Identification of structure in condensed matter with the topological cluster classification

TL;DR

This paper introduces the topological cluster classification (TCC) algorithm, which identifies local structures in condensed matter by analyzing bond topologies, improving detection accuracy for simple liquids and crystalline phases.

Contribution

The paper presents a novel TCC algorithm with a modified Voronoi bond detection method for better identification of local structures in liquids and crystals.

Findings

Effective detection of local structures in Lennard-Jones liquids and crystals

Enhanced bond detection accuracy through modified Voronoi method

Applicable to monatomic and binary simple liquids with up to 13 particles

Abstract

We describe the topological cluster classification (TCC) algorithm. The TCC detects local structures with bond topologies similar to isolated clusters which minimise the potential energy for a number of monatomic and binary simple liquids with $m\leq13$ particles. We detail a modified Voronoi bond detection method that optimizes the cluster detection. The method to identify each cluster is outlined, and a test example of Lennard-Jones liquid and crystal phases is considered and critically examined.