Literature DB >> 33507741

Role of Nanoscale Interfacial Proximity in Contact Freezing in Water.

Sarwar Hussain1, Amir Haji-Akbari1.   

Abstract

Contact freezing is a mode of atmospheric ice nucleation in which a collision between a dry ice nucleating particle (INP) and a water droplet results in considerably faster heterogeneous nucleation. The molecular mechanism of such an enhancement is, however, still a mystery. While earlier studies had attributed it to collision-induced transient perturbations, recent experiments point to the pivotal role of nanoscale proximity of the INP and the free interface. By simulating the heterogeneous nucleation of ice within INP-supported nanofilms of two model water-like tetrahedral liquids, we demonstrate that such nanoscale proximity is sufficient for inducing rate increases commensurate with those observed in contact freezing experiments, but only if the free interface has a tendency to enhance homogeneous nucleation. Water is suspected of possessing this latter property, known as surface freezing propensity. Our findings therefore establish a connection between the surface freezing propensity and kinetic enhancement during contact nucleation. We also observe that faster nucleation proceeds through a mechanism markedly distinct from classical heterogeneous nucleation, involving the formation of hourglass-shaped crystalline nuclei that conceive at either interface and that have a lower free energy of formation due to the nanoscale proximity of the interfaces and the modulation of the free interfacial structure by the INP. In addition to providing valuable insights into the physics of contact nucleation, our findings can assist in improving the accuracy of heterogeneous nucleation rate measurements in experiments and in advancing our understanding of ice nucleation on nonuniform surfaces such as organic, polymeric, and biological materials.

Entities:  

Year:  2021        PMID: 33507741     DOI: 10.1021/jacs.0c10663

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  2 in total

1.  Deep learning for unravelling features of heterogeneous ice nucleation.

Authors:  Chantal Valeriani
Journal:  Proc Natl Acad Sci U S A       Date:  2022-08-18       Impact factor: 12.779

2.  Accurate prediction of ice nucleation from room temperature water.

Authors:  Michael Benedict Davies; Martin Fitzner; Angelos Michaelides
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-25       Impact factor: 12.779

  2 in total

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