Kinetics and Mechanisms of Pressure-Induced Ice Amorphization and Polyamorphic Transitions in a Machine-Learned Coarse-Grained Water Model

D Dhabal and V Molinero, JOURNAL OF PHYSICAL CHEMISTRY B, 127, 2847-2862 (2023).

DOI: 10.1021/acs.jpcb.3c00434

Water glasses have attracted considerable attention due to their potential connection to a liquid-liquid transition in supercooled water. Here we use molecular simulations to investigate the formation and phase behavior of water glasses using the machinelearned bond-order parameter (ML-BOP) water model. We produce glasses through hyperquenching of water, pressure-induced amorphization (PIA) of ice, and pressure-induced polyamorphic transformations. We find that PIA of polycrystalline ice occurs at a lower pressure than that of monocrystalline ice and through a different mechanism. The temperature dependence of the amorphization pressure of polycrystalline ice for ML-BOP agrees with that in experiments. We also find that ML-BOP accurately reproduces the density, coordination number, and structural features of low-density (LDA), high- density (HDA), and very highdensity (VHDA) amorphous water glasses. ML- BOP accurately reproduces the experimental radial distribution function of LDA but overpredicts the minimum between the first two shells in high-density glasses. We examine the kinetics and mechanism of the transformation between low-density and high-density glasses and find that the sharp nature of these transitions in ML-BOP is similar to that in experiments and all-atom water models with a liquid-liquid transition. Transitions between ML-BOP glasses occur through a spinodal- like mechanism, similar to ice crystallization from LDA. Both glass-to- glass and glass-to-ice transformations have Avrami-Kolmogorov kinetics with exponent n = 1.5 +/- 0.2 in experiments and simulations. Importantly, ML-BOP reproduces the competition between crystallization and HDA -> LDA transition above the glass transition temperature Tg, and separation of their time scales below Tg, observed also in experiments. These findings demonstrate the ability of ML-BOP to accurately reproduce water properties across various regimes, making it a promising model for addressing the competition between polyamorphic transitions and crystallization in water and solutions.

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