Cluster Analysis in Liquids: A Novel Tool in TRAVIS.

Abstract

We present a novel cluster analysis implemented in our open-source software TRAVIS and its application to realistic and complex chemical systems. The underlying algorithm is exclusively based on atom distances. Using a two-dimensional model system, we first introduce different cluster analysis functions and their application to single snapshots and trajectories including periodicity and temporal propagation. Using molecular dynamics simulations of pure water with varying system size, we show that our cluster analysis is size-independent. Furthermore, we observe a similar clustering behavior of pure water in classical and ab initio molecular dynamics simulations, showing that our cluster analysis is universal. In order to emphasize the application to more complex systems and mixtures, we additionally apply the cluster analysis to ab initio molecular dynamics simulations of the [C2C1Im][OAc] ionic liquid and its mixture with water. Using that, we show that our cluster analysis is able to analyze the clustering of the individual components in a mixture as well as the clustering of the ionic liquid with water.