voronoi indexing. This self-sorted local atomic motif (SLAM) method builds upon the Kabsch algorithm incorporating techniques in computer vision to produce least-squares optimized 3D density maps. Simultaneously, the SLAM method incorporates self-contained categorization to define local motifs based upon atomic structures physically present in a model rather than imposing biased criterion inherent in Voronoi indexing methods.
We present the methodology of the SLAM method and also present resulting motifs through stereographic projections. Subtle distortions of the tetrahedral structure of a-Ge is shown to change upon annealing and comparisons to continuous random network models show different dihedral disorder with respect to reverse monte carlo models. A first examination of structures in metallic glass is shown and a discussion of its potential application to shear-band structure and composition.