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 (dcritical) that dictates the transition between efficient removal and persistent fouling. Solid particles smaller than dcritical 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 dcritical 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.