SOURCE-LINKED INTELLIGENCE

Pioneering Membrane Solutions for a Sustainable Future

CORDIS · observation · Publication date unknown

odegradable membranes using renewable resources such as cellulose, chitosan, and natural fibres, replacing fossil-based polymers and hazardous solvents. The project will combine material science with machine learning (ML) to predict and optimise membrane properties, enabling scalable, energy-efficient fabrication while ensuring mechanical stability, biocompatibility, and high performance. Targeted applications include water treatment, antimicrobial filtration, and other areas requiring safe and selective separations. The consortium brings together 11 partners (6 academic, 5 non-academic) from Belgium, Türkiye, Ireland, Italy, Latvia, and Malaysia in an international, inter-sectoral, and interdisciplinary collaboration. Academic and industrial partners will jointly develop novel material combinations, optimise fabrication methods, and validate operational performance through pilot demonstrations. LCA and TEA will guide sustainable design, ensuring circularity and end-of-life strategies. Beyond scientific and technical innovation, Green-Mem is committed to open science, gender equality

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recordType

award

status

SIGNED

region

EU

value

1222440

unit

EUR