Effective electrical conductivity of microstructural patterns of binary mixtures on a square lattice in the presence of nearest-neighbour interactions
R. Wiśniowski and
W. Olchawa
Physica A: Statistical Mechanics and its Applications, 2018, vol. 512, issue C, 293-304
Abstract:
The effective conductivity and percolative behaviour of microstructural patterns of binary mixtures are studied. Microstructure patterns are not entirely random, but result from the presence of attractive or repulsive interactions and thermal fluctuations. The interactions of the particles with one another lead to the formation of correlations between particle positions, while thermal fluctuations weaken these correlations. A simple lattice model is used, where each site is occupied by a single particle, and interactions can occur only between the nearest neighbours. The Kawasaki algorithm is adopted to create 2D microstructure samples. The microstructure is treated as a continuous medium, which means that the contribution from the flow through ‘choke points’ is taken into account in the calculation of the effective conductivity. We studied the thermodynamics of the system and its effective conductivity in a wide range of parameters. A change in the percolation threshold when the temperature changed was observed. The direction of the threshold shift depends on the sign of the interaction between the particles. In the high temperature range, we obtained a formula describing the dependence of the percolation threshold on temperature, as well as on the critical exponent.
Keywords: Effective properties of heterogeneous materials; Lattice model; Percolation (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437118310719
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:512:y:2018:i:c:p:293-304
DOI: 10.1016/j.physa.2018.08.128
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().