Translational and Rotational Diffusion in Liquid Water at Very High Pressure: A Simulation Study

Relationships between Molecular Structural Order Parameters and Equilibrium Water Dynamics in Aqueous Mixtures

Water's unique thermophysical properties and how it mediates aqueous interactions between solutes have long been interpreted in terms of its collective molecular structure. The seminal work of Errington and Debenedetti [Nature 2001, 409, 318-321] revealed a striking hierarchy of relationships among the thermodynamic, dynamic, and structural properties of water, motivating many efforts to understand (1) what measures of water structure are connected to different experimentally accessible macroscopic responses and (2) how many such structural metrics are adequate to describe the collective structural behavior of water. Diffusivity constitutes a particularly interesting experimentally accessible equilibrium property to investigate such relationships because advanced NMR techniques allow the measurement of bulk and local water dynamics in nanometer proximity to molecules and interfaces, suggesting the enticing possibility of measuring local diffusivities that report on water structure. Here, we apply statistical learning methods to discover persistent structure-dynamic correlations across a variety of simulated aqueous mixtures, from alcohol-water to polypeptoid-water systems. We investigate a variety of molecular water structure metrics and find that an unsupervised statistical learning algorithm (namely, sequential feature selection) identifies only two or three independent structural metrics that are sufficient to predict water self-diffusivity accurately. Surprisingly, the translational diffusivity of water across all mixed systems studied here is strongly correlated with a measure of tetrahedral order given by water's triplet angle distribution. We also identify a separate small number of structural metrics that well predict an important thermodynamic property, the excess chemical potential of an idealized methane-sized hydrophobe in water. Ultimately, we offer a Bayesian method of inferring water structure by using only structure-dynamics linear regression models with experimental Overhauser dynamic nuclear polarization (ODNP) measurements of water self-diffusivity. This study thus quantifies the relationships among several distinct structural order parameters in water and, through statistical learning, reveals the potential to leverage molecular structure to predict fundamental thermophysical properties. In turn, these findings suggest a framework for solving the inverse problem of inferring water's molecular structure using experimental measurements such as ODNP studies that probe local water properties.

Structure and dynamics of water plastic crystals from computer simulations

Water has a rich phase diagram with several crystals, as confirmed by experiments. High-pressure and high-temperature water is of interest for Earth's mantle and exoplanetary investigations. It is in this region of the phase diagram of water that new plastic crystal phases of water have been revealed via computer simulations by both classical forcefields and ab initio calculations. However, these plastic phases still remain elusive in experiments. Here, we present a complete characterization of the structure, dynamics, and thermodynamics of the computational plastic crystal phases of water using molecular dynamics and the two-phase thermodynamic method and uncover the interplay between them. The relaxation times of different reorientational correlation functions are obtained for the hypothetical body-centered-cubic and face-centered-cubic plastic crystal phases of water at T = 440 K and P = 8 GPa. Results are compared to a high pressure liquid and ice VII phases to improve the understanding of the plastic crystal phases. Entropy results indicate that the fcc crystal is more stable compared to the bcc structure under the studied conditions.

Effects of Hydrogen Bonding on the Rotational Dynamics of Water-Like Molecules in Liquids: Insights from Molecular Dynamics Simulations

Rotational motion of molecules plays an important role in determining NMR spin relaxation properties of liquids. The textbook theory of NMR spin relaxation predominantly uses the assumption that the reorientational dynamics of molecules is described by a continuous time rotational diffusion random walk with a single rotational diffusion coefficient. Previously we and others have shown that reorientation of water molecules on the timescales of picoseconds is not consistent with the Debye rotational-diffusion model. In particular, multiple timescales of molecular reorientation were observed in liquid water. This was attributed to the hydrogen bonding network in water and the consequent presence of collective rearrangements of the molecular network. In order to better understand the origins of the complex reorientational behaviour of water molecules, we carried out molecular dynamics (MD) simulations of a liquid that has a similar molecular geometry to water but does not form hydrogen bonds: hydrogen sulfide. These simulations were carried out at T=208K and p=1 atm (~5K below the boiling point). Ensemble-averaged Legendre polynomial functions of hydrogen sulfide exhibited a Gaussian decay on the sub-picosecond timescale but, unlike water, did not exhibit oscillatory behaviour. We attribute these differences to hydrogen sulfide’s absence of hydrogen bonding.