Multifaceted design optimization for superomniphobic surfaces.

Abstract:

:Superomniphobic textures are at the frontier of surface design for vast arrays of applications. Despite recent substantial advances in fabrication methods for reentrant and doubly reentrant microstructures, design optimization remains a major challenge. We overcome this in two stages. First, we develop readily generalizable computational methods to systematically survey three key wetting properties: contact angle hysteresis, critical pressure, and minimum energy wetting barrier. For each, we uncover multiple competing mechanisms, leading to the development of quantitative models and correction of inaccurate assumptions in prevailing models. Second, we combine these analyses simultaneously, demonstrating the power of this strategy by optimizing structures that are designed to overcome challenges in two emerging applications: membrane distillation and digital microfluidics. As the wetting properties are antagonistically coupled, this multifaceted approach is essential for optimal design. When large surveys are impractical, we show that genetic algorithms enable efficient optimization, offering speedups of up to 10,000 times.

journal_name

Sci Adv

journal_title

Science advances

authors

Panter JR,Gizaw Y,Kusumaatmaja H

doi

10.1126/sciadv.aav7328

subject

Has Abstract

pub_date

2019-06-21 00:00:00

pages

eaav7328

issue

6

issn

2375-2548

pii

aav7328

journal_volume

5

pub_type

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