Two state model for the ML-BOP potential

N Zorzi and A Neophytou and F Sciortino, MOLECULAR PHYSICS, 122 (2024).

DOI: 10.1080/00268976.2024.2407025

The coarse-grained machine-learning derived ML-BOP model Chan et al., Nature Commun. 10, 379 (2019) provides a monoatomic representation of the water-water interaction potential in which orientational interactions are included as three-body contributions. Despite its simplicity, the model reproduces the phase diagram of water and its anomalies. Here, we show that a two-state Gibbs free energy expression - fitted simultaneously on the temperature and pressure dependence of the density and internal energy - predicts the existence of a liquid-liquid critical point, with critical parameters consistent with previous estimates. We also show that in this model: (i) while the low density liquid is pre-empted by crystal nucleation, the high-density liquid and its spinodal are accessible in numerical studies down to 100 K; (ii) crystallisation requires the presence of a local low density region. Thus, for densities larger than the critical density, spinodal decomposition (or nucleation of the low-density liquid) is a pre- requisite for ice nucleation.

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