906
Views
137
CrossRef citations to date
0
Altmetric
Original Articles

Atomic modelling of strengthening mechanisms due to voids and copper precipitates in α-iron

, &
Pages 3623-3641 | Received 11 Oct 2002, Accepted 22 Feb 2003, Published online: 12 May 2010
 

Abstract

Recently a model has been developed by Osetsky and Bacon to study edge dislocations moving over large distances on the atomic scale. It permits investigation of motion of a dislocation under different conditions of applied shear stress with constant or variable strain rate and temperature, and in the presence of obstacles. In this paper we apply the model to study the motion of an infinite straight but flexible edge dislocation through a row of either voids or coherent copper precipitates in bcc iron. Stress–strain curves, energy barrier profile and strength characteristics of obstacles and other dislocation configuration information have been obtained from the modelling and compared with continuum treatments. Some specific atomic-scale mechanisms associated with strengthening due to voids and precipitates over a range of size have been observed and discussed.

Acknowledgements

This research was supported by the UK Engineering and Physical Sciences Research Council. It was undertaken when V.M. held a Fellowship of the Deutsche Forschungemeinschaft at the University of Liverpool.

Notes

† Email: [email protected].

Additional information

Notes on contributors

Yu. N. OsetskyFootnote

† Email: [email protected].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 786.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.