Point-Pattern Matching Technique for Local Structural Analysis in Condensed Matter

Abstract

The local arrangement of atoms is one of the most important predictors of mechanical and functional properties of materials. However, algorithms for identifying the geometrical arrangements of atoms in complex materials systems are lacking. To address this challenge, we present a point-pattern matching algorithm that can detect instances of a `template' structure in a given set of atom coordinates. To our knowledge this is the first geometrical comparison technique for atomistic configurations with very different number of atoms, and when the optimal rotations and translations required to align the configurations are unknown. The pattern matching algorithm can be combined with an appropriate set of metrics to quantify the similarity or dissimilarity between configurations of atoms. We demonstrate the unique capabilities of the point-pattern matching algorithm using two examples where the automated analysis of local atomistic structure can help advance the understanding of structure-property relationships in material science: (a) identifying local three-dimensional polyhedral units along interfacial defects, and (b) the analysis of quasi-icosahedral topologies in the atomistic structure of metallic glasses. We anticipate that the pattern matching algorithm will be applicable in the analysis of atomistic structures in broad areas of condensed matter systems, including biological molecules, polymers and disordered metallic systems. An online implementation of the algorithm is provided via the open source code hosted on GitHub (https://github.com/spatala/ppm3d).

References in corpus (8)

• Gaussian Approximation Potentials: the accuracy of quantum mechanics, without the electrons
• Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration
• Comparing molecules and solids across structural and alchemical space
• Grain-Boundary Kinetics: A Unified Approach
• A Topological Framework for Local Structure Analysis in Condensed Matter
• Protein-protein docking by generalized Fourier transforms on 5D rotational manifolds
• Complete topology of cells, grains, and bubbles in three-dimensional microstructures
• Short-Range Order Structure Motifs Learned from an Atomistic Model of a Zr${}_{50}$Cu${}_{45}$Al${}_5$ Metallic Glass

Cited by in corpus (1)

• Short-Range Order Structure Motifs Learned from an Atomistic Model of a Zr${}_{50}$Cu${}_{45}$Al${}_5$ Metallic Glass