Density isobar of water and melting temperature of ice: Assessing common density functionals

Author(s): Pablo Montero de Hijes, Christoph Dellago, Ryosuke Jinnouchi, Georg Kresse
Abstract: We investigate the density isobar of water and the melting temperature of ice using six different density functionals. Machine-learning potentials are employed to ensure computational affordability. Our findings reveal significant discrepancies between various base functionals. Notably, even the choice of damping can result in substantial differences. Overall, the outcomes obtained through density functional theory are not entirely satisfactory across most utilized functionals. All functionals exhibit significant deviations either in the melting temperature or equilibrium volume, with most of them even predicting an incorrect volume difference between ice and water. Our heuristic analysis indicates that a hybrid functional with 25% exact exchange and van der Waals damping averaged between zero and Becke-Johnson dampings yields the closest agreement with experimental data. This study underscores the necessity for further enhancements in the treatment of van der Waals interactions and, more broadly, density functional theory to enable accurate quantitative predictions for molecular liquids.
Organisation(s): Department of Lithospheric Research, Computational and Soft Matter Physics, Computational Materials Physics
External organisation(s): Toyota Central R&D Labs., Inc., VASP Software GmbH
Journal: Journal of Chemical Physics
Volume: 161
No. of pages: 8
ISSN: 0021-9606
DOI: https://doi.org/10.1063/5.0227514
Publication date: 10-2024
Peer reviewed: Yes
Austrian Fields of Science 2012: 103015 Condensed matter, 102019 Machine learning
ASJC Scopus subject areas: Physics and Astronomy(all), Physical and Theoretical Chemistry
Portal url: https://ucrisportal.univie.ac.at/en/publications/density-isobar-of-water-and-melting-temperature-of-ice-assessing-common-density-functionals(0273f587-e27a-4240-b069-90ed9c1e9960).html