Predictive model of ice adhesion on non-elastomeric materials.

Area of Science:

• Materials Science
• Surface Science
• Engineering Physics

Background:

• Ice accumulation on surfaces poses risks in infrastructure, transportation, and energy.
• Existing models for ice adhesion strength on shedding materials fail to account for substrate variations.
• The influence of the underlying substrate on ice adhesion has been overlooked.

Purpose of the Study:

• To develop a comprehensive predictive model for ice adhesion strength.
• To investigate the role of the underlying substrate in ice adhesion.
• To explain variations in measured ice adhesion across different laboratories.

Main Methods:

• Developed a predictive model for ice adhesion using the shear force method on multi-layered materials.
• Incorporated shear resistance of the coating and shear stress transfer to the substrate into the model.
• Conducted experimental validation of the model using various coating and substrate properties.

Main Results:

• The model highlights the critical role of the underlying substrate in determining ice adhesion strength.
• The relationship between ice adhesion and coating thickness differs significantly for elastomeric and non-elastomeric materials.
• The model successfully explains variations in ice adhesion measurements across different studies.

Conclusions:

• The developed model provides a framework for understanding and predicting ice adhesion.
• It elucidates how to achieve materials with both low ice adhesion and high mechanical durability.
• This research facilitates innovation in designing advanced ice-shedding materials for diverse applications.