Predictive model of ice adhesion on non-elastomeric materials

[Display omitted] When ice accumulates on a surface, it can adversely impact functionality and safety of a platform in infrastructure, transportation, and energy sectors. Despite several attempts to model the ice adhesion strength on ice-shedding materials, none have been able to justify variation i...

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Veröffentlicht in:Journal of colloid and interface science 2023-10, Vol.648, p.481-487
Hauptverfasser: Nazifi, Sina, Firuznia, Rojan, Huang, Zixu, Jahanbakhsh, Amirmohammad, Ghasemi, Hadi
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Sprache:eng
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Zusammenfassung:[Display omitted] When ice accumulates on a surface, it can adversely impact functionality and safety of a platform in infrastructure, transportation, and energy sectors. Despite several attempts to model the ice adhesion strength on ice-shedding materials, none have been able to justify variation in the ice adhesion strength measured by various laboratories on a simple bare substrate. This is primarily due to the fact that the effect of underlying substrate of an ice-shedding material has been entirely neglected. Here, we establish a comprehensive predictive model for ice adhesion using the shear force method on a multi-layered material. The model considers both shear resistance of the material and shear stress transfer to the underlying substrate. We conducted experiments to validate the model predictions on the effect of coating and substrate properties on the ice adhesion. The model reveals the importance of the underlying substrate of a coating on ice adhesion. Most importantly, the correlation between the ice adhesion and the coating thickness are entirely different for elastomeric and non-elastomeric materials. This model justifies different measured ice adhesion across various laboratories on the same material and elucidates how one could achieve both low ice adhesion and high mechanical durability. Such predictive model and understanding provides a rich platform to guide the future material innovation with minimal adhesion to the ice.
ISSN:0021-9797
1095-7103
DOI:10.1016/j.jcis.2023.06.018