A Synthetically-accessible Universe of Chemically Recyclable Polymers

Abstract:Polymers synthesized via ring-opening polymerization (ROP) of cyclic monomers represent an important class of materials due to their chemical recyclability and possible insertion in several critical applications. We present a dataset of 1 million synthetically realizable ROP polymer structures generated through a combination of Virtual Forward Synthesis (VFS) and polymer expert language models and qualified by stringent chemical heuristics. VFS is used to generate ROP polymers by applying known reactions to existing monomers. The polymer foundation models polyBART and POLYT5 further enable the generation of ROP candidates, with polyBART exploring its learned latent space and POLYT5 producing candidates via sequence-to-sequence generation. The resulting ROP polymers are subjected to robust filtering criteria to ensure novelty, validity and overall data quality through a combination of automated validation pipelines and a comprehensive set of chemist-informed heuristic rules introduced in this work for the first time. We hope that this dataset will serve as a valuable resource for downstream sustainable applications.

Soft Condensed Matter (cond-mat.soft); Artificial Intelligence (cs.AI)

arXiv:2608.00149 [cond-mat.soft]

(or arXiv:2608.00149v1 [cond-mat.soft] for this version)

https://doi.org/10.48550/arXiv.2608.00149 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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