Density and Compressibility of Liquid Water and Ice from First-Principles Simulations with Hybrid Functionals

Gaiduk, Alex P.; Gygi, François; Galli, Giulia

doi:10.1021/acs.jpclett.5b00901

Cited by 92 publications

(109 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fig. 2b) and total densities are shifted to larger values (in agreement with AIMD simulations performed at a single state point [38,40,47]), reducing deviations from experiment to 5 -10 %. Moreover, a density minimum in the super- cooled regime (at ≈200 K and ≈215 K for BLYP-vdW and RPBE-vdW, respectively) can be identified that is consistent with experimental measurements of water confined in silica pores [37] and simulations using empirical water models [7,8].…”

Section: A Neural Network Potentialssupporting

confidence: 83%

How van der Waals interactions determine the unique properties of water

Morawietz

Singraber

Dellago

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

405

415

View full text Add to dashboard Cite

Whereas the interactions between water molecules are dominated by strongly directional hydrogen bonds (HBs), it was recently proposed that relatively weak, isotropic van der Waals (vdW) forces are essential for understanding the properties of liquid water and ice. This insight was derived from ab initio computer simulations, which provide an unbiased description of water at the atomic level and yield information on the underlying molecular forces. However, the high computational cost of such simulations prevents the systematic investigation of the influence of vdW forces on the thermodynamic anomalies of water. Here, we develop efficient ab initio-quality neural network potentials and use them to demonstrate that vdW interactions are crucial for the formation of water's density maximum and its negative volume of melting. Both phenomena can be explained by the flexibility of the HB network, which is the result of a delicate balance of weak vdW forces, causing, e.g., a pronounced expansion of the second solvation shell upon cooling that induces the density maximum.water structure | van der Waals interactions | neural network potentials | ab initio liquid water | density-functional theory W ater is an exceptional liquid exhibiting several anomalies, of which the density maximum at 4°C is the most prominent (1). Together with the negative volume of melting, it is responsible for the fact that water freezes from the top down and ice floats on water. The unusual behavior of water can be directly related to its ability to form hydrogen bonds (HBs) which are of strongly directional nature and determine the microscopic structure of water (2, 3). To investigate the anomalies of water at the molecular level, atomistic computer simulations have become an essential tool. Important contributions have been made by simulations using simple empirical water models (3-8).Simulations based on ab initio molecular dynamics (AIMD) (9-11) allow determination of the properties of water with high predictive power and enable a detailed analysis of their underlying microscopic mechanisms. In contrast to empirical water models (5), which depend on experimental data resulting in a limited transferability, in AIMD the atomic forces that govern the molecular dynamics are obtained directly from quantum mechanics. Although this approach is in principle exact [in combination with methods that account for the quantum nature of the nuclei (12, 13)], ab initio simulations of condensed matter systems are feasible only if approximate but efficient methods such as density-functional theory (DFT) are used. Even then, however, simulations are restricted to short times and small systems. AIMD simulations have been used to a limited extent to investigate the phase behavior of water, for instance by estimating melting temperatures (14, 15) and vapor-liquid coexistence curves (16, 17). However, many fundamental thermodynamic properties of water have not been evaluated to date. To circumvent the limitations of on-the-fly AIMD, various efficient water potentia...

show abstract

Section: A Neural Network Potentialssupporting

confidence: 83%

How van der Waals interactions determine the unique properties of water

Morawietz

Singraber

Dellago

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

405

415

View full text Add to dashboard Cite

show abstract

“…Related work has shown that revPBE gives even lower densities [144,276], with ρ eq ranging from 0.69 to 0.85 g/cm 3 . PBE also underestimates the density [144,273,276,[278][279][280], but more modestly, with ρ eq varying from 0.86 to 0.96 g/cm 3 in different studies. One of the few DFT studies of the moderately compressed liquid is that of Ref.…”

Section: Ggas and Hybridsmentioning

confidence: 99%

Perspective: How good is DFT for water?

