Percolation transition of short-ranged square well fluids in bulk and confinement

Using grand canonical Monte Carlo simulations, we investigate the percolation behavior of a square-well fluid with an ultra-short range of attraction in three dimension (3D) and in confined geometry. The latter is defined through two parallel and structureless walls (slit-pore). We focus on temperat...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Journal of chemical physics 2013-02, Vol.138 (6), p.064904-064904
Hauptverfasser: Neitsch, Helge, Klapp, Sabine H L
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Using grand canonical Monte Carlo simulations, we investigate the percolation behavior of a square-well fluid with an ultra-short range of attraction in three dimension (3D) and in confined geometry. The latter is defined through two parallel and structureless walls (slit-pore). We focus on temperatures above the critical temperature of the (metastable) condensation transition of the 3D system. Investigating a broad range of systems sizes, we first determine the percolation thresholds, i.e., the critical packing fraction for percolation η(c). For the slit-pore systems, η(c) is found to vary with the wall separation L(z) in a continuous but non-monotonic way, η(c)(L(z)→∞)=η(c)(3D). We also report results for critical exponents of the percolation transition, specifically, the exponent ν of the correlation length ξ and the two fisher exponents τ and σ of the cluster-size distribution. These exponents are obtained from a finite-size analysis involving the cluster-size distribution and the radii of gyration distribution at the percolation threshold. Within the accuracy of our simulations, the values of the critical exponents of our 3D system are comparable to those of 3D random percolation theory. For narrow slit-pores, the estimated exponents are found to be close to those obtained from the random percolation theory in two dimensions.
ISSN:0021-9606
1089-7690
DOI:10.1063/1.4790406