Analyzing melts and fluids from ab initio molecular dynamics simulations with the UMD package

TL;DR

This paper introduces UMD, an open-source Python package for analyzing ab initio molecular dynamics simulations of fluids, enabling detailed structural, transport, and thermodynamic property calculations.

Contribution

The paper presents a new Python-based tool that simplifies analysis of simulation data, including chemical speciation, diffusion, and viscosity, specifically tailored for natural fluid systems.

Findings

Supports analysis of silicate and oxide melts, water, and supercritical fluids.

Provides a simplified UMD file format for storing simulation data.

Enables comprehensive property calculations from atomic trajectories.

Abstract

We develop a Python-based open-source package to analyze the results stemming from ab initio molecular-dynamics simulations of fluids. The package is best suited for applications on natural systems, like silicate and oxide melts, water-based fluids, various supercritical fluids. The package is a collection of Python scripts that include two major libraries dealing with file formats and with crystallography. All the scripts are run at the command line. We propose a simplified format to store the atomic trajectories and relevant thermodynamic information of the simulations, which is saved in UMD files, standing for Universal Molecular Dynamics. The UMD package allows the computation of a series of structural, transport and thermodynamic properties. Starting with the pair-distribution function it defines bond lengths, builds an interatomic connectivity matrix, and eventually determines the chemical speciation. Determining the lifetime of the chemical species allows running a full statistical analysis. Then dedicated scripts compute the mean-square displacements for the atoms as well as for the chemical species. The implemented self-correlation analysis of the atomic velocities yields the diffusion coefficients and the vibrational spectrum. The same analysis applied on the stresses yields the viscosity. The package is available via the GitHub website and via its own dedicated page of the ERC IMPACT project as open-access package.