Reevaluating Self-Cleaning Performance of Nanostructured Superhydrophobic Coatings

Self-cleaning is widely regarded as an inherent property of superhydrophobic surfaces, yet it often deteriorates under realistic environmental contamination, revealing a fundamental gap between simplified laboratory tests of self-cleaning performance and practical service. Here, we establish a multimodal, particle-size-resolved methodology to systematically reassess the self-cleaning behavior of a nanostructured superhydrophobic (nano-SH) coating through superhydrophobicity tracking and microscopic residue analyses. Using hydrophilic SiO₂@polydopamine particles spanning 10 nm-100 μm and three contamination modes (solid particles, water dispersions, and ethanol dispersions), we quantitatively correlate superhydrophobicity evolution with contaminant retention. We identify a previously unreported size-governed fouling pathway and introduce a nanostructure-defined critical particle size (<i>d</i>_critical) that dictates the transition between efficient removal and persistent fouling. Solid particles smaller than <i>d</i>_critical become lodged within the nanostructure of the coating yet cause little superhydrophobicity degradation, whereas water dispersions preserve the Cassie-Baxter state and entirely prevent particle infiltration. In contrast, low-surface-tension ethanol induces capillary penetration and mechanical locking of nanoparticles below <i>d</i>_critical into submicrometer pores, causing an irreversible and significant decline of superhydrophobicity. An eight month outdoor exposure test further confirms that the nano-SH coating resists complex atmospheric fouling, maintains nanostructural integrity, and preserves high superhydrophobicity. Overall, this work bridges laboratory evaluations with real-world conditions and provides a mechanistic framework for designing durable superhydrophobic coatings capable of long-term self-cleaning in complex environments.