通过机器学习统一坚固和脆弱液体的框架：液体二氧化硅的研究
Unifying framework for strong and fragile liquids via machine learning: a study of liquid silica
摘要：
玻璃形成液体的脆性表征了其弛豫动力学随冷却而减慢的速度。强液体的粘度遵循阿留申定律，具有与温度无关的势垒高度，以重排负责松弛，而脆弱的液体经历了更快的增加，其动力学，这表明势垒高度随温度降低而增加。坚固的玻璃形成体通常是网状玻璃，而易碎的玻璃形成体通常是分子或硬球状的。由于这些差异在微观水平上，强大和脆弱的玻璃形成通常被分开处理，从理论的角度来看。二氧化硅在低温下是典型的强玻璃形成剂，但在高温下也表现出神秘的强到脆的转变。在这里，我们表明，柔软度，一个基于结构的机器学习参数，以前已被应用到脆弱的玻璃成型提供了一个有用的描述模型液体二氧化硅在强大和脆弱的制度，并通过强大的脆弱的交叉。就像易碎的玻璃成型品一样，柔软度和动态之间的关系在所有制度下都是不变的，但平均柔软度随温度而变化。二氧化硅中的强到弱的交叉不是由于结构的突然、质的变化，而是可以用具有连续和线性变化的局部结构的简单的阿耳忒修斯形式来解释。我们的研究结果统一在一个简单的概念图片下的液体二氧化硅的研究。
英文摘要：
The fragility of a glassforming liquid characterizes how rapidly its relaxation dynamics slow down with cooling. The viscosity of strong liquids follows an Arrhenius law with a temperature-independent barrier height to rearrangements responsible for relaxation, whereas fragile liquids experience a much faster increase in their dynamics, suggesting a barrier height that increases with decreasing temperature. Strong glassformers are typically network glasses, while fragile glassformers are typically molecular or hard-sphere-like. As a result of these differences at the microscopic level, strong and fragile glassformers are usually treated separately from a theoretical point of view. Silica is the archetypal strong glassformer at low temperatures, but also exhibits a mysterious strong-to-fragile crossover at higher temperatures. Here we show that softness, a structure-based machine learned parameter that has previously been applied to fragile glassformers provides a useful description of model liquid silica in the strong and fragile regimes, and through the strong-to-fragile crossover. Just as for fragile glassformers, the relationship between softness and dynamics is invariant and Arrhenius in all regimes, but the average softness changes with temperature. The strong-to-fragile crossover in silica is not due to a sudden, qualitative change in structure, but can be explained by a simple Arrhenius form with a continuously and linearly changing local structure. Our results unify the study of liquid silica under a single simple conceptual picture.
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