Abstract
Thermoset polymers are an area of intense research due to their low cost,
ease of processing, environmental resistance, and unique physical properties. The favorable
properties of this class of polymers have many applications in aerospace, automotive, marine,
and sports equipment industries. Molecular simulations of thermosets are frequently used to
model formation of the polymer network, and to predict the thermomechanical properties. These
simulations usually require custom algorithms that are not easily accessible to non-experts and
not suited for high throughput screening. To address these issues, we have developed a robust
cross-linking algorithm that can incorporate different types of chemistries and leverage
GPU-enabled molecular dynamics simulations. Automated simulation analysis tools for
cross-linking simulations are also presented. Using four well known epoxy/amine formulations
as a foundational case study and benzoxazine as an example of how additional chemistries can
be modeled, we demonstrate the power of the algorithm to accurately predict curing and
thermophysical properties. These tools are able to streamline the thermoset simulation process,
opening up avenues to in-silico high throughput screening for advanced material development.