Connection between water's dynamical and structural properties: Insights from ab initio simulations.

SignificanceFirst-principles calculations, which explicitly account for the electronic structure of matter, can shed light on the molecular structure and dynamics of water in its supercooled state. In this work, we use density functional theory, which relies on a functional to describe electronic exchange and correlations, to evaluate which functional best describes the temperature evolution of bulk water transport coefficients. We also assess the validity of the Stokes-Einstein relation for all the functionals in the temperature range studied, and explore the link between structure and dynamics. Based on these results, we show how transport coefficients can be computed from structural descriptors, which require shorter simulation times to converge, and we point toward strategies to develop better functionals.

Surface tension of liquids and binary mixtures from molecular dynamics simulations.

In this work we assess and extend strategies for calculating surface tension of complex liquids from molecular dynamics simulations: the mechanical route and the instantaneous liquid interface (ILI) approach. The former employs the connection between stress tensor and surface tension, whereas the latter involves computation of instantaneous density field. Whereas the mechanical route is general, the ILI method involves system-dependent parameters restricting its original application to liquid water only. Here we generalize the approach to complex molecular liquids using atomic van der Waals radii. The performance of the approaches is evaluated on two liquid systems: acetonitrile and water-methanol mixture. In addition, we compare the effect of the computational models for interaction potentials based on semi-empirical electronic structure theory and classical force fields on the estimate of the surface tension within both stress tensor and ILI approaches.

Subsystem Density Functional Theory Augmented by a Delta Learning Approach to Achieve Kohn-Sham Accuracy.

Simulations based on electronic structure theory naturally include polarization and have no transferability problems. In particular, Kohn-Sham density functional theory (KS-DFT) has become the method of reference for ab initio molecular dynamics simulations of condensed matter systems. However, the high computational cost often poses strict limits on the affordable system size as well as on the extension of sampling (number of configurations). In this work, we propose an improvement to the subsystem density functional theory approach, known as the Kim-Gordon (KG) scheme, thus enabling the sampling of configurations for condensed molecular systems keeping the KS-DFT level accuracy at a fraction of computer time. Our scheme compensates the known KG shortcomings of the electronic kinetic energy term by adding a simple correction and can match KS-DFT accuracy in energies and forces. The computationally cheap correction is determined by means of a machine learning procedure. The proposed KG scheme is applied within a linear scaling self-consistent field formalism and is assessed by a series of molecular dynamics simulations of liquid water under different conditions. Although system-dependent, the correction is transferable between system sizes and temperatures.