Gillan

Alfè

Michaelides

2016

The Journal of Chemical Physics

698

687

View full text Add to dashboard Cite

This article presents a perspective on Kohn-Sham density functional theory (KS-DFT) for electronic structure calculations in chemical physics. This theory is in widespread use for applications to both molecules and solids. We pay special attention to several aspects where there are both concerns and progress toward solutions. These include: 1. The treatment of open-shell and inherently multiconfig-urational systems (the latter are often called multireference systems and are variously classified as having strong correlation, near-degeneracy correlation, or high static correlation; KS-DFT must treat these systems with broken-symmetry determinants). 2. The treatment of noncovalent interactions. 3. The choice between developing new functionals by parametrization, by theoretical constraints, or by a combination. 4. The ingredients of the exchange-correlation functionals used by KS-DFT, including spin densities, the magnitudes of their gradients, spin-specific kinetic energy densities, nonlocal exchange (Hartree-Fock exchange), nonlocal correlation, and subshell-dependent corrections (DFT+U). 5. The quest for a universal functional, where we summarize some of the success of the latest Minnesota functionals, namely MN15-L and MN15, which were obtained by optimization against diverse databases. 6. Time-dependent density functional theory, which is an extension of DFT to treat time-dependent problems and excited states. The review is a snapshot of a rapidly moving field, and-like Marcel Duchamp-we hope to convey progress in a stimulating way. Published by AIP Publishing. [http://dx.

show abstract

“…In contrast, the intermediate-and long-ranged parts of the vdW interactions have not been captured by any general-purpose GGA. Recent studies have identified vdW interactions as an important determinant of water structure; vdW interactions often lead to more disordered water structures, more accurate water densities, and improved dynamic properties (11,(24)(25)(26)(28)(29)(30). Thus, the H-bond network of liquid water is produced by a delicate competition among covalent bonds, H bonds, and vdW interactions, and describing this complex interplay of interactions continues to be a highly challenging task.…”

Section: Significancementioning

confidence: 99%

Ab initio theory and modeling of water

Chen

Remsing

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

425

407

View full text Add to dashboard Cite

Water is of the utmost importance for life and technology. However, a genuinely predictive ab initio model of water has eluded scientists. We demonstrate that a fully ab initio approach, relying on the strongly constrained and appropriately normed (SCAN) density functional, provides such a description of water. SCAN accurately describes the balance among covalent bonds, hydrogen bonds, and van der Waals interactions that dictates the structure and dynamics of liquid water. Notably, SCAN captures the density difference between water and ice Ih at ambient conditions, as well as many important structural, electronic, and dynamic properties of liquid water. These successful predictions of the versatile SCAN functional open the gates to study complex processes in aqueous phase chemistry and the interactions of water with other materials in an efficient, accurate, and predictive, ab initio manner.water | ab initio theory | hydrogen bonding | density functional theory | molecular dynamics W ater is arguably the most important molecule for life and is involved in almost all biological processes. Without water, life, as we know it, would not exist, earning water the pseudonym "matrix of life," among others (1). Despite the apparent simplicity of an H2O molecule, water in the condensed phase displays a variety of anomalous properties that originate from its complex structure. In an ideal arrangement, water molecules form a tetrahedral network of hydrogen (H) bonds with each vertex being occupied by a water molecule. This tetrahedral network is realized in the solid phase ice Ih, but thermal fluctuations disrupt the H-bond network in the liquid state, with the network fluctuating on picosecond to nanosecond timescales. Due to the complexity of the H-bond network and its competition with thermal fluctuations, a precise molecular-level understanding of the structure of liquid water remains elusive. Major challenges lie in unambiguously capturing the atomic-scale fluctuations in water experimentally. Current approaches such as time-resolved spectroscopy (2, 3) and diffraction measurements (4, 5) may be able to resolve changes on picosecond timescales but rely on interpretation through models, which often cannot describe all of the details of liquid water with quantitative accuracy. Not surprisingly, the nature of the H-bond network in liquid water continues to be at the center of scientific debate, and advances in both experiment and theory are needed, especially with regard to quantitative modeling of aqueous phase chemistry.Ab initio molecular dynamics (AIMD) simulation (6) is an ideal approach for modeling the condensed phases of water across the phase diagram and aqueous phase chemistry using quantum mechanical principles (7-11), although for some applications, such as the study of liquid vapor phase equilibria (12), Monte Carlo methods are better suited. In particular, Kohn-Sham density functional theory (DFT) (13)-used to model the system in its electronic ground state-provides an efficient framework that enables the si...

show abstract

Density and Compressibility of Liquid Water and Ice from First-Principles Simulations with Hybrid Functionals

Cited by 92 publications

References 83 publications

How van der Waals interactions determine the unique properties of water

How van der Waals interactions determine the unique properties of water

Perspective: How good is DFT for water?

Ab initio theory and modeling of water

Contact Info

Product

Resources

About