Development, performance analysis and application of polymer inclusion membranes: A critical review

Polymer Inclusion Membranes (PIMs) have emerged as sustainable separation platforms that integrate carrier-mediated selectivity within stable polymeric matrices, eliminating drawbacks of conventional solvent extraction such as solvent loss and emulsion formation. This review examines the fundamental principles, recent developments, and performance characteristics of PIMs, emphasizing design, fabrication, and operational optimization. The three essential components, base polymers, plasticizers, and carriers are systematically analysed alongside their synergistic effects on membrane stability, selectivity, and transport efficiency. Emerging materials including ionic liquids and deep eutectic solvents as dual-function plasticizers/carriers receive particular attention. Preparation methods are critically evaluated, including solution casting, phase inversion, and thermal compression techniques. Transport mechanisms encompassing carrier diffusion and fixed-site jumping are thoroughly discussed. Operational parameters including pH, temperature, and hydrodynamic conditions are analysed for their impact on efficiency. A comparative analysis demonstrates broad applicability in metal ion extraction, dye removal, contaminant elimination, and specialized applications in chemical analysis, biocatalysis, fuel cells, and gas separation. Despite significant advances, challenges remain including relatively low flux, carrier leakage, mechanical stability limitations, and lack of standardized metrics. Future directions emphasize covalently bound carriers, electrochemical system integration, machine learning optimization, and sustainable material development for large-scale implementation. • Comprehensive critical review of PIMs with comparative performance analysis • Synergistic effects of polymers, plasticizers, and carriers control selectivity. • Ionic liquids and DESs enhance transport and reduce carrier leakage. • Critical analysis identifies scalability challenges and future directions.