Correlation between Fragility and the Arrhenius Crossover Phenomenon in Metallic, Molecular, and Network Liquids

Abstract

We report the observation of a distinct correlation between the kinetic fragility index $m$ and the reduced Arrhenius crossover temperature ${\theta }_A=T_A/T_g$ in various glass-forming liquids, identifying three distinguishable groups. In particular, for 11 glass-forming metallic liquids, we universally observe a crossover in the mean diffusion coefficient from high-temperature Arrhenius to low-temperature super-Arrhenius behavior at approximately ${\theta }_A\approx 2$ which is in the stable liquid phases. In contrast, for fragile molecular liquids, this crossover occurs at much lower ${\theta }_A\approx 1.4$ and usually in their supercooled states. The ${\theta }_A$ values for strong network liquids spans a wide range higher than 2. Intriguingly, the high-temperature activation barrier $E_{\infty }$ is universally found to be $\sim 11k_B{T}_g$ and uncorrelated with the fragility or the reduced crossover temperature ${\theta }_A$ for metallic and molecular liquids. These observations provide a way to estimate the low-temperature glassy characteristics ($T_g$ and $m$) from the high-temperature liquid quantities ($E_{\infty }$ and ${\theta }_A$).

6 pages, 4 figures

References in corpus (4)

• Theoretical perspective on the glass transition and amorphous materials
• Interatomic repulsion softness directly controls the fragility of supercooled metallic melts
• High Frequency dynamics in metallic glasses
• Broadband dielectric spectroscopy on benzophenone: alpha relaxation, beta relaxation, and mode coupling theory

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