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Critical review of modeling, measurement, and prediction of ice nucleation on surfaces.

Author(s) : GARDNER D. B., WANG H.

Type of article: IJR article, Review

Summary

The freezing of water on surfaces is an important phase change process with an outsized influence in both natural and engineered systems. Liquid water below the melting temperature can persist for a finite time in a metastable, supercooled state until freezing initiates through nucleation, a process enhanced by the presence of a surface. Despite the importance of this phenomenon, current methods remain inadequate to predict ice nucleation rates across surface types, and experimental data is difficult to compare due to the differing methodologies used, limiting further understanding. This review synthesizes established frameworks modeling ice nucleation and analyzes limitations in applying classical nucleation theory toward quantitative prediction. Simplified, theory-inspired models used to describe the nucleation rate as a function of temperature are discussed. Additionally, models describing how the ice nucleation rate may vary across a surface are compared. Current experimental methods for measuring ice nucleation rates on surfaces are assessed for their ability to produce accurate data that can lead to greater consistency between studies. Variability in results based on factors such as humidity and triple interface effects are discussed. Statistical analysis approaches for experimental freezing data are reviewed. Experimental observations of nonstationary ice nucleation in an unexpectedly large time scale are discussed in the context of experimental methods. Finally, the potential of emerging machine learning techniques to aid in predicting heterogeneous ice nucleation is discussed.

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Format PDF

Pages: 32-44

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Details

  • Original title: Critical review of modeling, measurement, and prediction of ice nucleation on surfaces.
  • Record ID : 30032347
  • Languages: English
  • Subject: Technology
  • Source: International Journal of Refrigeration - Revue Internationale du Froid - vol. 163
  • Publication date: 2024/07
  • DOI: http://dx.doi.org/10.1016/j.ijrefrig.2024.04.005

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