Correlation: An Analyzing Tool for Liquids and for Amorphous Solids

TL;DR

Correlation is an open-source, user-friendly software tool designed for analyzing liquids and amorphous solids by calculating various correlation functions, supporting large structures and multiple file formats for comprehensive structural analysis.

Contribution

The paper introduces Correlation, a modular, cross-platform software that facilitates large-scale analysis of disordered materials using correlation functions, with easy integration into high-throughput workflows.

Findings

Supports up to 25,000 atoms in structure analysis

Compatible with multiple first-principles and classical simulation files

Exports results in CSV format for further analysis

Abstract

For almost a century, since Bernal\'s attempts at a molecular theory of liquid structure(Bernal [1]), correlation functions have been the bridge to compare theoretical calculations with experimental measurements in the study of disordered materials. Pair Distribution Functions (g(r)), Radial Distribution Functions (J(r)), Plane Angle Distributions (g({\theta})) and Coordination Numbers (nc) have been widely used to characterize amorphous and liquid materials (Waseda [2]; Elliott [3]; Valladares et al. [4]) and, in particular Bulk Metallic Glasses (Miller and Liaw [5]; Galv\'an-Col\'in et al. [6]). Correlation is an Open-Source software designed to analyze liquid structures and amorphous solids; the software is user-friendly, the modular design makes it easy to integrate in High-Throughput Computing (HTC) to process structures with a large number of constituents in a standardized fashion. Correlation is ready to be used in Windows,Linux and Mac. Currently, we support DMol3 (CAR), CASTEP (CELL), ONETEP (DAT)and VASP (POSCAR) structure files. The code can handle up to 25,000 atoms, so it can be used to analyze both classical and first-principles simulations. At the end, the output of every single correlation function is exported to the corresponding comma-separated value file (CSV), to further analyze the results.