Accelerated Scheme to Predict Ring-Opening Polymerization Enthalpy: Simulation-Experimental Data Fusion and Multitask Machine Learning

A Toland and H Tran and LH Chen and YH Li and C Zhang and W Gutekunst and R Ramprasad, JOURNAL OF PHYSICAL CHEMISTRY A, 127, 10709-10716 (2023).

DOI: 10.1021/acs.jpca.3c05870

Ring-opening enthalpy (Delta H-ROP) is a fundamental thermodynamic quantity controlling the polymerization and depolymerization of an important class of recyclable polymers, namely, those created from ring- opening polymerization (ROP). Highly accurate first-principles-based computational methods to compute Delta H-ROP are computationally too demanding to efficiently guide the design of depolymerizable polymers. In this work, we develop a generalizable machine-learning model that was trained on experimental measurements and reliably computed simulation results of Delta H-ROP (the latter provides a pathway to systematically increase the chemical diversity of the data). Predictions of Delta H-ROP using this machine-learning model require essentially no time while the prediction accuracy is about similar to 8 kJ/mol, approaching the well- known chemical accuracy. We hope that this effort will contribute to the future development of new depolymerizable polymers.

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