Liquid water contains the building blocks of diverse ice phases

• Published in: Nature communications Vol. 11; no. 1; p. 5757
• Main Authors: Monserrat, Bartomeu, Brandenburg, Jan Gerit, Engel, Edgar A., Cheng, Bingqing
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 13.11.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 119/118; 639/301/119; 639/638/440; 639/638/563/606; 639/638/563/981; Complexity; Datasets; Fluid dynamics; Humanities and Social Sciences; Ice; Learning algorithms; Machine learning; Molecular modelling; multidisciplinary; Phases; Physical properties; Physical simulation; Principal components analysis; Science; Science (multidisciplinary); Water; Water chemistry
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-020-19606-y

Water molecules can arrange into a liquid with complex hydrogen-bond networks and at least 17 experimentally confirmed ice phases with enormous structural diversity. It remains a puzzle how or whether this multitude of arrangements in different phases of water are related. Here we investigate the structural similarities between liquid water and a comprehensive set of 54 ice phases in simulations, by directly comparing their local environments using general atomic descriptors, and also by demonstrating that a machine-learning potential trained on liquid water alone can predict the densities, lattice energies, and vibrational properties of the ices. The finding that the local environments characterising the different ice phases are found in water sheds light on the phase behavior of water, and rationalizes the transferability of water models between different phases. Molecular understanding of water is challenging due to the structural complexity of liquid water and the large number of ice phases. Here the authors use a machine-learning potential trained on liquid water to demonstrate the structural similarity of liquid water and that of 54 real and hypothetical ice phases.