Investigating the Quasi-Liquid Layer on Ice Surfaces: a Comparison of Order Parameters

Jihong Shi, Maxwell Fulford, Hui Li, Mariam Marzook, Maryam Reisjalali, Matteo Salvalaglio, Carla Molteni

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Ice surfaces are characterized by pre-melted quasi-liquid layers (QLLs), which mediate both crystal growth processes and interactions with external agents. Understanding QLLs at the molecular level is necessary to unravel the mechanisms of ice crystal formation. Computational studies of the QLLs heavily rely on the accuracy of the methods employed for identifying the local molecular environment and arrangements, discriminating between solid-like and liquid-like water molecules. Here we compare the results obtained using different order parameters to characterize the QLLs on hexagonal ice (Ih) and cubic ice (Ic) model surfaces investigated with molecular dynamics (MD) simulations in a range of temperatures. For the classification task, in addition to the traditional Steinhardt order parameters in different flavours, we select an entropy fingerprint and a deep learning neural network approach (DeepIce), which are conceptually different methodologies. We find that all the analysis methods give qualitatively similar trends for the behaviours of the QLLs on ice surfaces with temperature, with some subtle differences in the classification sensitivity limited to the solid–liquid interface. The thickness of QLLs on the ice surface increases gradually as the temperature increases. The trends of the QLL size and of the values of the order parameters as a function of temperature for the different facets may be linked to surface growth rates which, in turn, affect crystal morphologies at lower vapour pressure. The choice of the order parameter can be therefore informed by computational convenience except in cases where a very accurate determination of the liquid–solid interface is important.
Original languageEnglish
Pages (from-to)12476-12487
Number of pages12
JournalPhysical Chemistry Chemical Physics
Volume24
Issue number20
DOIs
Publication statusPublished - 5 May 2022

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