Neighbor network in a polydisperse hard-disk fluid: degree distribution and assortativity

The network structure of the corneal endothelium

A generic network model is applied to study the structure of the mammalian corneal endothelium. The model has been shown to reproduce the network properties of a wide range of systems, from low-dimensional inorganic glasses to colloidal nanoparticles deposited on a surface. Available extensive experimental microscopy results are analyzed and combined to highlight the behavior of two key metrics, the fraction of hexagonal rings (p₆) and the coefficient of variation of the area. Their behavior is analyzed as a function of patient age, the onset of diabetes, and contact lens wearing status. Wearing contact lenses for ∼10 years is shown to change the endothelium structure by the equivalent of ∼30 years contact lens-free. Model network configurations are obtained using a Monte Carlo bond-switching algorithm, with the resulting topologies controlled by two potential model parameters (the bond and angular force constants) and the Monte Carlo temperature. The effect of systematically varying these parameters is investigated. In addition, the effect of constraining the ring size distribution is investigated. The networks generated with relatively weak bond force constants are shown to correlate best with the experimental information. The importance of extracting the full ring size distribution (rather than simply the fraction of hexagons) is discussed.

Generalized network theory of physical two-dimensional systems

The properties of a wide range of two-dimensional network materials are investigated by developing a generalized network theory. The methods developed are shown to be applicable to a wide range of systems generated from both computation and experiment; incorporating atomistic materials, foams, fullerenes, colloidal monolayers, and geopolitical regions. The ring structure in physical networks is described in terms of the node degree distribution and the assortativity. These quantities are linked to previous empirical measures such as Lemaître's law and the Aboav-Weaire law. The effect on these network properties is explored by systematically changing the coordination environments, topologies, and underlying potential model of the physical system.

Simplified computational model for generating biological networks

A method to generate and simulate biological networks is discussed. An expanded Wooten–Winer–Weaire bond switching methods is proposed which allows for a distribution of node degrees in the network while conserving the mean average node degree. The networks are characterised in terms of their polygon structure and assortativities (a measure of local ordering). A wide range of experimental images are analysed and the underlying networks quantified in an analogous manner. Limitations in obtaining the network structure are discussed. A “network landscape” of the experimentally observed and simulated networks is constructed from the underlying metrics. The enhanced bond switching algorithm is able to generate networks spanning the full range of experimental observations.

We discuss a Monte Carlo method to simulate biological networks and compare to the underlying networks in experimental images.

Equation of state of polydisperse hard-disk mixtures in the high-density regime

A proposal to link the equation of state of a monocomponent hard-disk fluid to the equation of state of a polydisperse hard-disk mixture is presented. Event-driven molecular dynamics simulations are performed to obtain data for the compressibility factor of the monocomponent fluid and of 26 polydisperse mixtures with different size distributions. Those data are used to assess the proposal and to infer the values of the compressibility factor of the monocomponent hard-disk fluid in the metastable region from those of mixtures in the high-density region. The collapse of the curves for the different mixtures is excellent in the stable region. In the metastable regime, except for two mixtures in which crystallization is present, the outcome of the approach exhibits a rather good performance. The simulation results indicate that a (reduced) variance of the size distribution larger than about 0.01 is sufficient to avoid crystallization and explore the metastable fluid branch.