Performance of SCAN Meta-GGA Functionals on Nonlinear Mechanics of Graphene-Like <i>g</i>-SiC

Although meta-generalized-gradient approximations (meta-GGAs) are believed potentially the most accurate among the efficient first-principles calculations, the performance has not been accessed on the nonlinear mechanical properties of two-dimensional nanomaterials. Graphene, like two-dimensional si...

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Bibliographic Details
Main Author: Qing Peng
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Crystals
Subjects:
Online Access:https://www.mdpi.com/2073-4352/11/2/120
Description
Summary:Although meta-generalized-gradient approximations (meta-GGAs) are believed potentially the most accurate among the efficient first-principles calculations, the performance has not been accessed on the nonlinear mechanical properties of two-dimensional nanomaterials. Graphene, like two-dimensional silicon carbide <i>g</i>-SiC, has a wide direct band-gap with applications in high-power electronics and solar energy. Taken <i>g</i>-SiC as a paradigm, we have investigated the performance of meta-GGA functionals on the nonlinear mechanical properties under large strains, both compressive and tensile, along three deformation modes using Strongly Constrained and Appropriately Normed Semilocal Density Functional (SCAN) as an example. A close comparison suggests that the nonlinear mechanics predicted from SCAN are very similar to that of Perdew-Burke-Ernzerhof (PBE) formulated functional, a standard Density Functional Theory (DFT) functional. The improvement from SCAN calculation over PBE calculation is minor, despite the considerable increase of computing demand. This study could be helpful in selection of density functionals in simulations and modeling of mechanics of materials.
ISSN:2073-4352