Structurally determined directionality identifies the boundary between mobile and immobile domains in a disordered material.

The structure and available degrees of freedom of an amorphous configuration can determine the location of dynamic heterogeneities. In the same way, these features can also determine the directionality of the particle motion. In this paper we propose that directionality can be attributed to those particles that only participate in a single unconstrained motion.

The influence of overconstraint on the spatial distribution of mobility in an amorphous network.

It is proposed that the dynamic heterogeneities of an amorphous material are strongly correlated with the spatial distribution of unconstrained degrees of freedom in the associated network of mechanical constraints. This latter distribution is shown to depend sensitively on whether or not overconstraints are permitted in the constraint network. When overconstraints are avoided, relaxation is achieved with few bond rearrangements and the susceptibility χ(4) increases monotonically with increasing constraint density, in contrast to the case of a random network.

Length scales of dynamic heterogeneities in a network of fluctuating mechanical constraints.

We describe a random bond network with fluctuating mechanical constraints for which structural and dynamical length scales are explicitly defined and can be compared with the observable properties of the system. The constraints give well-defined individual structures, describing rigid clusters of particles, and there are distinct structural changes between different configurations. In addition, unambiguous unconstrained motions, including extended collective motions, can be defined within each configuration of constraints.

Unconstrained motions, dynamic heterogeneities, and relaxation in disordered solids.

A disordered network of bonds with a fixed configuration can relax via a variety of unconstrained motions. These motions can be directly inferred from the topological arrangement of constraints without any geometrical information. We use the pebble game algorithm of Jacobs and Thorpe [D.

Connectivity in the potential energy landscape for binary Lennard-Jones systems.

Connectivity in the potential energy landscape of a binary Lennard-Jones system can be characterized at the level of cage-breaking. We calculate the number of cage-breaking routes from a given local minimum and determine the branching probabilities at different temperatures, along with correlation factors that represent the repeated reversals of cage-breaking events. The number of reversals increases at lower temperatures and for more fragile systems, while the number of accessible connections decreases.

Rigidity percolation and the spatial heterogeneity of soft modes in disordered materials.

We show how the spatial character of unconstrained motion in a network of bonds can be directly inferred from the topological arrangement of constraints. Relaxation time scales of these soft modes are determined, and from this information we generate spatial maps of the heterogeneous distribution of relaxation times in the disordered network. We show that the nature of the dynamic heterogeneity and its sensitivity to changes in bond configuration depends dramatically on the proximity of the system to the rigidity percolation point.

Energy landscapes for diffusion: analysis of cage-breaking processes.

A wide spectrum of potential energy barriers exists for binary Lennard-Jones systems. Here we examine the barriers and cage-breaking rearrangements that are pertinent to long-term diffusion. Single-step cage-breaking processes, which follow high-barrier routes, are identified, and different methods and criteria for defining a cage-breaking process are considered.

Equilibrium density of states and thermodynamic properties of a model glass former.

This paper presents an analysis of the thermodynamics of a model glass former. We have performed equilibrium sampling of a popular binary Lennard-Jones model, employing parallel tempering Monte Carlo to cover the crystalline, amorphous, and liquid regions of configuration space. Disconnectivity graphs are used to visualize the potential energy landscape in the vicinity of a crystalline geometry and in an amorphous region of configuration space.

Super-Arrhenius diffusion in an undercooled binary Lennard-Jones liquid results from a quantifiable correlation effect.

On short time scales an underlying Arrhenius temperature dependence of the diffusion constant can be extracted from the fragile, super-Arrhenius diffusion of a binary Lennard-Jones mixture. This Arrhenius diffusion is related to the true super-Arrhenius behavior by a factor that depends on the average angle between steps in successive time windows. The correction factor accounts for the fact that on average, successive displacements are negatively correlated, and this effect can therefore be linked directly with the higher apparent activation energy for diffusion at low temperature.

Diagnosing broken ergodicity using an energy fluctuation metric.

The Mountain and Thirumalai energy fluctuation metric, Omega(t), has been used to study the effective ergodicity of 60- and 256-atom binary Lennard-Jones mixtures in order to determine the reliability of the calculated diffusion constants at different energies. A plot of Omega(t) against 1time allows the identification of two distinct regimes: ergodic supercooled liquids, where Omega(t) approaches zero, and nonergodic glassy states, where Omega(t) asymptotically approaches a nonzero value on the molecular dynamics time scale. This approach seems to be more appropriate than attempting to define a threshold value for Omega(t)/Omega(0).

Chemical documents: machine understanding and automated information extraction.

Automatically extracting chemical information from documents is a challenging task, but an essential one for dealing with the vast quantity of data that is available. The task is least difficult for structured documents, such as chemistry department web pages or the output of computational chemistry programs, but requires increasingly sophisticated approaches for less structured documents, such as chemical papers. The identification of key units of information, such as chemical names, makes the extraction of useful information from unstructured documents possible.