Outcome
Higher-value circular feedstocks and products derived from existing waste and side streams.

What we do
We explore and design mechanical, chemical and biological routes to convert waste into new materials and products. This includes process selection, laboratory trials, quality control strategies and preliminary scale-up concepts for textiles, polymers, organics and composites.

AI capabilities
AI supports decision-making and quality management:

• Predictive models that estimate yield and quality based on feedstock composition and process conditions
• Data-driven optimisation of process parameters to balance performance, cost and environmental impact
• Classification models for incoming materials and products to support “design for circularity” and traceability
• Statistical and machine-learning tools to analyse experimental data and prioritise the most promising pathways

Our focus is on building models that are clearly linked to experimental evidence and that can be explained to both technical and non-technical stakeholders.

Good for
Textile and polymer recyclers, manufacturers exploring secondary feedstocks, and organisations developing new circular materials.