Predicting the Size Scaling in Strength of Nanolayered Materials by a Discrete Slip Crystal Plasticity Model
Abstract
The main attraction of metallic nanolayered composites (MNCs) lies not only with their five-to ten-fold increases in strength over that of their constituents, but also in the tunability of their superior strength with nanolayer thickness. While the size scaling in strength prevails in many MNC material systems, the size scaling cannot be accurately predicted with crystal plasticity framework. Here, we present a crystal plasticity based computational method that considers plasticity to occur in grain boundary-controlled discrete slip events and apply it to predict the deformation response and underlying mechanisms in Cu/Nb MNCs. Predicted tensile stress-strain responses are shown to achieve agreement with measurements for four distinct nanolayer thicknesses, without introducing adjustable parameters. The model predicts the Hall-Petch size scaling of strength on layer thickness and the rising plastic anisotropy as the layer thickness reduces. Analysis of the results indicates that the origin of the layer size effect on strength results from the limits layer thickness places on the lengths of dislocations sources lying in the grain boundaries.
Recommended Citation
T. Chen et al., "Predicting the Size Scaling in Strength of Nanolayered Materials by a Discrete Slip Crystal Plasticity Model," International Journal of Plasticity, vol. 124, pp. 247 - 260, Elsevier Ltd, Jan 2020.
The definitive version is available at https://doi.org/10.1016/j.ijplas.2019.08.016
Department(s)
Materials Science and Engineering
Keywords and Phrases
Crystal Plasticity; Dislocations; Finite Elements; Grain Boundaries; Layered Material
International Standard Serial Number (ISSN)
0749-6419
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2020 Elsevier Ltd, All rights reserved.
Publication Date
01 Jan 2020
Comments
This work was supported by the grants from NSF CAREER Award (CMMI-1652662).