Chemical recycling is a crucial step towards a circular economy for plastics while keeping carbon emissions low. Today’s modern sorting facilities typically produce a dozen of different streams from the collected waste. It is expected that this will be the status quo for the coming decade, with polyolefin rich streams being by far the most important. In MADCAP the objective is to recycle these polyolefin waste streams by converting them to chemicals or liquid energy carriers instead of combusting them, as is done today. In particular, novel catalysts will be screened with a multiscale modeling framework to maximize the yield of valuable olefins. Modeling will be used to gain insights in the catalytic pyrolysis of plastic waste from molecular detail to reactor-scale interactions. By understanding how and why molecules react, it is possible to optimize product yields, and to create and design new catalysts for the selective production of the desired key chemicals. This project aims to advance state-of-the-art techniques from various chemical engineering disciplines. The model guided catalyst design for plastic waste chemical recycling is driven by in-depth microkinetic modeling, by advanced experimentation using the unique equipment at the Laboratory for Chemical Technology, and by incorporating artificial intelligence for inverse catalyst design and fast and accurate property prediction