| Sumario: | Gas separation plays an essential role in refineries and the chemical industry, with membrane-based technologies gaining prominence for their low cost, compact equipment with a space-saving design footprint, energy efficiency, ease of scale-up, and environmental benefits. Current research focuses on enhancing membrane performance in actual operating conditions by optimizing the equilibrium between selectivity and permeability to expand commercial and industrial applications. This balance between selectivity and permeability can be addressed by using mixed-matrix membranes (MMMs), which are formed by adding nanostructured fillers to the polymer to enhance its separation properties. In this scenario, covalent-organic frameworks (COFs) show considerable potential. COFs have generated significant interest in membrane separation owing to their stable organic structures, compatibility with polymers, and tailorable pore sizes and chemical functionalities. This review provides a systematic overview of COF-based MMMs for gas separation, distinguishing this work from previous reviews that broadly address other inorganic fillers incorporated into MMMs. The manuscript critically examines the physicochemical design principles and effective synthesis routes of COF fillers, their structure-performance relationships within polymer matrix, and, finally, their influence on gas transport behavior under practical operating conditions. Furthermore, a thorough examination of the challenges and opportunities of COF-based MMMs, along with recent advancements in the field, is conducted. The key benefits and drawbacks of using COFs with MOF as a double filler in MMM for gas separation are assessed with respect to permeability, selectivity, interfacial compatibility, and long-term stability. The review also provides recent advances in molecular modeling and machine-learning approaches for rational COF-based MMM design. Lastly, a summary of current research initiatives and potential future research directions is provided to accelerate the development of scalable and industrially viable COF-based MMMs.
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