# Reaction coordinates and rate constants for liquid droplet nucleation: quantifying the interplay between driving force and memory

## TL;DR

This study develops a reaction coordinate for liquid droplet nucleation that accounts for local density fluctuations and memory effects, improving rate constant calculations across different supersaturations.

## Contribution

The paper introduces a new reaction coordinate combining multiple order parameters, capturing non-Markovian effects at lower supersaturations, enhancing nucleation rate predictions.

## Key findings

- Reaction coordinate shifts from simple atom count to include density fluctuations at lower supersaturation.
- Density fluctuations exhibit long memory, affecting the Markovian assumption in nucleation modeling.
- Infrequent metadynamics with the new RC yields four orders of magnitude faster and more accurate nucleation rate estimates.

## Abstract

In this work we revisit the classic problem of homogeneous nucleation of a liquid droplet in a supersaturated vapor phase. We consider this at different extents of the driving force, which here is the extent of supersaturation, and calculate a reaction coordinate (RC) for nucleation as the driving force is varied. The RC is constructed as a linear combination of three order parameters, where one accounts for the number of liquid-like atoms, and the other two for local density fluctuations. The RC is calculated from all-atom biased and unbiased molecular dynamics (MD) simulations using the spectral gap optimization approach "SGOOP" [P. Tiwary and B. J. Berne, Proc. Natl. Acad. Sci. U. S. A. 113, 2839 (2016)]. Our key finding is that as the supersaturation decreases, the RC ceases to simply be the number of liquid-like atoms, and instead it becomes important to explicitly consider local density fluctuations that correlate with shape and density variations in the nucleus. All three order parameters are found to have similar barriers in their respective potentials of mean force, however, as the supersaturation decreases the density fluctuations decorrelate slower and thus carry longer memory. Thus at lower supersaturations density fluctuations are non-Markovian and can not be simply ignored from the RC by virtue of being noise. Finally, we use this optimized RC to calculate nucleation rates in the infrequent metadynamics framework, and show it leads to more accurate estimate of the nucleation rate with four orders of magnitude acceleration relative to unbiased MD.