AIM-HIGH develops a scalable manufacturing and testing workflow to transform variable polypropylene (PP) waste into recycled materials with consistent, controllable properties. Although PP represents 16% of global plastics production, only around 3% is recycled, largely due to property degradation during reprocessing, which makes performance unpredictable in demanding applications.
The project combines additive manufacturing with advanced “Material Testing 2.0” methods to generate extensive property data from a small number of intelligently designed test specimens. This high-density dataset will be analysed using artificial intelligence to predict the optimal blend of recycled PP, virgin polymer, additives, and processing parameters required to achieve target performance.
The approach will be validated using high-demand impact protection applications, demonstrating reliability even with unknown waste streams. By integrating AI-driven materials discovery with practical manufacturing validation, AIM-HIGH aims to upcycle an underutilised waste stream, reduce landfill disposal, and support green polymer production in line with circular economy and sustainability goals.
