IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v482y2017icp56-64.html
   My bibliography  Save this article

Grain boundary and lattice diffusion in nanocrystal α-iron: An atomistic simulation study

Author

Listed:
  • Mohammadzadeh, Roghayeh
  • Mohammadzadeh, Mina

Abstract

To obtain fundamental understanding on the effect of grain boundaries on the diffusion kinetics, molecular dynamics simulations (MD) were carried out on single crystal and nanocrystal (with a mean grain size of 2.5 nm) bcc iron using the second nearest-neighbor modified embedded atom method (2NN-MEAM) interatomic potential. Self-diffusion coefficient in single crystal and nanocrystal samples were calculated in the temperature range from 350 K to 1000 K. A temperature-dependence of the diffusion coefficient according to the Arrhenius law was obtained for both lattice and grain boundary diffusion. By doing so, activation energies as well as pre-exponential factors were derived from the diffusion coefficients and compared to experimental data. MD simulation results show that diffusion rate of iron atoms in nanocrystal sample is 6 to 28 orders of magnitude greater than single crystal. The trajectory of iron atoms during diffusion process verified that diffusion occurs mostly in the grain boundaries of nanocrystal iron; suggesting that grain boundary diffusion is dominant in nanocrystal iron. Based on the obtained results pure grain boundary diffusion coefficient was calculated.

Suggested Citation

  • Mohammadzadeh, Roghayeh & Mohammadzadeh, Mina, 2017. "Grain boundary and lattice diffusion in nanocrystal α-iron: An atomistic simulation study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 56-64.
  • Handle: RePEc:eee:phsmap:v:482:y:2017:i:c:p:56-64
    DOI: 10.1016/j.physa.2017.04.070
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117303801
    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/j.physa.2017.04.070?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.

    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:482:y:2017:i:c:p:56-64. 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.