A Mechanism-Based Reaction-Diffusion Model for Accelerated Discovery of Thermoset Resins Frontally Polymerized by Olefin Metathesis

15 May 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Frontal ring-opening metathesis polymerization (FROMP) involves a self-perpetuating exothermic reaction, which enables the rapid and energy-efficient manufacturing of thermoset polymers and composites. Current state-of-the-art reaction-diffusion FROMP models rely on a phenomenological description of the olefin metathesis kinetics, limiting their ability to model the governing thermo-chemical FROMP processes. Furthermore, the existing models are unable to predict the variations in FROMP kinetics with changes in the resin composition and as a result are of limited utility towards accelerated discovery of new resin formulations. In this manuscript, we formulate a chemically meaningful model grounded in the established mechanism of ring-opening metathesis polymerization (ROMP). Our study aims to validate the hypothesis that the ROMP mechanism, applicable to monomer-initiator solutions below 100°C, remains valid under the non-ideal conditions encountered in FROMP, including ambient to >200°C temperatures, sharp temperature gradients, and neat monomer environments. Through extensive simulations, we demonstrate that our mechanism-based model accurately predicts FROMP behavior across various resin compositions, including polymerization front velocities and thermal characteristics (e.g., Tmax). Additionally, we introduce a semi-inverse workflow that predicts FROMP behavior from a single experimental data point. Notably, the physiochemical parameters utilized in our model can be obtained through DFT calculations and minimal experiments, highlighting the model's potential for rapid screening of new FROMP chemistries in pursuit of thermoset polymers with superior thermo-chemo-mechanical properties.

Keywords

Frontal Ring-Opening Metathesis Polymerization
Polymerization Kinetics
Accelerated Discovery

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