Surface evolver simulations of drops on microposts

TL;DR

This paper adapts the Surface Evolver algorithm to predict the collapse transition of droplets on microposts, revealing how post shape influences the stability of superhydrophobic Cassie states.

Contribution

It introduces a method to simulate the collapse transition on arbitrarily shaped posts, improving understanding of stability factors in superhydrophobic surfaces.

Findings

Curved posts with horizontal sections stabilize the Cassie state better.

The algorithm accurately predicts depinning mechanisms.

Post shape significantly affects transition parameters.

Abstract

An important feature in the design of superhydrophobic surfaces is their robustness against collapse from the Cassie-Baxter configuration to the Wenzel state. Upon such a transition a surface loses its properties of low adhesion and friction. We describe how to adapt the Surface Evolver algorithm to predict the parameters and mechanism of the collapse transition on posts of arbitrary shape. In particular, contributions to the free energy evaluated over the solid-liquid surface are reduced to line integrals to give good convergence. The algorithm is validated for straight, vertical and inclined, posts. Numerical results for curved posts with a horizontal section at their ends show that these are more efficient in stabilising the Cassie state than straight posts, and identify whether the interface first depins from the post sides or the post tips.