The collective burst mechanism of angular jumps in liquid water

Evidence of ferroelectric features in low-density supercooled water from ab initio deep neural-network simulations

Over the last decade, an increasing body of evidence has emerged, supporting the existence of a metastable liquid-liquid critical point in supercooled water whereby two distinct liquid phases of different densities coexist. Analyzing long molecular dynamics simulations performed using deep neural-network force fields trained to accurate quantum mechanical data, we demonstrate that the low-density liquid phase displays a strong propensity toward spontaneous polarization, as witnessed by large and long-lived collective dipole fluctuations. Our findings suggest that the dynamical stability of the low-density phase, and hence the transition from high-density to low-density liquid, is triggered by a collective process involving an accumulation of rotational angular jumps, which could ignite large dipole fluctuations. This dynamical transition involves subtle changes in the electronic polarizability of water molecules which affects their rotational mobility within the two phases. These findings hold the potential for catalyzing activity in the search for dielectric-based probes of the putative second critical point.

Networks of Hydrogen Bond Networks in Water Clusters

Water clusters play a prominent role in atmospheric and solution chemistry. Numerous arrangements of protons, H-bond configurations or networks, shape the cluster properties. Studies of small water clusters by cryogenic scanning tunneling microscopy and high-resolution rovibrational spectroscopy have established proton rearrangement mechanisms forming pathways between H-bond networks. The mechanisms, concerted tunneling in particular, describe the local processes connecting pairs of configurations. Here, proton rearrangement networks mapping these transformations are defined and explored to provide a global view of the H-bond configurations in clusters. The networks are constructed for clusters of different sizes and structures. Their analysis reveals an odd-even effect with respect to the number of water molecules, exponential growth of the small-world character, bimodality of the degree distributions, and gapped assortativity of the networks. The last two properties signify the unexpected division of H-bond configurations into two classes according to their network connectivity. The results demonstrate qualitative differences between proton rearrangement mechanisms, suggest a strong influence of the cluster structure. The generated networks are of interest as real-world models for network rewiring; they establish an alternative platform for studies of proton rearrangements in H-bonded systems.

Spontaneous Dipole Reorientation in Confined Water and Its Effect on Wetting/Dewetting of Hydrophobic Nanopores

The properties of nanoconfined fluids are important for a broad range of natural and engineering systems. In particular, wetting/dewetting of hydrophobic nanoporous materials is crucial due to their broad applicability for molecular separation and liquid purification; energy storage, conversion, recuperation, and dissipation; for catalysis, chromatography, and so on. In this work, a rapid, orchestrated, and spontaneous dipole reorientation was observed in hydrophobic nanotubes of various pore sizes d (7.9-16.5 Å) via simulations. This phenomenon leads to the fragmentation of water clusters in the narrow nanopores (d = 7.9, 10 Å) and strongly affects dewetting through cluster repulsion. The cavitation in these pores has an electrostatic origin. The dependence of hydrogen-bonded network properties on the tube aperture is obtained and is used to explain wetting (intrusion)-dewetting (extrusion) hysteresis. Computer simulations and experimental data demonstrate that d equals ca. 12.5 Å is a threshold between a nonhysteretic (spring) behavior, where intrusion-extrusion is reversible, and a hysteretic one (shock absorber), where hysteresis is prominent. This work suggests that water clustering and the electrostatic nature of cavitation are important factors that can be effectively exploited for controlling the wetting/dewetting of nanoporous materials.

Lessons Learned from Multiobjective Automatic Optimizations of Classical Three-Site Rigid Water Models Using Microscopic and Macroscopic Target Experimental Observables

The development of accurate water models is of primary importance for molecular simulations. Despite their intrinsic approximations, three-site rigid water models are still ubiquitously used to simulate a variety of molecular systems. Automatic optimization approaches have been recently used to iteratively refine three-site water models to fit macroscopic (average) thermodynamic properties, providing state-of-the-art three-site models that still present some deviations from the liquid water properties. Here, we show the results obtained by automatically optimizing three-site rigid water models to fit a combination of microscopic and macroscopic experimental observables. We use Swarm-CG, a multiobjective particle-swarm-optimization algorithm, for training the models to reproduce the experimental radial distribution functions of liquid water at various temperatures (rich in microscopic-level information on, e.g., the local orientation and interactions of the water molecules). We systematically analyze the agreement of these models with experimental observables and the effect of adding macroscopic information to the training set. Our results demonstrate how adding microscopic-rich information in the training of water models allows one to achieve state-of-the-art accuracy in an efficient way. Limitations in the approach and in the approximated description of water in these three-site models are also discussed, providing a demonstrative case useful for the optimization of approximated molecular models, in general.

Dynamics of Hydrogen Bonds between Water and Intrinsically Disordered and Structured Regions of Proteins

Recent studies indicate more restricted dynamics of water around intrinsically disordered proteins (IDPs) than structured proteins. We examine here the dynamics of hydrogen bonds between water molecules and two proteins, small ubiquitin-related modifier-1 (SUMO-1) and ubiquitin-conjugating enzyme E2I (UBC9), which we compare around intrinsically disordered regions (IDRs) and structured regions of these proteins. It has been recognized since some time that excluded volume effects, which influence access of water molecules to hydrogen-bonding sites, and the strength of hydrogen bonds between water and protein affect hydrogen bond lifetimes. While we find those two properties to mediate lifetimes of hydrogen bonds between water and protein residues in this study, we also find that the lifetimes are affected by the concentration of charged groups on other nearby residues. These factors are more important in determining the hydrogen bond lifetimes than whether a residue hydrogen bonding with water belongs to an IDR or to a structured region.

Turning an energy-based defect detector into a multi-molecule structural indicator for water

Recent studies have provided conclusive evidence for the existence of a liquid-liquid critical point in numerical models of water. Such a scenario implies the competition between two local molecular arrangements of different densities: a high-density liquid (HDL) and a low-density liquid (LDL). Within this context, the development of accurate structural indicators to properly characterize the two interconverting local structures is demanded. In a previous study, we introduced a reliable energy-based structural descriptor that properly discriminates water molecules into tetrahedrally arranged molecules (T molecules) and distorted molecules (D molecules). The latter constitute defects in terms of hydrogen bond (HB) coordination and have been shown to represent a minority component, even at high temperatures above the melting point. In addition, the D molecules tend to form high-quality HBs with three T molecules and to be surrounded by T and D molecules at further distances. Thus, it became evident that, while the LDL state might consist of a virtually pure T state, the HDL state would comprise mixed molecular arrangements including the D molecules. Such a need to abandon the single-molecule description requires the investigation of the degree of structural information to be incorporated in order to build an appropriate multi-molecule indicator. Hence, in this work, we shall study the effect of the local structural constraints on the water molecules in order to discriminate the different molecular arrangements into two disjoint classes. This will enable us to build a multi-molecule structural indicator for water whose performance will then be investigated within the water's supercooled regime.