Abstract

Simulations of crystal deformation and structural transformation may generate complex datasets involving networks with million to billion chemical bonds which makes local structure analysis a challenge. An ideal analysis method must recognize perfect crystal structures, such as face-centered cubic, body-centered cubic and hexagonal close packed, and differentiate structural defects such as dislocations, stacking faults, grain boundaries, cracks and surfaces. Currently a few methods are used for this purpose, e.g., the Common Neighbor Analysis (CNA) and the Centrosymmetry Parameter (CSP). This paper proposes an alternative method based on the calculation of a single parameter that depends on the common atomic neighborhood. We validate the method characterizing local structures in complex molecular-dynamics datasets, clarifying its advantages over the CNA and the CSP methods.

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