Marius Michele Harry Porteboeuf
AI-driven Accelerated Material Discovery for Organocatalysis.
Rel. Carlo Ricciardi, Yves Leterrier, James L. Hedrick. Politecnico di Torino, Corso di laurea magistrale in Nanotechnologies For Icts (Nanotecnologie Per Le Ict), 2024
Abstract
This thesis is about chemical polymer recycling for a better circular economy assisted by AI foundation’s model predictions. The research focuses on the selection and the design of organocatalysts for selective depolymerization of polycondensation polymers with glycolysis. 9% of post-consumer plastics are recycled and most of them are mechanical (less than 1% chemically recycled) [7]. Glycolysis still faces some energy efficiency, environmental and economical issues due to the low price of virgin oil. Those issues are notably related to the quality of the product after depolymerization as mixed polymers, food and metal contamination and additives are contained in post-consumer plastics. The solution lies mostly into organocatalyst’s selectivity and activation capabilities.
This kind of catalysts avoid usage of metal elements that are a source of monomers contamination
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