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We investigate the structural similarities between liquid water and 53 ices,including 20 knowncrystalline phases. We base such similarity comparison on thelocal environments that consist of atoms within a certain cutoff radius of acentral atom. We reveal that liquid water explores the localenvironments of thediverse ice phases, by directly comparing the environments in these phasesusing general atomic descriptors, and also by demonstrating that amachine-learning potential trained on liquid water alone can predict thedensities, the lattice energies, and vibrational properties of theices. Thefinding that the local environments characterising the different ice phases arefound in water sheds light on water phase behaviors, and rationalizes thetransferability of water models between different phases.

Extracting ice phases from liquid water: why a machine-learning water model generalizes so well