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Title: Inferring grain boundary structure–property relations from effective property measurements

Abstract

Grain boundaries strongly affect many materials properties in polycrystalline materials. Yet, very few structure–property models exist for grain boundaries, due in large part to the complicated and poorly understood way in which the properties of grain boundaries vary with their crystallographic structure. Here, we infer grain boundary structure–property correlations from measurements of the effective properties of a polycrystal. We refer to this method as grain boundary properties localization. We apply this technique to a simple model system of grain boundary diffusivity in a two-dimensional microstructure, and infer the properties of low- and high-angle grain boundaries from the effective diffusivity of the grain boundary network. The generalization and use of these methods could greatly reduce the computational and experimental effort required to establish structure–property correlations for grain boundaries. More broadly, the technique of properties localization could be used to infer the properties of many microstructural constituents in complex microstructures.

Authors:
ORCiD logo [1];  [2];  [1];  [1]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  2. Univ. of Alabama, Tuscaloosa, AL (United States)
Publication Date:
Research Org.:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1557826
Grant/Contract Number:  
SC0008926
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Materials Science
Additional Journal Information:
Journal Volume: 50; Journal Issue: 21; Journal ID: ISSN 0022-2461
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Localization Problem; Effective Diffusivity; Percolation Threshold; Triple Junction; Effective Property

Citation Formats

Johnson, Oliver K., Li, Lin, Demkowicz, Michael J., and Schuh, Christopher A. Inferring grain boundary structure–property relations from effective property measurements. United States: N. p., 2015. Web. doi:10.1007/s10853-015-9241-4.
Johnson, Oliver K., Li, Lin, Demkowicz, Michael J., & Schuh, Christopher A. Inferring grain boundary structure–property relations from effective property measurements. United States. doi:10.1007/s10853-015-9241-4.
Johnson, Oliver K., Li, Lin, Demkowicz, Michael J., and Schuh, Christopher A. Tue . "Inferring grain boundary structure–property relations from effective property measurements". United States. doi:10.1007/s10853-015-9241-4. https://www.osti.gov/servlets/purl/1557826.
@article{osti_1557826,
title = {Inferring grain boundary structure–property relations from effective property measurements},
author = {Johnson, Oliver K. and Li, Lin and Demkowicz, Michael J. and Schuh, Christopher A.},
abstractNote = {Grain boundaries strongly affect many materials properties in polycrystalline materials. Yet, very few structure–property models exist for grain boundaries, due in large part to the complicated and poorly understood way in which the properties of grain boundaries vary with their crystallographic structure. Here, we infer grain boundary structure–property correlations from measurements of the effective properties of a polycrystal. We refer to this method as grain boundary properties localization. We apply this technique to a simple model system of grain boundary diffusivity in a two-dimensional microstructure, and infer the properties of low- and high-angle grain boundaries from the effective diffusivity of the grain boundary network. The generalization and use of these methods could greatly reduce the computational and experimental effort required to establish structure–property correlations for grain boundaries. More broadly, the technique of properties localization could be used to infer the properties of many microstructural constituents in complex microstructures.},
doi = {10.1007/s10853-015-9241-4},
journal = {Journal of Materials Science},
number = 21,
volume = 50,
place = {United States},
year = {2015},
month = {7}
}

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Works referenced in this record:

Percolation and Conduction
journal, October 1973