Percolation structure model in the smearing region†

Snarskiı̆, A. A.; Morozovsky, A. E.

doi:10.1080/00207219508926146

Cited by 10 publications

(3 citation statements)

References 3 publications

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“…Note that in ZT (20) parameters of thermoelectric materials 1 1 1 , ,    and 2 2 2 , ,    form a peculiar combination (just as 2 Z    ), which is not, however, a direct function of 1 h     ) the distribution of currents and fields in a medium close to flow threshold, i.e. at 1   is "controlled" by percolation structure -bridges and interlayers [13][14][15]. The presence of additional processes, in this case thermoelectric, certainly, affects the distribution of currents in a medium, however, bridges and interlayers remain the governing elements of percolation structure, as before.…”

Section: Self-dual Mediamentioning

confidence: 99%

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The Effective Properties of Macroscopically Inhomogeneous Ferromagnetic Composites

Snarskiı̆

Zhenirovsky

2004

Continuum Models and Discrete Systems

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 Review of theoretical methods for description of thermoelectrical properties of two-phase macroscopically inhomogeneous media is given. Description by means of a hierarchical model of percolation structure is given, allowing a description on a qualitative and quantitative level of the basic regularities of effective thermoelectric coefficient close to flow threshold. А.А. Snarskii I.V. Bezsudnov А.А. Snarskii, I.V. Bezsudnov Thermoelectric properties of macroscopically inhomogeneous composites

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Section: Self-dual Mediamentioning

confidence: 99%

“…In so doing, we will consider that 2 1 1    and 2 1    . As it will be obvious, a hierarchical model of percolation structure [13][14][15] makes possible not only to show the difference in behaviour of e  for these cases, but also to determine critical indexes e  .…”

Section: Research On Behaviour Of E Ementioning

confidence: 99%

The Effective Properties of Macroscopically Inhomogeneous Ferromagnetic Composites

Snarskiı̆

Zhenirovsky

2004

Continuum Models and Discrete Systems

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“…1 where different first level generators are assumed depending on whether the percolating cluster exists or does not. Let us eventually note that more detailed treatment of the problem is possible if we use the new model of two-phase systems working inside the smearing region, 27 i.e., for ͉͉Ͻh instead of the model of Fig. 1.…”

Section: Hierarchical Modelmentioning

confidence: 99%

Voltage distribution in a two-component random system

Kolek

1996

Phys. Rev. B

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A disordered medium composed of randomly arranged metal and insulator, both with finite conductance, is considered. The distribution of voltage drops in such two-component random system has been calculated both analytically and numerically. It is shown that the distribution N(y) of the logarithm of voltage drops, yϭϪln(2), is the sum of several members, N ck (y) and N ik (y), kϭ0,1,2,. .. . Members N ck (y) describe the voltage distribution in the metallic phase. Members N ik (y) describe the voltage distribution in the insulating component. The subsequent members are shifted subsequently on the y axis by an amount of 2k ln(hL 1/()), where is the crossover exponent and is the percolation correlation length exponent. The zero-order member of the N ck family is governed by the multifractal spectrum f (␣), where ␣ϭy/lnL, found originally for the random resistor network. The zero-order member of the N ik family is governed by the multifractal spectrum (␣) found originally for the random resistor superconductor network. The next members are built from two components. The first one is the scaled repetition of N c0 for the N ck family or N i0 for the N ik family. The other one is the distribution of voltage drops in such percolation objects like dangling ends, isolated clusters for the N ck family or clusters perimeter for the N ik family.

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