Osmocapillary phase separation at contact lines

Swollen soft materials have various uncommon wetting properties, such as anomalous contact angles, extremely low adhesion, stimuli-responsive adhesion, and time-dependent wetting. These properties are related to the solvent exudation near the contact lines. Existing studies assume that the phenomenon is governed by the elastocapillary effect, predicting that a stiffer material suppresses the solvent exudation. Here we show that the phenomenon is governed by the osmocapillary effect instead, predicting that a stiffer material promotes solvent exudation while a higher osmotic pressure suppresses it. We combine a small-deformation analytical model and nonlinear finite element simulations to develop a model that quantitatively predicts a wide range of existing experimental data with no fitting parameters.

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Publication Details

Journal
Soft Matter
Published
2025-01-01
DOI
https://doi.org/10.1039/d5sm00325c
Citations
3
Primary Topic
Adhesion, Friction, and Surface Interactions
Type
article
Field-Weighted Citation Impact
2.59

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article

Osmocapillary phase separation at contact lines

Qihan Liu, Luochang Wang
3 citations
Soft Matter
Adhesion, Friction, and Surface Interactions
2.59
article

Osmocapillary phase separation at contact lines

Qihan Liu, Luochang Wang
article en
3 citations

Abstract

Swollen soft materials have various uncommon wetting properties, such as anomalous contact angles, extremely low adhesion, stimuli-responsive adhesion, and time-dependent wetting. These properties are related to the solvent exudation near the contact lines. Existing studies assume that the phenomenon is governed by the elastocapillary effect, predicting that a stiffer material suppresses the solvent exudation. Here we show that the phenomenon is governed by the osmocapillary effect instead, predicting that a stiffer material promotes solvent exudation while a higher osmotic pressure suppresses it. We combine a small-deformation analytical model and nonlinear finite element simulations to develop a model that quantitatively predicts a wide range of existing experimental data with no fitting parameters.

Soft MatterVol. 21(32)
University of Pittsburgh (US)
National Science Foundation
Openalex Percentile: Top 10%
Adhesion, Friction, and Surface Interactions
2.59
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