IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v207y1994i1p163-167.html
   My bibliography  Save this article

Effective conductivity of porous silicon: A theoretical approach

Author

Listed:
  • Tagüeña-Martínez, J.
  • del Río, J.A.
  • Ochoa-Tapia, J.A.

Abstract

From a theoretical point of view, linear transport in homogeneous systems is well understood. However, transport phenomena through porous materials are far more complicated. In fact, there are some materials like porous silicon with a very promising technological impact, where mainly experimental evidence is available and theoretical models have scarcely been developed. In a previous work, we obtained an analytical expression for the axial effective electrical conductivity of a model simulating porous silicon (PS). We used the averaging volume method that has proven to be successful in treating fluid transport in porous media. The PS model was based on experimental information about the structure of this new material and experimental data for crystalline Si and hydrogenated a-Si thin films. With this method we can calculate the bulk and the surface contribution to the tensorial effective conductivity. Here we present the transverse effective conductivity results where percolation effects can be observed, using the same method and model. However, in the XY plane the calculation is more complicated and it can only be performed numerically. The understanding of the effective electrical conductivity behavior as a whole may be important for electronic applications of PS.

Suggested Citation

  • Tagüeña-Martínez, J. & del Río, J.A. & Ochoa-Tapia, J.A., 1994. "Effective conductivity of porous silicon: A theoretical approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 207(1), pages 163-167.
  • Handle: RePEc:eee:phsmap:v:207:y:1994:i:1:p:163-167
    DOI: 10.1016/0378-4371(94)90368-9
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0378437194903689
    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

    File URL: https://libkey.io/10.1016/0378-4371(94)90368-9?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.

    More about this item

    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:eee:phsmap:v:207:y:1994:i:1:p:163-167. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.