scholarly journals Linear polymers in disordered media: The shortest, the longest, and the mean self-avoiding walk on percolation clusters

2012 ◽  
Vol 85 (1) ◽  
Author(s):  
Hans-Karl Janssen ◽  
Olaf Stenull
Fractals ◽  
1995 ◽  
Vol 03 (03) ◽  
pp. 453-463 ◽  
Author(s):  
J.-P. HOVI ◽  
AMNON AHARONY

The distributions of structural properties, which span between two terminals on percolation clusters, are studied using the “H-cell” renormalization group (RG). The RG iteration for these distributions is directly related to a simple Galton-Watson branching process, and we therefore apply theorems developed in the mathematical literature to obtain exact expressions for the asymptotic distribution functions. Distributions of the minimal path lengths, average edge-to-edge self-avoiding walk lengths, and of the masses of percolation clusters are found, and we derive exact exponential forms for the asymptotic tail behavior of the scaled probability densities at both small and large arguments. We also find new results for the multifractal distribution of wave functions on these clusters.


2000 ◽  
Vol 61 (6) ◽  
pp. 6858-6865 ◽  
Author(s):  
Anke Ordemann ◽  
Markus Porto ◽  
H. Eduardo Roman ◽  
Shlomo Havlin ◽  
Armin Bunde

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Bendegúz Dezső Bak ◽  
Tamás Kalmár-Nagy

Cluster growth models are utilized for a wide range of scientific and engineering applications, including modeling epidemics and the dynamics of liquid propagation in porous media. Invasion percolation is a stochastic branching process in which a network of sites is getting occupied that leads to the formation of clusters (group of interconnected, occupied sites). The occupation of sites is governed by their resistance distribution; the invasion annexes the sites with the least resistance. An iterative cluster growth model is considered for computing the expected size and perimeter of the growing cluster. A necessary ingredient of the model is the description of the mean perimeter as the function of the cluster size. We propose such a relationship for the site square lattice. The proposed model exhibits (by design) the expected phase transition of percolation models, i.e., it diverges at the percolation threshold p c . We describe an application for the porosimetry percolation model. The calculations of the cluster growth model compare well with simulation results.


2002 ◽  
Vol 16 (12) ◽  
pp. 449-457
Author(s):  
ZHI-JIE TAN ◽  
XIAN-WU ZOU ◽  
WEI ZHANG ◽  
SHENG-YOU HUANG ◽  
ZHUN-ZHI JIN

Self-attracting walk (SATW) on non-uniform substrates has been investigated by Monte Carlo simulations. The non-uniform substrates are described by Leath percolation clusters with occupied probability p. p stands for the degree of non-uniformity, and takes on values in the range pc≲p ≤1 where pc is the threshold of percolation. For the case of strong attractive interaction u, p has little influence on the walk which is dominated by attractive interactions. Furthermore, in the case of small scales, the exponent ν of the mean end-to-end distance <R2(t)> versus time t is given by ν≃1/(ds+1), while the exponent k of visited sites versus t is given by k≃ds/(ds+1), where ds are the fractal dimensions of the substrates. For u ≃ 0, the walk reduces to the random walk on percolations with p in pc≲p≤1. Also, ν and k decrease sensitively with the reduction of p. It is found, the blocked sites in the substrates (i.e. defects) have much greater influence on the walk driven by thermal flunctuation than that dominated by the attractive interaction.


1989 ◽  
Vol 177 ◽  
Author(s):  
Gary S. Grest ◽  
Kurt Kremer ◽  
Michael Murat

ABSTRACTWe describe how molecular dynamics simulations for a relatively simple coarse grained model can be very useful for investigating the static and dynamic properties of polymers and other macromolecular liquids. We show that it is important to use a simplified coarse grained model instead of a detailed microscopic model if one is interested in studying on modern supercomputers large systems which also relax slowly. As examples we present results for isolated star polymers with f-arms and diluted gelation/percolation clusters. We find in agreement with recent neutron scattering experiments that diluted percolation clusters swell and that their fractal dimension is reduced from 2.5 to 2. We also discuss our results for a dense melt of entangled linear polymers to show that the method is effective at high density. Our results for the entangled melt cover the crossover from Rouse to reptation and strongly support the concept of reptation.


Fractals ◽  
2003 ◽  
Vol 11 (supp01) ◽  
pp. 37-52 ◽  
Author(s):  
F. MALLAMACE ◽  
S. H. CHEN ◽  
P. GAMBADAURO ◽  
D. LOMBARDO ◽  
A. FARAONE ◽  
...  

In this work we study an attractive micellar system for which the percolation curve terminates near the critical point. We have studied such an intriguing situation by means of scattering (elastic and dynamical) and viscoelasticity experiments. Obtained data are accounted by considering in a proper way the fractal clustering processes typical of percolating systems and the related scaling concepts. We observe that the main role in the system structure and dynamics it is played by the cluster's partial screening of hydrodynamic interaction. This behaves on approaching the percolation threshold dramatic effects on the system rheological properties and on the density decay relaxations. The measured correlation functions assume a stretched exponential form and the system becomes strongly viscoelastic. The overall behavior of the measured dynamical and structural parameters indicates, that in the present micellar system, the clustering process originates dilute, polydisperse and swelling structures. Finally, this originates an interesting situation observed in the present experiment. As it has been previously, proposed by A. Coniglio et al., percolation clusters can be considered to be "Ising clusters" with the same properties as the Fisher's critical droplets. Therefore at the critical point the percolation connectedness length (ξp) can be assumed as the diverging correlation length (ξp ≡ ξ) and the mean cluster size diverges as the susceptibility.


Sign in / Sign up

Export Citation Format

Share Document