Ab initio theory and modeling of water

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.

References in corpus (12)

• Quantum ESPRESSO: a modular and open-source software project for quantum simulations of materials
• Maximally localized Wannier functions: Theory and applications
• Perspective: How good is DFT for water?
• Nuclear quantum effects in water
• The Individual and Collective Effects of Exact Exchange and Dispersion Interactions on the Ab Initio Structure of Liquid Water
• Density, structure and dynamics of water: the effect of Van der Waals interactions
• Acceleration Schemes for Ab-Initio Molecular Dynamics and Electronic Structure Calculations
• On the Accuracy of van der Waals Inclusive Density-Functional Theory Exchange-Correlation Functionals for Ice at Ambient and High Pressures
• Isobaric first-principles molecular dynamics of liquid water with nonlocal van der Waals interactions
• Dissecting Hydrophobic Hydration and Association
• Deconstructing classical water models at interfaces and in bulk
• Liquid Water through Density-Functional Molecular Dynamics: Plane-Wave vs Atomic-Orbital Basis Sets

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