Topology optimization of robust superhydrophobic surfaces

TL;DR

This paper introduces a topology optimization method for designing micro-structured superhydrophobic surfaces, identifying optimal branching post geometries that enhance water repellency and are inspired by biological strategies.

Contribution

It is the first application of topology optimization to micro-structured superhydrophobic surfaces, revealing optimal branching geometries for improved performance.

Findings

Branching post cross-sections are optimal for superhydrophobicity.

Topology optimization effectively identifies geometries that minimize liquid penetration.

Filtering techniques allow control over the design's characteristic length scale.

Abstract

In this paper we apply topology optimization to micro-structured superhydrophobic surfaces for the first time. It has been experimentally observed that a droplet suspended on a brush of micrometric posts shows a high static contact angle and low roll-off angle. To keep the fluid from penetrating the space between the posts, we search for an optimal post cross section, that minimizes the vertical displacement of the liquid-air interface at the base of the drop when a pressure difference is applied. Topology optimisation proves effective in this framework, showing that posts with a branching cross-section are optimal, which is consistent with several biologic strategies to achieve superhydrophobicity. Through a filtering technique, we can also control the characteristic length scale of the optimal design, thus obtaining feasible geometries