Adam Redfearn
Papers
1
Total Citations
5
H-Index
1
About
Adam Redfearn is a rising leader at the intersection of artificial intelligence and sustainable chemistry, with a primary focus on accelerating the discovery of catalysts for plastic waste valorization. His most notable contribution is the development of an AI-driven framework that systematically explores the vast, sparsely mapped landscape of Lewis acid–base catalysts for polyethylene terephthalate (PET) glycolysis—a critical step toward efficient chemical recycling. This pioneering work, published in 2026 and already garnering 5 citations, demonstrates how machine learning can optimize experimental design to identify high-performance catalysts far more rapidly than traditional trial-and-error approaches. By bridging computational prediction with experimental validation, Redfearn’s research directly addresses one of the central challenges in circular polymer economies: the need to depolymerize PET into valuable monomers at scale. His approach not only reduces the time and cost of catalyst screening but also offers a transferable blueprint for tackling other complex chemical transformations. As an early-career researcher, Redfearn’s work signals a paradigm shift toward data-driven discovery in sustainable materials science, positioning him as a key innovator in the fight against plastic pollution.
Research Focus
Key Achievements
Top Papers
- 1