Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan 48109, USA.
Division of Natural Sciences, Oita University, Oita-shi 870-1192, Japan.
Nat Commun. 2017 May 19;8:15417. doi: 10.1038/ncomms15417.
Complex states in glasses can be neatly expressed by the potential energy landscape (PEL). However, because PEL is highly multi-dimensional it is difficult to describe how the system moves around in PEL. Here we demonstrate that it is possible to predict the evolution of macroscopic state in a metallic glass, such as ageing and rejuvenation, through a set of simple equations describing excitations in the PEL. The key to this simplification is the realization that the step of activation from the initial state to the saddle point in PEL and the following step of relaxation to the final state are essentially decoupled. The model shows that the interplay between activation and relaxation in PEL is the key driving force that simultaneously explains both the equilibrium of supercooled liquid and the thermal hysteresis observed in experiments. It further predicts anomalous peaks in truncated thermal scanning, validated by independent molecular dynamics simulation.
玻璃中的复杂态可以通过势能景观（PEL）进行简洁地表达。然而，由于 PEL 具有高度多维性，因此很难描述系统在 PEL 中如何移动。在这里，我们通过一组简单的方程展示了通过描述 PEL 中的激发来预测金属玻璃中宏观状态的演化，例如老化和恢复。这种简化的关键在于认识到从初始状态到 PEL 鞍点的激活步骤以及随后松弛到最终状态的步骤基本上是解耦的。该模型表明，PEL 中的激活和松弛之间的相互作用是同时解释过冷液体平衡和实验中观察到的热滞后的关键驱动力。它进一步预测了截断热扫描中的异常峰，这通过独立的分子动力学模拟得到了验证。
