Superhydrophobic surfaces (SHS) are often obtained by chemical coatings or low-surface-energy materials, yet such approaches suffer from limited durability and environmental concerns. This thesis explores a purely geometry-driven strategy to realize SHS on intrinsically hydrophilic substrates, using two-photon polymerization (TPP) for high-fidelity fabrication. The study begins with conventional geometries such as pillar arrays, where parametric analyses revealed how variations in height, width, and spacing influence wettability. Although these designs improved hydrophobicity, they consistently failed to achieve the superhydrophobic threshold. Building on these limitations, bioinspired Salvinia-like architectures were developed. By tuning arm number, diameter, spacing, and hierarchical arrangements, contact angles above 160° were obtained, confirming that geometry alone can induce stable Cassie–Baxter states without chemical modification. To address robustness, advanced design strategies introduced vertical self-similarity, lateral staggering, and hybrid architecture. These structures exploit structural periodicity: when one tier is removed by abrasion, the next periodic unit regenerates the surface functionality. As a result, multi-tier hybrid designs maintained superhydrophobicity over abrasion depths corresponding to an entire structural period (40 µm) even up to approximately 60 µm, far exceeding the performance of single-tier configurations. Robustness was further validated through evaporation-induced transition and droplet impact experiments, which confirmed the stability of air entrapment under dynamic and wear conditions. This work establishes a geometry-only framework for designing durable SHS on hydrophilic materials. By linking structural periodicity with functional recovery, it provides generalizable principles for scalable applications in self-cleaning, anti-fouling, drag reduction, microfluidics, and other domains requiring long-lasting water repellency.
Manufacturing of microstructured surfaces for advanced functionality
LIU, KAI
2026
Abstract
Superhydrophobic surfaces (SHS) are often obtained by chemical coatings or low-surface-energy materials, yet such approaches suffer from limited durability and environmental concerns. This thesis explores a purely geometry-driven strategy to realize SHS on intrinsically hydrophilic substrates, using two-photon polymerization (TPP) for high-fidelity fabrication. The study begins with conventional geometries such as pillar arrays, where parametric analyses revealed how variations in height, width, and spacing influence wettability. Although these designs improved hydrophobicity, they consistently failed to achieve the superhydrophobic threshold. Building on these limitations, bioinspired Salvinia-like architectures were developed. By tuning arm number, diameter, spacing, and hierarchical arrangements, contact angles above 160° were obtained, confirming that geometry alone can induce stable Cassie–Baxter states without chemical modification. To address robustness, advanced design strategies introduced vertical self-similarity, lateral staggering, and hybrid architecture. These structures exploit structural periodicity: when one tier is removed by abrasion, the next periodic unit regenerates the surface functionality. As a result, multi-tier hybrid designs maintained superhydrophobicity over abrasion depths corresponding to an entire structural period (40 µm) even up to approximately 60 µm, far exceeding the performance of single-tier configurations. Robustness was further validated through evaporation-induced transition and droplet impact experiments, which confirmed the stability of air entrapment under dynamic and wear conditions. This work establishes a geometry-only framework for designing durable SHS on hydrophilic materials. By linking structural periodicity with functional recovery, it provides generalizable principles for scalable applications in self-cleaning, anti-fouling, drag reduction, microfluidics, and other domains requiring long-lasting water repellency.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/360411
URN:NBN:IT:UNIPD-360411