The effect of grain-size on fracture of polycrystalline silicon carbide: A multiscale analysis using a molecular dynamics-peridynamics framework
S Gur and MR Sadat and GN Frantziskonis and S Bringuier and LY Zhang and K Muralidharan, COMPUTATIONAL MATERIALS SCIENCE, 159, 341-348 (2019).
DOI: 10.1016/j.commatsci.2018.12.038
A robust atomistic to mesoscale computational multiscale/multiphysics modeling framework that explicitly takes into account atomic-scale descriptions of grain-boundaries, is implemented to examine the interplay between grain-size and fracture of polycrystalline cubic silicon carbide (3C-SiC). A salient feature of the developed framework is the establishment of scale-parity between the chosen atomistic and the mesoscale methods namely molecular dynamics (MD) and peridynamics (PD) respectively, which enables the ability to model the effect of the underlying microstructure as well as obtain relevant new insights into the role of grain-size on the ensuing mechanical response of 3C-SiC. Material properties such as elastic modulus, and fracture toughness of single crystals and bicrystals of various orientations are obtained from MD simulations, and using appropriate statistical analysis, MD derived properties are interfaced with PD simulations, resulting in mesoscale simulations that accurately predict the role of grain-size on failure strength, fracture energy, elastic modulus, fracture toughness, and tensile toughness of polycrystalline 3C-SiC. In particular, it is seen that the fracture strength follows a Hall-Petch law with respect to grain-size variations, while mode-I fracture toughness increases with increasing grain-size, consistent with available literature on brittle fracture of polycrystalline materials. Equally importantly, the developed MD-PD multiscale/multiphysics framework represents an important step towards developing materials modeling paradigms that can provide a comprehensive and predictive description of the microstructureproperty-performance interplay in solid-state materials.
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