Completed Materials & Manufacturing Chemistry

University of Nottingham and B & M Longworth (Edgworth) Ltd - AKT3 2024

In plain English

AI plain-English summary

Most of the world’s clothing waste—complex blends of synthetic and natural fibres—currently ends up in landfill or incinerators, because no cost-effective method exists to break them back down into their original chemical building blocks. This project tests a new technology called pressolysis that uses pressure and chemical reactions to dismantle those mixed-fabric garments into valuable raw materials. If it works, the process could turn mountains of discarded jumpers, jeans, and jackets into feedstocks for new textiles, plastics, or bio-based products, rather than letting them rot or burn. The immediate impact would be on the recycling and manufacturing supply chains: garment recyclers could handle the most problematic waste streams, and textile mills could buy recycled inputs instead of virgin oil-derived polymers. This is an applied engineering demonstration, not fundamental science—the team is proving that a specific reactor setup can handle real-world mixed waste at a useful scale. Success would mean a concrete tool for closing the loop on fast fashion’s leftovers.

View original technical description
To demonstrate the capacity of novel pressolysis based technologies to be utilised for the of recycling of the world's most abundant and complex waste garments, into valuable synthetic and bio-based feedstocks, for return to a circular economy.

View the original record at the funder ↗

Related Research

Grants with similar aims, by meaning.

University of Leeds (The) and MYGroup Hull Limited (AKT3) 2024
De Montfort University and Generation Phoenix Limited (AKT3) 2024
University of Lincoln and Rockford Trading Company Limited AKT 3
Loughborough University and Generation Phoenix Limited AKT3
SuperPolyWash - Supercritical CO2 washing and decontamination of post-consumer plastic film waste

Original classification

Knowledge Transfer Partnership

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.