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A two-scale model predicting the mechanical behavior of nanocrystalline solids

Abstract:
Polycrystalline materials, with nanosized grains (< 100 nm), exhibit superior strength exceeding those of their coarse-grained counterparts. With such small grains, the deformation mechanisms taking place at grain boundaries (GBs) become dominant compared to the intragranular crystal plasticity. Recent studies have revealed that the deformation mechanisms are influenced by the GB network. For instance, a high yield stress in nanostructured metals can be obtained by choosing the relevant grain boundary character distribution (GBCD). In this paper we present an original numerical multiscale approach to predict the mechanical behavior of nanostructured metals according to their GBCD composed of either high angle (HA) GBs (HAB) or low angle (LA) GBs (LAB). Molecular simulations using the quasicontinuum method (QC) are performed to obtain the mechanical response at the nanoscale of GB undergoing simple shear (GB sliding behavior) and tensile loads (GB opening behavior). To simulate the grain behavior, a mechanical model of dislocation motions through a forest dislocation is calibrated using a nanoindentation simulation performed with QC. These QC results are then used in a finite element code (direct numerical simulation-DNS) as a GB constitutive model and as a grain constitutive model. This two-scale framework does not suffer from length scale limitations conventionally encountered when considering the two scales separately. © 2013 Elsevier Ltd. All rights reserved.
Publication status:
Published

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Publisher copy:
10.1016/j.jmps.2013.04.009

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Journal:
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS More from this journal
Volume:
61
Issue:
9
Pages:
1895-1914
Publication date:
2013-09-01
DOI:
ISSN:
0022-5096


Keywords:
Pubs id:
pubs:404096
UUID:
uuid:01879d4f-2487-4d6d-a46a-1a076fdd825a
Local pid:
pubs:404096
Source identifiers:
404096
Deposit date:
2013-11-16
ARK identifier:

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