Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations

TL;DR

This review discusses how molecular dynamics simulations have advanced understanding of crystal nucleation in liquids, highlighting current challenges and future directions for more accurate, realistic modeling of nucleation processes.

Contribution

It synthesizes recent simulation studies, critiques classical nucleation theory, and identifies key open questions and methodological improvements needed in the field.

Findings

Simulations have revealed diverse nucleation mechanisms.

Classical nucleation theory's applicability is often questioned.

Enhanced sampling methods are crucial for realistic system modeling.

Abstract

The nucleation of crystals in liquids is one of nature's most ubiquitous phenomena, playing an important role in areas such as climate change and the production of drugs. As the early stages of nucleation involve exceedingly small time and length scales, atomistic computer simulations can provide unique insight into the microscopic aspects of crystallization. In this review, we take stock of the numerous molecular dynamics simulations that in the last few decades have unraveled crucial aspects of crystal nucleation in liquids. We put into context the theoretical framework of classical nucleation theory and the state of the art computational methods, by reviewing simulations of e.g. ice nucleation or crystallization of molecules in solutions. We shall see that molecular dynamics simulations have provided key insight into diverse nucleation scenarios, ranging from colloidal particles to natural gas hydrates, and that in doing so the general applicability of classical nucleation theory has been repeatedly called into question. We have attempted to identify the most pressing open questions in the field. We believe that by improving (i.) existing interatomic potentials; and (ii.) currently available enhanced sampling methods, the community can move towards accurate investigations of realistic systems of practical interest, thus bringing simulations a step closer to experiments.