Experimental study demonstrates active wettability control via 3D-printed bioinspired microstructures on dielectric elastomer actuators, suggesting applications in programmable microfluidics.
Bioinspired functional surfaces with tunable wettability have garnered significant attention in surface engineering due to their potential in applications, such as self-cleaning and microfluidic control. However, existing wettability modulation methods often face limitations in response time, control precision, and repeatability. Herein, this study presents a biomimetic design for active wettability control by integrating 3D-printed Salvinia molesta -inspired microstructures controlled by dielectric elastomer actuators (DEAs). Using two-photon polymerization, hierarchical eggbeater microstructures were precisely fabricated on a flexible, stretchable, and transparent polymer film, achieving robust interfacial bonding and demonstrating 90.8% shape recovery after deformation. Systematic evaluation of the hydrophobic properties revealed that designs with a higher number of concentric rings and reduced center-to-center spacing exhibited enhanced water droplet adhesion while maintaining Cassie–Baxter state suspension. The fabricated microstructures demonstrated tunable hydrophobicity, achieving contact angles of 140.8 ± 1.4° to 149.7 ± 1.8° in the Cassie–Baxter state and roll-off angles of 5.7 ± 0.9° to 30.0 ± 1.6°, indicating precise control over wetting behavior. The DEA system enabled dynamic wettability modulation through voltage-controlled adjustment of microstructure spacing, facilitating rapid transitions from Cassie–Baxter to Wenzel states. In addition, the DEA-induced programmable microstructure enabled surface adhesion modification, allowing droplet manipulation and transportation. This innovative integration of biomimetic microstructures with DEA technology offers significant potential for advanced applications requiring fast, reversible wettability control, including droplet-based microfluidics and active self-cleaning surfaces.
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Yang et al. (2025) studied this question.
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