Ab initio theory and modeling of water (1709.10493v1)

Abstract: 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 I{\it h} 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.

• The paper presents SCAN's ability to predict water's density anomalies by accurately balancing hydrogen and van der Waals interactions.
• It demonstrates superior structural and dynamic predictions that closely match experimental radial distribution functions and diffusion coefficients.
• SCAN-driven electronic structure estimates correct prior DFT inaccuracies, offering deeper insights into water's hydrogen bonding network.

Overview of "Ab initio Theory and Modeling of Water"

The paper "Ab initio Theory and Modeling of Water" primarily focuses on addressing the longstanding challenge of accurately modeling water at the molecular level using first-principles approaches. The researchers in this paper apply the strongly constrained and appropriately normed (SCAN) density functional to capture the intricate balance of intermolecular forces, specifically focusing on covalent bonds, hydrogen bonds, and van der Waals (vdW) interactions. This work not only presents a comprehensive assessment of the structural, electronic, and dynamic properties of water but also compares the predictions from SCAN to experimental data and previous density functional theory (DFT) approaches, such as the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA).

Key Highlights

1. Predictive Modeling with SCAN: The SCAN functional is a non-empirical meta-GGA that adheres to known exact constraints. The authors demonstrate that it effectively captures the relative densities of liquid water and ice I\textsubscript{h}, in line with experimental observations, where previous models like PBE have failed. This indicates that SCAN excels in balancing the various types of bonding forces that are critical for accurately predicting the phase density anomalies in water.
2. Structural and Dynamic Properties: SCAN provides a superior description of the radial distribution functions (RDFs), capturing the features in agreement with experimental data, notably in the oxygen-oxygen and oxygen-hydrogen correlations. Furthermore, it adjusts hydrogen bond strengths, leading to improved predictions of dynamic properties, such as diffusion coefficients and rotational correlation times, showing significant agreement with experimental values.
3. Electronic Structure: The electronic density of states (DOS) derived using SCAN aligns well with photoemission experiments, correcting discrepancies noted in previous models. This correction is indicative of improved electronic structural predictions, which play a critical role in describing the hydrogen bonding network and associated properties like the dipole moment.
4. Impact of van der Waals Interactions: The paper emphasizes that SCAN's capacity to describe intermediate-ranged vdW interactions is crucial for producing a more disordered and dense liquid water structure. The paper finds that these interactions influence both the structural compactness and thermal properties of water, including its density and tetrahedral order.

Numerical Results and Implications

• SCAN predicts the density of water to be 1.050 g/mL compared to the experimental density of 0.99656 g/mL, significantly closer than that predicted by other methods such as PBE, which predicts a lower density of 0.850 g/mL.
• SCAN successfully predicts that ice has a lower density than water, correctly modeling the natural buoyancy phenomena observed experimentally.
• The calculated diffusion coefficient using SCAN is 0.190 Å$^2$/ps, aligning closely with the experimental value of 0.187 Å$^2$/ps.

The successful implementation of SCAN advances the theoretical understanding of liquid water and establishes a foundation for more accurate simulations of aqueous phase processes, chemical reactions, and other phenomena influenced by water's unique molecular interactions. The implications extend further to studies of complex systems in heterogeneous environments and interfaces, where the competition between van der Waals forces and hydrogen bonding becomes critical.

Future Directions

This paper lays the groundwork for future research that could incorporate nuclear quantum effects to further refine the predictions of the molecular dynamics of water. The SCAN functional's enhanced capabilities suggest its promising application in broader contexts, including materials science and biological systems that rely on the unique properties of water. Bridging these insights with experimental techniques could further resolve ongoing debates and refine theoretical models pertaining to water and other complex molecular liquids. Additionally, computational efficiency remains a focal point for developing these predictive models to extend their applicability across larger and more diverse systems.