研究目的
To examine the interplay between grain-size and fracture of polycrystalline cubic silicon carbide (3C-SiC) using a multiscale modeling framework.
研究成果
The MD-PD multiscale framework successfully predicted that fracture strength follows a Hall-Petch law (decreasing with grain size), while mode-I fracture toughness increases with grain size in polycrystalline 3C-SiC. The framework provides a robust method for linking atomic-scale properties to mesoscale behavior, offering insights into microstructure-property relationships and enabling future studies on complex materials.
研究不足
The study relies on computational models (MD and PD), which may not fully capture all real-world complexities such as electronic effects or experimental variabilities. The Tersoff potential in MD does not include electronic degrees of freedom. The PD model assumes brittle fracture and uses simplified bond-based interactions, which might not account for all fracture mechanisms. Grain boundary types and sizes are limited to the ranges simulated, and extrapolation to other conditions may require validation.
1：Experimental Design and Method Selection:
A multiscale/multiphysics framework combining molecular dynamics (MD) for atomistic simulations and peridynamics (PD) for mesoscale simulations was implemented. MD was used to simulate single crystals and bicrystals with various grain boundary configurations, while PD was used for polycrystalline systems. The Tersoff interatomic potential was chosen for MD to describe covalent bonding in 3C-SiC. The prototype micro-brittle (PMB) model was used in PD for brittle fracture modeling.
2：Sample Selection and Data Sources:
MD simulations involved single crystals with 25 different crystallographic orientations and 172 bicrystals (16 symmetric tilt grain boundaries, 132 asymmetric tilt grain boundaries, and 24 random grain boundaries). PD simulations used polycrystalline cells generated via Voronoi tessellation with grain sizes ranging from 200 nm to 550 nm.
3：List of Experimental Equipment and Materials:
Computational simulations were performed using the LAMMPS software framework. No physical equipment was used as it is a computational study.
4：Experimental Procedures and Operational Workflow:
For MD, simulation cells were equilibrated using NPT and NVT ensembles at 300 K, followed by uniaxial deformation at a strain rate of
5：001/ps to induce mode-I fracture. Properties like elastic modulus and fracture toughness were extracted. For PD, polycrystalline cells were subjected to similar uniaxial strain, with parameters derived from MD results through statistical analysis (Monte Carlo simulations). Stress-strain responses were recorded. Data Analysis Methods:
Statistical analysis included calculating mean, standard deviation, and coefficient of variation for properties. Weibull analysis was performed on fracture stress data. Fracture energy and toughness were computed from energy differences and area measurements using software like OVITO for visualization.
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