Optimizing toward Discovery: AI-Driven Exploration of Lewis Acid–Base Catalysts for PET Glycolysis
University of Science and Technology of China · Hefei National Center for Physical Sciences at Nanoscale · +2 more institutions
Abstract
The depolymerization of polyethylene terephthalate (PET) through efficient chemical recycling remains a central challenge in plastic waste valorization, in part because the catalyst landscape is vast and sparsely explored. Here, we present an artificial intelligence (AI)-driven discovery framework that integrates Bayesian optimization (BO), large language models (LLMs), and high-throughput robotics to accelerate the search for Lewis acid–base catalysts for PET glycolysis. Starting from a literature-guided baseline, BO used LLM-derived semantic embeddings of chemical knowledge to navigate a high-dimensional space of 11,160 candidate pairs, identifying promising candidates beyond the initial state of the art.…
Citation impact
- FWCI
- 34.78
- Percentile
- 100%
- References
- 44
Authors
10- YYYe Yu
University of Science and Technology of China, Hefei National Center for Physical Sciences at Nanoscale
- ZXZikai Xie
University of Science and Technology of China, Hefei National Center for Physical Sciences at Nanoscale
- MLMan Luo
University of Science and Technology of China, Hefei National Center for Physical Sciences at Nanoscale
- ARAdam Redfearn
University of Birmingham
- ABArianna Brandolese
University of Birmingham
Topics & keywords
- Polyethylene terephthalate
- Workflow
- Catalysis
- Depolymerization
- Chemical space
- Bayesian optimization
- Yield (engineering)