While molecular simulations have contributed to the modern understanding of the glass transition, they are constrained in prediction of experimental glass temperatures T_g because they are limited to times far shorter than those associated with experimental glass formation. Here, we bridge this gap via a model-based forecasting approach. We assess models of the temperature dependence of dynamics in glass forming liquids based upon the rate at which their prediction of T_g and fragility converge upon incorporating increasingly long timescale data. We find that the Cooperative Model of Schmidtke et al. typically provides the best predictions, ultimately enabling good T_g predictions from all-atom simulations of a range of polymers. Together with a protocol for efficient simulation of dynamics in glass-forming liquids, this strategy enables high-throughput computational screening of the glass transition. The success of the Cooperative Model in predicting low temperature behavior adds support to the two-barrier scenario underlying this model.

尽管分子模拟为现代理解玻璃化转变做出了贡献，但它们被限制在实验玻璃温度T _g的预测中，因为它们的时间远远短于与实验玻璃形成相关的时间。在这里，我们通过基于模型的预测方法弥合了这一差距。我们评估玻璃成形液动力学动力学的温度依赖性模型，该模型基于合并了越来越长的时间尺度数据的T _g和脆性预测的收敛速度。我们发现Schmidtke等人的合作模型。通常会提供最佳的预测，最终使T _g达到最佳一系列聚合物的全原子模拟预测。结合有效模拟玻璃成形液动力学的协议，该策略可以对玻璃化转变进行高通量计算筛选。合作模型在预测低温行为方面的成功为该模型所基于的两道屏障方案提供了支持。