Hydrophobic membranes used in membrane distillation (MD) systems are often subject to wetting during long-term operation. Thus, it is of great importance to fully understand factors that influence the wettability of hydrophobic membranes and their impact on the overall separation efficiency that can be achieved in MD systems. This Critical Review summarizes both fundamental and applied aspects of membrane wetting with particular emphasis on interfacial interaction between the membrane and solutes in the feed solution. First, the theoretical background of surface wetting, including the relationship between wettability and interfacial interaction, definition and measurement of contact angle, surface tension, surface free energy, adhesion force, and liquid entry pressure, is described. Second, the nature of wettability, membrane wetting mechanisms, influence of membrane properties, feed characteristics and operating conditions on membrane wetting, and evolution of membrane wetting are reviewed in the context of an MD process. Third, specific membrane features that increase resistance to wetting (e.g., superhydrophobic, omniphobic, and Janus membranes) are discussed briefly followed by the comparison of various cleaning approaches to restore membrane hydrophobicity. Finally, challenges with the prevention of membrane wetting are summarized, and future work is proposed to improve the use of MD technology in a variety of applications.

The expansion of oil and gas extraction from unconventional reservoirs has led to an increase in the amount of produced water that has to be managed by this industry. Direct contact membrane distillation (DCMD) is a promising technology for treatment of produced water to enable water recovery and reduce the environmental footprint of this industry. The feasibility of DCMD for the treatment of highly saline produced water from the Permian Basin in TX with commercially available polyethylene and polytetrafluoroethylene membranes was evaluated in this study. An increase in water recovery by a DCMD system operated in the batch (concentrating) mode led to an increase in permeate conductivity. Partial removal of organic compounds from the produced water by biodegradation, chemical oxidation, and/or activated carbon adsorption could not resolve deterioration in permeate quality, and none of the organics observed in the permeate contributed to its conductivity. The observed increase in permeate conductivity was attributed to the passage of ammonia vapor from the feed side followed by protonation on the permeate side. This study revealed that permeate conductivity may not always be a reliable indicator of membrane wetting and underscores the importance of understanding the interactions between specific solutes and membrane materials.

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We quantified the impact of support interactions on the binding and interaction energies of CO and O adsorbed on Pt 13 nanoclusters supported on amorphous silica surfaces through the use of density functional theory calculations. We used an accurate model for amorphous silica having two different surface silanol concentrations, corresponding to low (200 °C) and high (715 °C) surface pretreatment temperatures. We compared CO and O adsorbed on supported and freestanding Pt 13 clusters. We found that Pt 13 is highly susceptible to both support-and adsorbate-induced reconstruction, depending on the relaxed structure of the Pt 13 cluster on the surface. Structure relaxation effects dominate over electronic effects of the support. We considered an ensemble of 50 different systems by varying the placement of the Pt 13 cluster on the surfaces and by exploring a range of different binding sites for CO and O on the Pt 13 cluster. In select cases, binding energy differences between supported and freestanding Pt 13 are as large as 2 eV. However, the mean absolute error between supported and freestanding clusters over all systems we studied is only a few tenths of an eV. Coverage effects on coadsorption of CO and O are significantly different on supported clusters compared with the Pt(111) surface. Our results can be used for predicting when support interactions may be important for any reaction catalyzed by small metal nanoclusters.

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