From wetting mechanisms to anti-wetting membrane design: An interfacial and colloidal perspective on membrane distillation.

Authors

Abduelrahman Adam Omer, Duo Wang, Yong Wang, Chao Yang

Published in

Advances in colloid and interface science. Volume 358. Pages 104032. Aug 26, 2026. Epub Aug 26, 2026.

Abstract

Membrane distillation (MD) is a promising thermally driven desalination technology due to its high rejection of non-volatile contaminants and its ability to operate under relatively mild conditions. However, membrane wetting remains a persistent challenge that hinders its distillation efficiency and long-term application. This review presents a mechanism-based perspective on MD wetting by linking capillary pressure imbalance, surface-tension reduction, surfactant adsorption, scaling, and colloid-driven interfacial interactions to pore invasion and performance deterioration. The influence of key membrane properties, including hydrophobicity, liquid entry pressure, surface free energy, pore structure, and thermal conductivity, was discussed in relation to wetting resistance. Building on this mechanistic understanding, four anti-wetting strategies are examined, including stabilization of the Cassie-Baxter state through hierarchical structures, extension of liquid repellency using ultralow-surface-energy materials, asymmetric interfacial regulation through Janus architectures, and dynamic interfacial regulation using stimuli-responsive membranes. Furthermore, the role of engineered colloidal nanomaterials as versatile building blocks for anti-wetting interfaces is discussed across the four design strategies. Artificial intelligence and machine learning, particularly inverse design and physics-informed approaches, are highlighted as emerging tools for membrane discovery and optimization. Future perspectives are outlined toward mechanism-guided membrane fabrication, validation under realistic feed conditions, and data-driven design of durable anti-wetting MD membranes. This review proposes anti-wetting strategies as well as design principles in the separation applications.

PMID:
42669237
Bibliographic data and abstract were imported from PubMed on 31 Aug 2026.

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