Toward rational design of ionic liquid/metal-organic framework composites for efficient gas separations: Combining molecular modeling, machine learning, and experiments to move beyond trial-and-error

Abstract

This review presents a comprehensive overview of the emerging field of ionic liquid/metal-organic framework (IL/MOF) composites, which synergistically combine the unique properties of two material families, ILs and MOFs, for adsorption- and membrane-based gas separation applications. ILs, with their low volatility and tunable chemical properties, enhance the functionality of MOFs, which are highly porous materials characterized by their large surface areas and adjustable pore sizes. The effective integration of these two materials through various synthesis techniques has led to the development of novel IL/MOF composites exhibiting superior gas adsorption and separation capabilities, particularly for CO2 capture, compared to pristine MOFs. The use of these composites as fillers in polymers resulted in mixed matrix membranes with enhanced selectivities. This field is advancing rapidly, yet the design of IL/MOF composites still relies on a trial-and-error approach. After providing an overview of the current state-of-the-art in gas separation applications of IL/MOF composites, we specifically focused on the pivotal role of computational studies in both complementing and, beyond that, guiding the experimental design of novel IL/MOF composites. The importance of harnessing experiments, computational modeling, and machine learning methods to accelerate the discovery of new IL/MOF composites as adsorbents and membranes was discussed with recent examples. Finally, we addressed the current challenges and future opportunities in this rapidly evolving field, emphasizing the significant potential of IL/MOF composites to revolutionize the current gas adsorption and separation technologies.