Is the Local Ion Density Sufficient to Drive NaCl Nucleation from the Melt and Aqueous Solution?

TL;DR

This study uses advanced molecular dynamics simulations with deep learning to analyze NaCl nucleation, revealing local ion density's role and the importance of additional structural factors in the process.

Contribution

The paper introduces a novel deep learning-based reaction coordinate estimation method that improves nucleation sampling and analysis in both molten and aqueous NaCl environments.

Findings

Local ion density distinguishes solid and liquid states.

Fluctuations in ion density are necessary but not sufficient for nucleation.

Enthalpy and local structure are crucial near transition states.

Abstract

Even though nucleation is ubiquitous in different science and engineering problems, investigating nucleation is extremely difficult due to the complicated ranges of time and length scales involved. In this work, we simulate NaCl nucleation in both molten and aqueous environments using enhanced sampling all-atom molecular dynamics with deep learning-based estimation of reaction coordinates. By incorporating various structural order parameters and learning the reaction coordinate as a function thereof, we achieve significantly improved sampling relative to traditional ad hoc descriptions of what drives nucleation, particularly in the aqueous medium. Our results reveal a one-step nucleation mechanism in both environments, with reaction coordinate analysis highlighting the importance of local ion density in distinguishing solid and liquid states. However, while fluctuations in the local ion density are necessary to drive nucleation, they are not sufficient. Our analysis shows that near the transition states, descriptors such as enthalpy and local structure become crucial. Our protocol proposed here enables robust nucleation analysis and phase sampling, and could offer insights into nucleation mechanisms for generic small molecules in different environments.