Structure identification methods for atomistic simulations of crystalline materials

TL;DR

This paper reviews and compares various computational methods for classifying local atomic structures in crystalline materials, introduces an extension for multi-phase systems, and proposes a new algorithm for grain boundary analysis.

Contribution

It provides a performance comparison of existing algorithms, extends Common Neighbor Analysis for multi-phase systems, and introduces the Neighbor Distance Analysis method.

Findings

Performance comparison of analysis algorithms

Extension of CNA for multi-phase systems

Introduction of Neighbor Distance Analysis for grain boundaries

Abstract

We discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as Common Neighbor Analysis, Centrosymmetry Analysis, Bond Angle Analysis, Bond Order Analysis, and Voronoi Analysis. In addition we propose a simple extension to the Common Neighbor Analysis method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the Neighbor Distance Analysis, that is designed to identify atomic structure units in grain boundaries.