Rapid, Accurate and Reproducible Prediction of the Glass Transition Temperature Using Ensemble-Based Molecular Dynamics Simulation.

For the computational design of new polymeric materials, accurate methods for determining the glass transition temperature () are required. We apply an ensemble approach in molecular dynamics (MD) and examine its predictions of and their associated uncertainty. We separate the uncertainty into the aleatoric contributions arising from dynamical chaos and that due to the computational scenarios chosen to compute . We propose a new scenario for computing , where the density-temperature behavior is computed by running all temperatures concurrently, rather than invoking a sequential approach, thereby significantly reducing wall-clock time from days to several hours without increasing the aleatoric uncertainty. On comparing concurrent and sequential scenarios on six highly cross-linked epoxy resins cured with aromatic amines, we find excellent agreement with our experimentally determined using dynamical mechanical analysis for both scenarios. The confidence intervals are found to scale as , where is the number of members in the ensemble, implying that ensembles comprised of at least ten replicas are required to predict using MD with 95% confidence intervals of less than 20 K. The optimal MD simulation protocol is 4 ns of burn-in time followed by 2 ns of production run time.