IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v512y2018icp293-304.html
   My bibliography  Save this article

Effective electrical conductivity of microstructural patterns of binary mixtures on a square lattice in the presence of nearest-neighbour interactions

Author

Listed:
  • Wiśniowski, R.
  • Olchawa, W.

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.

Suggested Citation

  • Wiśniowski, R. & Olchawa, W., 2018. "Effective electrical conductivity of microstructural patterns of binary mixtures on a square lattice in the presence of nearest-neighbour interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 293-304.
  • Handle: RePEc:eee:phsmap:v:512:y:2018:i:c:p:293-304
    DOI: 10.1016/j.physa.2018.08.128
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118310719
    Download Restriction: 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

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:512:y:2018:i:c:p:293-304. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.