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

Area of Science:

• Physical Chemistry
• Computational Chemistry
• Statistical Mechanics

Background:

• Water's thermophysical properties are linked to its molecular structure and interactions.
• Understanding structure-property relationships is crucial for aqueous systems.
• Advanced NMR techniques offer insights into water dynamics and local structure.

Purpose of the Study:

• To identify key water structure metrics correlated with macroscopic properties.
• To develop methods for predicting water's thermophysical properties from its structure.
• To establish a framework for inferring water structure using experimental dynamics measurements.

Main Methods:

• Application of statistical learning (sequential feature selection) to simulated aqueous mixtures.
• Analysis of various molecular water structure metrics.
• Development of a Bayesian method using structure-dynamics linear regression and ODNP data.

Main Results:

• Two to three independent structural metrics accurately predict water self-diffusivity.
• Translational diffusivity strongly correlates with tetrahedral order (triplet angle distribution).
• A small set of metrics predicts the excess chemical potential of hydrophobes.

Conclusions:

• Molecular water structure can be leveraged to predict fundamental thermophysical properties.
• Experimental measurements of water self-diffusivity (e.g., ODNP) can be used to infer local water structure.
• This work provides a framework for solving the inverse problem of water structure determination.