Published February 1, 2018 | Version v1
Journal article

Local random configuration-tree theory for string repetition and facilitated dynamics of glass

Creators

  • 1. Department of Applied Physics, Hong Kong Polytechnic University, Hong Kong (China)

Description

We derive a microscopic theory of glassy dynamics based on the transport of voids by micro-string motions, each of which involves particles arranged in a line hopping simultaneously displacing one another. Disorder is modeled by a random energy landscape quenched in the configuration space of distinguishable particles, but transient in the physical space as expected for glassy fluids. We study the evolution of local regions with m coupled voids. At a low temperature, energetically accessible local particle configurations can be organized into a random tree with nodes and edges denoting configurations and micro-string propagations respectively. Such trees defined in the configuration space naturally describe systems defined in two- or three-dimensional physical space. A micro-string propagation initiated by a void can facilitate similar motions by other voids via perturbing the random energy landscape, realizing path interactions between voids or equivalently string interactions. We obtain explicit expressions of the particle diffusion coefficient and a particle return probability. Under our approximation, as temperature decreases, random trees of energetically accessible configurations exhibit a sequence of percolation transitions in the configuration space, with local regions containing fewer coupled voids entering the non-percolating immobile phase first. Dynamics is dominated by coupled voids of an optimal group size, which increases as temperature decreases. Comparison with a distinguishable-particle lattice model (DPLM) of glass shows very good quantitative agreements using only two adjustable parameters related to typical energy fluctuations and the interaction range of the micro-strings. (paper: disordered systems, classical and quantum)

Availability note (English)

Available from http://dx.doi.org/10.1088/1742-5468/aaac56

Additional details

Identifiers

Publishing Information

Journal Title
Journal of Statistical Mechanics
Journal Volume
2018
Journal Issue
2
Journal Page Range
[24 p.]
ISSN
1742-5468

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52047616
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
APPROXIMATIONS; FLUIDS; INTERACTION RANGE; PARTICLES; PROBABILITY; RANDOMNESS; VOIDS
Descriptors DEC
CALCULATION METHODS; DISTANCE