Predicting polymerization reactions via transfer learning using chemical language models
Ronaldo Giro,
Brenda Ferrari,
Matteo Manica
et al.
Abstract:Polymers are candidate materials for a wide range of sustainability applications such as carbon capture and energy storage. However, computational polymer discovery lacks automated analysis of reaction pathways and stability assessment through retro-synthesis. Here, we report the first extension of transformer-based language models to polymerization reactions for both forward and retrosynthesis tasks. To that end, we have curated a polymerization dataset for vinyl polymers covering reactions and retrosynthesi… Show more
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