IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v93y2020i1d10.1140_epjb_e2019-100226-1.html
   My bibliography  Save this article

The low-power law emergent response of random RCC’ networks

Author

Listed:
  • Ahmed Benyahia

    (LEPM, Faculté de Physique, USTO-MB)

  • Rachid Bouamrane

    (LEPM, Faculté de Physique, USTO-MB)

Abstract

In this paper, we analyse the emergent response of random resistor-capacitor (RC) networks, which are widely used in modeling binary composite materials. By simply introducing two kinds of capacitors C and C′, we simulate the size effect of micro-capacitors formed by dielectric regions separating conductive regions in real materials. A low-power law emergent response (low PLER) is obtained in the framework of these random networks which we will be naming (RCC’) therein. This simple model also explains the observed low frequency dispersion in porous sample of the perovskite lead zirconate titanate (PZT) as well as lead halide perovskite solar cells. The calculations has been achieved by using the well known Frank and Lobb algorithm. In addition, we investigate the effect of capacitor proportions and value ratios (C′/C) on the PLER. A good agreement with EMA predictions is obtained at intermediate frequencies. Graphical abstract

Suggested Citation

  • Ahmed Benyahia & Rachid Bouamrane, 2020. "The low-power law emergent response of random RCC’ networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 93(1), pages 1-7, January.
    • Handle: RePEc:spr:eurphb:v:93:y:2020:i:1:d:10.1140_epjb_e2019-100226-1
    DOI: 10.1140/epjb/e2019-100226-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1140/epjb/e2019-100226-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1140/epjb/e2019-100226-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Benyahia, Ahmed & Bouamrane, Rachid, 2023. "Modelling the minimum conductivity of graphene using random resistor networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).

    More about this item

    Keywords

    Solid State and Materials;

    Statistics

    Access and download statistics

    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:spr:eurphb:v:93:y:2020:i:1:d:10.1140_epjb_e2019-100226-1. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.