A Variational Approach to Assess Reaction Coordinates for Two-Step Crystallisation

TL;DR

This paper applies a variational approach to Markov processes to evaluate reaction coordinates in crystallisation, identifying key collective variables and revealing a two-step nucleation mechanism through Markov State Models.

Contribution

It introduces a variational framework using VAMP and MSMs to assess and optimize reaction coordinates for crystallisation simulations, highlighting the importance of specific collective variables.

Findings

Collective variables correlated with condensed phase particles, energy, and entropy are effective order parameters.

Two barriers separate the fluid phase from crystals, as shown by MSMs.

The two-step nucleation mechanism is confirmed in higher-dimensional analyses.

Abstract

Molecule- and particle-based simulations provide the tools to test, in microscopic detail, the validity of classical nucleation theory. In this endeavour, determining nucleation mechanisms and rates for phase separation requires an appropriately defined reaction coordinate to describe the transformation of an out-of-equilibrium parent phase, for which myriad options are available to the simulator. In this article, we describe the application of the variational approach to Markov processes (VAMP) to quantify the suitability of reaction coordinates to study crystallisation from supersaturated colloid suspensions. Our analysis indicates that collective variables (CVs) that correlate with the number of particles in the condensed phase, the system potential energy and approximate configurational entropy often feature as the most appropriate order parameters to quantitatively describe the crystallisation process. We apply time-lagged independent component analysis to reduce high-dimensional reaction coordinates constructed from these CVs to build Markov State Models (MSMs), which indicate that two barriers separate a supersaturated fluid phase from crystals in the simulated environment. The MSMs provide consistent estimates for crystal nucleation rates, regardless of the dimensionality of the order parameter space adopted; however, the two-step mechanism is only consistently evident from spectral clustering of the MSMs in higher dimensions. As the method is general and easily transferable, the variational approach we adopt could provide a useful framework to study controls for crystal nucleation.