Energy landscape-driven non-equilibrium evolution of inherent structure in disordered material

Abstract

Complex states in glasses can be neatly expressed by the potential energy landscape (PEL). However, because PEL is highly multi-dimensional it is difficult to describe how the system moves around in PEL. Here we demonstrate that it is possible to predict the evolution of macroscopic state in a metallic glass, such as ageing and rejuvenation, through a set of simple equations describing excitations in the PEL. The key to this simplification is the realization that the step of activation from the initial state to the saddle point in PEL and the following step of relaxation to the final state are essentially decoupled. The model shows that the interplay between activation and relaxation in PEL is the key driving force that simultaneously explains both the equilibrium of supercooled liquid and the thermal hysteresis observed in experiments. It further predicts anomalous peaks in truncated thermal scanning, validated by independent molecular dynamics simulation.

Structural properties of Ge-S amorphous networks in relationship with rigidity transitions: Anab initiomolecular dynamics study

“…It is also seen that the fraction of homopolar defects is influenced by the energy of the system reached after the quench, as is the Ge-Ge homopolar distance, the sample with the lowest energy having also a slightly longer homopolar distance (2.54 Å vs 2.45 Å) and a reduced Ge-Ge correlation distance for the ES motif (2.89 Åvs 2.95 Å). It would certainly be of interest to relate in more detail characteristics of the energy landscape and the energy of inherent structures with structural properties 73,74 of the obtained glassy materials but such a study is unfortunately beyond the possibilities of DFT based methods given the limitation in size and equilibration time. One is, therefore, left at a rather qualitative albeit insightful level of description.…”

Predicting Shear Transformation Events in Metallic Glasses

“…To this end, several methods have been developed during the past years to search for the first order saddle points of a given system, among them the activation-relaxation technique nouveau (ARTn) [21][22][23] is the most widely used one in exploring the energy landscape of metallic glasses [24][25][26][27][28] as prior knowledge of the final state is not required. In this letter, ARTn will be employed to harvest the ST events in a Cu 64 Zr 36 MG model, which contains 10000 atoms in total and was generated with a cooling rate of 10 9 K/s.…”

“…Exploring the PEL is known to be an indispensable way to understand the complex phenomenology in metallic glasses [31][32][33]. The thermal activation events in the PEL has been discussed and used to understand the structure and energy evolution based on thermal histories [28].…”

Smart machine learning or discovering meaningful physical and chemical contributions through dimensional stacking

“…In general, glasslike behavior is associated with complex nonequilibrium states of matter with strong disorder. 52 However, the disorder is often associated with lack of structural organization. In comparison, here glassy behavior is observed in bulk single crystals, where the disorder is observed for the functional (i.e., physical) response of the material, as a direct result of local chemical and polar heterogeneities.…”