Glass transition in metallic glasses: A microscopic model of topological fluctuations in the bonding network

Understanding of the structure and dynamics of liquids and glasses at an atomistic level lags well behind that of crystalline materials, even though they are important in many fields. Metallic liquids and glasses provide an opportunity to make significant advances because of its relative simplicity. We propose a microscopic model based on the concept of topological fluctuations in the bonding network. The predicted glass transition temperature, $T_g$, shows excellent agreement with experimental observations in metallic glasses. To our knowledge this is the first model to predict the glass transition temperature quantitatively from measurable macroscopic variables.

Figure 1

Glass transition temperature, $T_g$, multiplied by $k∕\left(2BV\right)$, as Eq. (1), plotted as a function of the Poisson’s ratio for various metallic glasses listed in Table . The values of $\nu$ and $B$ used here are evaluated at $T_g$, corrected by the procedure described in the Appendix. The solid line indicates ${\left({\epsilon }_v^T\right)}^2∕K_{\alpha }$, as in Eq. (7), with ${\epsilon }_v^T=0.095$.

Figure 2

The same data as Fig. 1, but expressed as $k{T}_g∕2GV$. The values of $\nu$ and $G$ used here are at $T_g$, corrected by the procedure described in the Appendix. The solid line indicates Eq. (7), with ${\epsilon }_v^T=0.095$.

Figure 3

The same data as Fig. 1, but expressed as $T_g∕E$ (above, in the units of K/GPa) and $k{T}_g∕2EV$ (below). The values of $\nu$ and $E$ used here are at $T_g$, corrected by the procedure described in the Appendix. The solid line in the lower figure indicates Eq. (7), with ${\epsilon }_v^T=0.095$.