A powerful computational crystallography method to study ice polymorphism

TL;DR

This paper introduces a computational protocol using Molecular Dynamics simulations and clustering to analyze and identify various ice polymorphs, demonstrating its effectiveness in studying ice phase stability.

Contribution

The study presents a novel automated method combining MD simulations with clustering to identify and compare ice crystal phases based on a new interaction potential.

Findings

Successfully describes most ice structures in the phase diagram

Estimates relative stability of sixteen ice phases

Demonstrates automated crystal structure identification

Abstract

Classical Molecular Dynamics (MD) simulations are employed as a tool to investigate structural properties of ice crystals under several temperature and pressure conditions. All ice crystal phases are analyzed by means of a computational protocol based on a clustering approach following standard MD simulations. The MD simulations are performed by using a recently published classical interaction potential for oxygen and hydrogen in bulk water, derived from neutron scattering data, able to successfully describe complex phenomena such as proton hopping and bond formation/breaking. The present study demonstrates the ability of the interaction potential model to well describe most ice structures found in the phase diagram of water and to estimate the relative stability of sixteen known phases through a cluster analysis of simulated powder diagrams of polymorphs obtained from MD simulations. The proposed computational protocol is suited for automated crystal structure identification.