In this master’s thesis, we investigated the interaction of water droplets with superhydrophobic surfaces and the influence of surface geometry on ice adhesion. We examined relevant theoretical foundations, including droplet rebound phenomena, transition between Cassie-Baxter and Wenzel regimes, and established methodologies for quantifying ice adhesion. By combining laser structuring and hydrophobization, we prepared several superhydrophobic aluminum surfaces with different microgeometries, on which more than 3500 droplet impact measurements were performed using water and water–glycerol mixtures. Using the collected dataset, machine learning was used to develop equations for predicting the rebound efficiency and the maximum spreading factor, which we compared with existing mathematical models from the literature. Using the droplet compression method between two surfaces, we identified the conditions under which the Cassie–Baxter wetting regime collapses. Through ice adhesion measurements using a custom-built testing setup we determined tje necessary shear strength to remove an ice cube from the surface. Based on the results, we analyzed the relationship between surface structure, droplet rebound behavior, and ice adhesion.
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