Homogeneous SPC/E water nucleation in large molecular dynamics simulations (1507.07335v1)

Abstract: We perform direct large molecular dynamics simulations of homogeneous SPC/E water nucleation, using up to $\sim 4\cdot 10^6$ molecules. Our large system sizes allow us to measure extremely low and accurate nucleation rates, down to $\sim 10^{19}\,\textrm{cm}^{-3}\textrm{s}^{-1}$, helping close the gap between experimentally measured rates $\sim 10^{17}\,\textrm{cm}^{-3}\textrm{s}^{-1}$. We are also able to precisely measure size distributions, sticking efficiencies, cluster temperatures, and cluster internal densities. We introduce a new functional form to implement the Yasuoka-Matsumoto nucleation rate measurement technique (threshold method). Comparison to nucleation models shows that classical nucleation theory over-estimates nucleation rates by a few orders of magnitude. The semi-phenomenological nucleation model does better, under-predicting rates by at worst, a factor of 24. Unlike what has been observed in Lennard-Jones simulations, post-critical clusters have temperatures consistent with the run average temperature. Also, we observe that post-critical clusters have densities very slightly higher, $\sim 5\%$, than bulk liquid. We re-calibrate a Hale-type $J$ vs. $S$ scaling relation using both experimental and simulation data, finding remarkable consistency in over $30$ orders of magnitude in the nucleation rate range, and $180\,$K in the temperature range.

• The paper employs extensive MD simulations with up to 4 million molecules to measure nucleation rates as low as 10^19 cm⁻³ s⁻¹.
• The paper shows that classical nucleation theory overestimates rates by 10- to 1000-fold compared to a semi-phenomenological model that better approximates observed behaviors.
• The paper finds that SPC/E water clusters maintain ambient simulation temperatures and display slight over-density, offering new insights into thermal and structural cluster properties.

Homogeneous SPC/E Water Nucleation in Large Molecular Dynamics Simulations

The research by Ang et al. explores the nucleation process of SPC/E water using extensive molecular dynamics (MD) simulations. This paper addresses the significant gap between experimental and simulated nucleation rates by employing large system sizes, containing up to approximately 4 million molecules, which facilitate the measurement of very low nucleation rates, down to about $10^{19}\,\textrm{cm}^{-3}\textrm{s}^{-1}$. This achievement significantly reduces the discrepancy with experimental results that typically report nucleation rates around $10^{17}\,\textrm{cm}^{-3}\textrm{s}^{-1}$.

The authors utilize a modified Yasuoka-Matsumoto technique to assess nucleation rates, thereby overcoming limitations associated with reaching steady-state nucleation regimes. Notably, the simulations reveal that classical nucleation theory (CNT) overestimates these rates by factors ranging from ten to one thousand, whereas the semi-phenomenological (SP) model, though underpredicting, offers a closer approximation of the observed nucleation behaviors.

One critical finding of the paper is that SPC/E water post-critical cluster temperatures reflect the ambient simulation conditions, indicating effective thermal exchange between clusters and their surroundings. This contrasts with Lennard-Jones nucleation scenarios, where post-critical clusters generally retain latent heat, resulting in elevated internal temperatures. Such disparities are likely attributable to the long-range Coulombic interactions present in the SPC/E model, which facilitate heat dissipation.

Moreover, the density profiles of clusters demonstrate a slight over-density compared to bulk liquid, contrary to the lower densities observed in Lennard-Jones fluids. This minor over-density implies potentially reduced surface areas, affecting nucleation rate predictions by lowering the Gibbs free energy associated with cluster formation.

The paper further validates a scaling law that integrates nucleation rates from both MD simulations and experimental data across an immense magnitude range and temperature span, unifying these into a coherent framework. This highlights the robustness of the proposed scaling approach, underscoring its utility in broadening the applicability of MD simulation data to real-world scenarios.

In summary, this research not only bridges the gap between laboratory experiments and MD simulations for homogeneous water nucleation but also challenges existing theoretical models. The detailed examination of cluster properties, such as temperatures and densities, alongside improved methodological approaches, pushes the boundaries of our understanding of nucleation thermodynamics. This work lays the groundwork for future studies that could refine nucleation models by incorporating findings on cluster dynamics and interaction processes, ultimately enhancing predictive capabilities in the context of atmospheric science and materials engineering.