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 (T_g) are required. We apply an ensemble approach in molecular dynamics (MD) and examine its predictions of T_g 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 T_g. We propose a new scenario for computing T_g, 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 T_g using dynamical mechanical analysis for both scenarios. The confidence intervals are found to scale as N^–0.5, where N is the number of members in the ensemble, implying that ensembles comprised of at least ten replicas are required to predict T_g 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.