Ab initio calculations of the lattice parameter and elastic stiffness coefficients of bcc Fe with solutes

Fellinger, Michael R.; Hector, Louis G.; Trinkle, Dallas R.

doi:10.1016/j.commatsci.2016.09.040

Title: Ab initio calculations of the lattice parameter and elastic stiffness coefficients of bcc Fe with solutes

Journal Article · Fri Oct 28 00:00:00 EDT 2016 · Computational Materials Science

DOI:https://doi.org/10.1016/j.commatsci.2016.09.040· OSTI ID:1363783

Fellinger, Michael R. ^[1]; Hector, Louis G. ^[2]; Trinkle, Dallas R. ^[1]

Univ. of Illinois, Urbana-Champaign, IL (United States). Dept. of Materials Science and Engineering
General Motors R&D Center, Warren, MI (United States)

Here, we present an efficient methodology for computing solute-induced changes in lattice parameters and elastic stiffness coefficients Cij of single crystals using density functional theory. We also introduce a solute strain misfit tensor that quantifies how solutes change lattice parameters due to the stress they induce in the host crystal. Solutes modify the elastic stiffness coefficients through volumetric changes and by altering chemical bonds. We compute each of these contributions to the elastic stiffness coefficients separately, and verify that their sum agrees with changes in the elastic stiffness coefficients computed directly using fully optimized supercells containing solutes. Computing the two elastic stiffness contributions separately is more computationally efficient and provides more information on solute effects than the direct calculations. We compute the solute dependence of polycrystalline averaged shear and Young's moduli from the solute dependence of the single-crystal Cij. We then apply this methodology to substitutional Al, B, Cu, Mn, Si solutes and octahedral interstitial C and N solutes in bcc Fe. Comparison with experimental data indicates that our approach accurately predicts solute-induced changes in the lattice parameter and elastic coefficients. The computed data can be used to quantify solute-induced changes in mechanical properties such as strength and ductility, and can be incorporated into mesoscale models to improve their predictive capabilities.

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Research Organization:: United States Automotive Materials Partnership LLC (USAMP LLC), Southfield, MI (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V); USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: EE0005976

OSTI ID:: 1363783

Alternate ID(s):: OSTI ID: 1397601

Report Number(s):: DOE-USAMP-05976-9

Journal Information:: Computational Materials Science, Vol. 126, Issue C; ISSN 0927-0256

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 31 works

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