The new insight into dynamic crossover in glass forming liquids from the apparent enthalpy analysis

One of the most intriguing phenomena in glass forming systems is the dynamic crossover (T(B)), occurring well above the glass temperature (T(g)). So far, it was estimated mainly from the linearized derivative analysis of the primary relaxation time τ(T) or viscosity η(T) experimental data, originally proposed by Stickel et al. [J. Chem. Phys. 104, 2043 (1996); J. Chem. Phys. 107, 1086 (1997)]. However, this formal procedure is based on the general validity of the Vogel-Fulcher-Tammann equation, which has been strongly questioned recently [T. Hecksher et al. Nature Phys. 4, 737 (2008); P. Lunkenheimer et al. Phys. Rev. E 81, 051504 (2010); J. C. Martinez-Garcia et al. J. Chem. Phys. 134, 024512 (2011)]. We present a qualitatively new way to identify the dynamic crossover based on the apparent enthalpy space (H(a)(') = dlnτ/d(1/T)) analysis via a new plot lnH(a)(') vs. 1∕T supported by the Savitzky-Golay filtering procedure for getting an insight into the noise-distorted high order derivatives. It is shown that depending on the ratio between the "virtual" fragility in the high temperature dynamic domain (m(high)) and the "real" fragility at T(g) (the low temperature dynamic domain, m = m(low)) glass formers can be splitted into two groups related to f < 1 and f > 1, (f = m(high)∕m(low)). The link of this phenomenon to the ratio between the apparent enthalpy and activation energy as well as the behavior of the configurational entropy is indicated.

An Urn Model for Cascading Failures on a Lattice

A cascading failure is a failure in a system of interconnected parts, in which the breakdown of one element can lead to the subsequent collapse of the others. The aim of this paper is to introduce a simple combinatorial model for the study of cascading failures. In particular, having in mind particle systems and Markov random fields, we take into consideration a network of interacting urns displaced over a lattice. Every urn is Pólya-like and its reinforcement matrix is not only a function of time (time contagion) but also of the behavior of the neighboring urns (spatial contagion), and of a random component, which can represent either simple fate or the impact of exogenous factors. In this way a non-trivial dependence structure among the urns is built, and it is used to study default avalanches over the lattice. Thanks to its flexibility and its interesting probabilistic properties, the given construction may be used to model different phenomena characterized by cascading failures such as power grids and financial networks.