Structure identification methods for atomistic simulations of crystalline materials

Physics – Condensed Matter – Materials Science

Scientific paper

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Scientific paper

We describe a new computational analysis technique to identify lattices and structural defects in large-scale atomistic computer simulations of crystalline materials. Our approach is based on a user-supplied catalog of template structures (motives). We use a graph-based pattern matching algorithm to find occurrences of periodic and non-periodic atomic arrangements in atomistic snapshots, and to generate a high-level description of a simulated microstructure. The method covers defects such as stacking faults, grain boundaries, crystal interfaces, point defects, and defect clusters in a wide range of crystal lattices. In contrast to existing methods, the proposed pattern matching algorithm is able to identify crystal structures with a polyatomic basis. Furthermore, we discuss how the local lattice orientation can be determined to measure crystal rotations, and how a defective crystal can be mapped to an ideal reference state. Finally, we derive a computational method for detecting and characterizing disclination defects in the analysis data.

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