Systematic Material Optimization for Membrane Distillation Resource Recovery through Materials Informatics, Life...

Material selection for membrane distillation (MD) remains dominated by empirical trial-and-error. This study presents the first application of Ansys Granta materials informatics to thermally driven membrane separation, integrating database-driven screening, direct contact MD (DCMD) experimental validation, and life cycle assessment (LCA) to identify optimal membrane materials across diverse circular water economy contexts. Twenty-two candidates spanning polymers, biopolymers, and ceramics were evaluated against thermal and mechanical performance, vapor transport efficiency, and chemical compatibility across five aggressive feed environments. LCA at a representative 10,000 m³·day^-1 facility scale reveals a counterintuitive lifecycle inversion: PEEK and PES, the two highest production-phase energy materials among all 22 candidates achieving net-positive lifecycle sustainability through robust end-of-life recycling, demonstrate that the production carbon footprint is a misleading proxy for environmental performance, a finding with implications beyond membrane engineering. Three commercial membranespolypropylene (PP), polyvinylidene fluoride (PVDF), and polytetrafluoroethylene (PTFE)validated the informatics predictions through DCMD desalination testing, achieving fluxes of 14 ± 2, 11 ± 3, and 29 ± 4 kg·m^-2·h^-1 with >99% salt rejection. Predicted flux agreed closely (R² ≈ 1); styrene-butadiene-styrene (SBS) exhibited the highest theoretical flux (413 kg·m^-2·h^-1), a theoretical upper bound reflecting intrinsic vapor transmission rather than practical MD performance. Cross-property analysis identified maximum service temperature and tensile strength as the strongest correlated pair (r = 0.67). The multicriteria performance index (Π) reveals fundamentally context-dependent rankings: titania leads under balanced weighting (Π = 0.67), SBS under flux priority (Π = 0.77), and PVC under sustainability priority (Π = 0.77). No universally optimal material exists; this replicable framework replaces single-criterion optimization with transparent, application-specific material guidance for circular water economy MD deployment.