| Literature DB >> 30610171 |
Bingqing Cheng1, Edgar A Engel2, Jörg Behler3,4, Christoph Dellago5, Michele Ceriotti2.
Abstract
Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations, and proton disorder. This is made possible by combining advanced free-energy methods and state-of-the-art machine-learning techniques. The ab initio description leads to structural properties in excellent agreement with experiments and reliable estimates of the melting points of light and heavy water. We observe that nuclear-quantum effects contribute a crucial [Formula: see text] to the stability of ice Ih, making it more stable than ice Ic. Our computational approach is general and transferable, providing a comprehensive framework for quantitative predictions of ab initio thermodynamic properties using machine-learning potentials as an intermediate step.Entities:
Keywords: ab initio thermodynamics; density functional theory; machine-learning potential; nuclear quantum effects; water
Year: 2019 PMID: 30610171 PMCID: PMC6347673 DOI: 10.1073/pnas.1815117116
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205