Understanding the Fragile-to-Strong Transition in Silica from Microscopic Dynamics

In this work, we revisit the fragile-to-strong transition (FTS) in the simulated BKS silica from the perspective of microscopic dynamics in an effort to elucidate the dynamical behaviors of fragile and strong glass-forming liquids. Softness, which is a machine-learned feature from local atomic structures, is used to predict the microscopic activation energetics and long-term dynamics. The FTS is found to originate from a change in the temperature dependence of the microscopic activation energetics. Furthermore, results suggest there are two diffusion channels with different energy barriers in BKS silica. The fast dynamics at high temperatures is dominated by the channel with small energy barriers ($<\sim 1\mathrm{eV}$), which is controlled by the short-range order. The rapid closing of this diffusion channel when lowering temperature leads to the fragile behavior. On the other hand, the slow dynamics at low temperatures is dominated by the channel with large energy barriers controlled by the medium-range order. This slow diffusion channel changes only subtly with temperature, leading to the strong behavior. The distributions of barriers in the two channels show different temperature dependences, causing a crossover at $\sim 3100\mathrm{K}$. This transition temperature in microscopic dynamics is consistent with the inflection point in the configurational entropy, suggesting there is a fundamental correlation between microscopic dynamics and thermodynamics.

Figure 1

Diffusion coefficients of Si atoms predicted by softness compared to those calculated directly from MD simulations. The diffusion coefficient is found approximately proportional to the square of the elementary hopping probability. Details of this relationship are discussed in the Supplemental Material [15]. The dashed line is an Arrhenius fitting of the low-temperature data. An FTS is clearly shown in the predicted diffusion coefficients around 3100 K, as noted by the arrow. The inset shows the diffusion coefficients around the experimental $T_g$ predicted by extrapolating softness distribution to lower temperatures (detailed in Supplemental Material [15], Sec. S5) are in good agreement with experimental data [39].

Figure 2

(a) Softness distributions at different temperatures. (b) Bimodal distributions of activation enthalpy of microscopic dynamics at different temperatures. (c) Average softness (left) and activation enthalpy (right) of microscopic dynamics as functions of temperature, both showing a kink at $\sim 3100\mathrm{K}$ corresponding to the FTS.

Figure 3

(a) A linear relationship between average activation enthalpy and activation entropy of microscopic dynamics. The slope of 5358 K is an onset temperature where diffusion of Si atoms in silica becomes independent of the local atomic structure. (b) A break of slope at 3100 K can be more clearly observed in the entropic contribution of activation energy corresponding to the FTS.