Predicting Glass Transition Temperatures of Epoxies with Coarse Grained Molecular Dynamics

Additional Funding Sources

This material is based upon work supported by The Boeing Company under contract BRT-LO217-0072. This material is based upon work supported by the National Science Foundation under Grant No. 1229709. This work leveraged research computing resources (R2) at Boise State University (DOI:10.5281/zenodo.1195027). This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications. This work used the computing resources supported by Boise State College of Engineering Information Technology services.

Presentation Date

7-2018

Abstract

We perform coarse-grained molecular dynamics simulations of epoxies to study the way their microstructure depends on how they are processed. We then perform additional simulations to calculate the glass transition temperatures of our systems and compare against similar experimental systems. We find that the glass transition temperatures of our un-toughened epoxy systems match up well with experiments. This work enables the structure of experimentally-relevant volumes of epoxies to be predicted, a problem that is intractable for many more detailed representations of epoxies.

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W2

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Predicting Glass Transition Temperatures of Epoxies with Coarse Grained Molecular Dynamics

We perform coarse-grained molecular dynamics simulations of epoxies to study the way their microstructure depends on how they are processed. We then perform additional simulations to calculate the glass transition temperatures of our systems and compare against similar experimental systems. We find that the glass transition temperatures of our un-toughened epoxy systems match up well with experiments. This work enables the structure of experimentally-relevant volumes of epoxies to be predicted, a problem that is intractable for many more detailed representations of epoxies.