Machine-guided template-based polymer retrosynthesis planning

Polymer informatics is being utilized to accelerate the design and discovery of polymers. However, the practical realization of designed polymer is still slow due to synthesis challenges, e.g., difficulties with the identification of potential polymerization mechanisms and optimal reactants/solvents/processing conditions. In the past, synthesis pathways adopted for a target polymer have been heavily dependent on chemical intuition and past experience. To expedite this process, we have developed a template-based approach to assist in polymer retrosynthesis planning. In this work, several thousands of polymer polymerization paths were manually accumulated from various resources to extract hundreds of synthetic templates and used as a knowledge base. Further, a similarity metric was adopted to select the synthetic templates for the target polymer. Finally, prediction accuracy was measured by comparison with known and expert-crafted polymerization paths. We believe that the proposed template-based approach can efficiently make synthesis recommendation for experimenters, accelerating polymer discovery.