Random-cluster model

C. M. Fortuin and P. W. Kasteleyn (1972) On the random-cluster model. I. Introduction and relation to other models. Physica 57, pp. 536-564... 

Wei ZD, Ran HB, Liu XA, Liu Y, Sun CX, Chan SH, Shen PK. Numerical analysis of Pt utilization in PEMFC catalyst layer using random cluster model. Electrochim Acta 2006 51 3091-96. 

P.-G. de Gennes later also considered the multisegment attraction regime. He suggested the so-called p-cluster model [11] in order to explain certain anomalies in behavior observed in many polymer species such as polyethyle-neoxide (PEO) see also [12]. The scenario of coil-globule transition with dominating multisegment interaction first considered by I.M. Lifshitz has been recently studied in [13]. The authors used a computer simulation of chains in a cubic spatial lattice to show that collapse of the polymer can be due to crystallization within the random coil. 

This oversimplified random network model proved to be rather useful for understanding water fluxes and proton transport properties of PEMs in fuel cells. - - - It helped rationalize the percolation transition in proton conductivity upon water uptake as a continuous reorganization of the cluster network due to swelling and merging of individual clusters and the emergence of new necks linking them. ... 

The effective conductivity of the membrane depends on its random heterogeneous morphology—namely, the size distribution and connectivity of fhe proton-bearing aqueous pafhways. On fhe basis of the cluster network model, a random network model of microporous PEMs was developed in Eikerling ef al. If included effecfs of varying connectivity of the pore network and of swelling of pores upon water uptake. The model was applied to exploring the dependence of membrane conductivity on water content and... 

In the random-walk model, the individual ions are assumed to move independently of one another. However, long-range electrostatic interactions between the mobile ions make such an assumption unrealistic unless n is quite small. Although corrections to account for correlated motions of the mobile ions at higher values of n may be expected to alter only the factor y of the pre-exponential factor Aj., there are at least two situations where correlated ionic motions must be considered explicitly. The first occurs in stoichiometric compounds having an = 1. but a low AH for a cluster rotation the second occurs for the situation illustrated in Fig. 3.6(c). 

To summarize, d = 4 makes a border line, the upper critical dimensionJ for the excluded volume problem. For d < 4 both the cluster expansion and the loop expansion break down term by term in the excluded volume limit. For d i> 4 the expansions are valid, the leading n- or c-dependence of the results being trivial, however. We may state that for d > 4 the random walk model or Flory-Huggins type mean field theories catch the essential physics of the problem. As will be explained more accurately in Chap. 10 the mechanism behind this is the fact that for d > 4 two nncorrelated random walks in general do not cross. 

In the next chapter (Chapter 2), we estimate the fuse current of a conducting random network or the breakdown field of a randomly metal-loaded dielectric, using the percolation cluster models and their statistics. We also discuss here the breakdown probability distributions of such networks. All these theoretical estimates are compared with the extensive experimental and computer simulation results. 

This distribution appears whenever g a) is given by a power law in (j, coming from the power law variation of the density of linear cracks g l) with their length 1. In the random percolation model considered here, this does not normally occur (except at the percolation threshold p = Pc)- However, for various correlated disorder models, applicable to realistic disorders in rocks, composite materials, etc., one can have such power law distribution for clusters, which may give rise to a Weibull distribution for their fracture strength. We will discuss such cases later, and concentrate on the random percolation model in this section. 

Several cluster models have been tested to account for patterns of small clusters (p = 1 or 2 bar in Fig. 18). First, clathrate models have been examined. The most popular of these consists of a regular dodedecahedron with one H2O molecule at each of the 20 vertices and possibly one additional molecule at the center. In this model, HjO molecules form regular pentagons with a molecular angle HOH of 108°, which is intermediate between 104.5°, the value for the free molecule, and 109.5°, that for tetrahedral bonding in the diamond cubic structure. Such a clathrate model, stabilized by an additional proton, accounts well for mass spectrometry results, but is found to be far too symmetrical to account for the structure of neutral clusters. An amorphous model,derived from Polk s random dense packing, has been tested. This... 

K. W. Foreman and K. F. Freed (1998) Lattice cluster theory of multicomponent polymer systems Chain semiflexibility and speciflc interactions. Advances in Chemical Physics 103, pp. 335-390 K. F. Freed and J. Dudowicz (1998) Lattice cluster theory for pedestrians The incompressible limit and the miscibility of polyolefin blends. Macromolecules 31, pp. 6681-6690 E. Helfand and Y. Tagami (1972) Theory of interface between immiscible polymers. 2. J. Chem. Phys. 56, p. 3592 E. Helfand (1975) Theory of inhomogeneous polymers - fundamentals of Gaussian random-walk model. J. Chem. Phys. 62, pp. 999-1005... 

The present work details the derivation of a full coupled-cluster model, including single, double, and triple excitation operators. Second quantization and time-independent diagrams are used to facilitate the derivation the treatment of (diagram) degeneracy and permutational symmetry is adapted from time-dependent methods. Implicit formulas are presented in terms of products of one- and two-electron integrals, over (molecular) spin-orbitals and cluster coefficients. Final formulas are obtained that restrict random access requirements to rank 2 modified integrals and sequential access requirements to the rank 3 cluster coefficients. 

Eisenberg, A. Hird, B. Moore, R.B. A new multiplet-cluster model for the morphology of random ionomers. Macromolecules 1990,23, 4098. 

One conceptually simple approach which has been used to represent temperature effects in metallic clusters is the random matrix model, developed by Akulin et al. [700]. The principles of the random matrix model, developed in the context of nuclear physics by Wigner and others, were outlined in chapter 10. The essential idea is to treat the cluster as a disordered piece of a solid. In the first approximation, the cluster is regarded as a Fermi gas of electrons, moving in an effective, spherically symmetric short range well. Without deformations, one-electron states then obey a Fermi distribution. As the temperature is raised, various scattering processes and perturbations arise, all of which lead to a random coupling between the states of the unperturbed system. One can... 

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