Correlation between surface morphology, superhydrophobicity, and icephobic behavior: a principal component analysis study

This study aimed to investigate the relationships between topographical parameters, wetting properties, and the icephobic behavior of textured surfaces. Principal component analysis (PCA) of the wetting data revealed a strong correlation between the slope of the patterns and the contact angle. However, because wetting states are not always reported with sufficient explanation, they were determined using the Extrand model. In some cases, discrepancies with experimental results were observed, likely due to metastable states caused by droplet pinning on micro-roughness. A separate PCA on icing delay time (IDT) data indicated a correlation between slope, contact angle, and IDT, without requiring prior knowledge of the wetting state. In contrast, PCA on ice adhesion data revealed no clear correlation, highlighting a lack of standardization in the field that hinders comparisons. To refine the results, another PCA was conducted using the Extrand-model-predicted wetting states, emphasizing the importance of accurately identifying the wetting regime to understand surface behavior. Given the challenges in correlating adhesion measurements, IDT emerges as a more relevant and accessible initial metric for evaluating icephobic properties. Finally, pattern slope appears to be a key topographical parameter. While other parameters showed no direct correlations, appropriate feature height and limited spacing are still critical to prevent complete droplet penetration.