Membrane distillation (MD) is a thermally induced membrane separation process that utilizes vapor pressure variance to permeate the more volatile constituent, typically water as vapor, across a hydrophobic membrane and rejects the less volatile components of the feed. Permeate flux decline, membrane fouling, and wetting are some serious challenges faced in MD operations. Thus, in recent years, various studies have been carried out on the modification of these MD membranes by incorporating nanomaterials to overcome these challenges and significantly improve the performance of these membranes. This review provides a comprehensive evaluation of the incorporation of new generation nanomaterials such as quantum dots, metalloids and metal oxide-based nanoparticles, metal organic frameworks (MOFs), and carbon-based nanomaterials in the MD membrane. The desired characteristics of the membrane for MD operations, such as a higher liquid entry pressure (LEPw), permeability, porosity, hydrophobicity, chemical stability, thermal conductivity, and mechanical strength, have been thoroughly discussed. Additionally, methodologies adopted for the incorporation of nanomaterials in these membranes, including surface grafting, plasma polymerization, interfacial polymerization, dip coating, and the efficacy of these modified membranes in various MD operations along with their applications are addressed. Further, the current challenges in modifying MD membranes using nanomaterials along with prominent future aspects have been systematically elaborated.

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Ultrafiltration (UF) as one of the mainstream membrane-based technologies has been widely used in water and wastewater treatment. Increasing demand for clean and safe water requires the rational design of UF membranes with antifouling potential, while maintaining high water permeability and removal efficiency. This work employed a machine learning (ML) method to establish and understand the correlation of five membrane performance indices as well as three major performance-determining membrane properties with membrane fabrication conditions. The loading of additives, specifically nanomaterials (A_wt %), at loading amounts of >1.0 wt % was found to be the most significant feature affecting all of the membrane performance indices. The polymer content (P_wt %), molecular weight of the pore maker (M_Da), and pore maker content (M_wt %) also made considerable contributions to predicting membrane performance. Notably, M_Da was more important than M_wt % for predicting membrane performance. The feature analysis of ML models in terms of membrane properties (i.e., mean pore size, overall porosity, and contact angle) provided an unequivocal explanation of the effects of fabrication conditions on membrane performance. Our approach can provide practical aid in guiding the design of fit-for-purpose separation membranes through data-driven virtual experiments.