Machine Learning Accelerated Prediction of Mechanical Properties in SiC Nanophononic Heterostructures

doi:10.16553/j.cnki.issn1000-985x.2025.0207

Abstract

Abstract: To systematically investigate the coupled effects of temperature and pore geometry on the mechanical properties of SiC nanophononic heterostructures （NHs），molecular dynamics simulations combined with a random forest machine learning method are employed to analyze the fracture behavior of SiC NHs under uniaxial tension in the temperature range from 50 K to 500 K. The models feature different pore sizes and aspect ratios of rectangular phononic crystal pores，with interfaces constructed along the armchair and zigzag crystal orientations. The results show that，as temperature increases，the fracture strength and fracture strain of SiC NHs decrease by 20%~32% and 26%~35%，respectively. The pore length of the rectangular phononic pores along the loading direction is identified as the dominant geometric parameter controlling the fracture strength. SiC NHs with armchair interfaces exhibit fracture strengths approximately 15%~20% higher than those with zigzag interfaces，and larger phononic pore sizes significantly intensify local stress concentration and thermal softening effects. The random forest model constructed based on molecular dynamics simulation data achieves high accuracy （R²=0.99） in predicting the fracture properties of SiC NHs，while its computational efficiency is about 600 times higher than that of molecular dynamics tensile simulations. This work provides theoretical support and a fast prediction tool for the controllable fabrication and mechanical performance design of SiC NHs in SiC nano-devices.

Key words: SiC NH; mechanical property; molecular dynamics; random forest; machine learning

CLC Number:

O471.5

DU Yifan, LIU Jingsong, JIANG Ping, REN Longjun. Machine Learning Accelerated Prediction of Mechanical Properties in SiC Nanophononic Heterostructures[J]. Journal of Synthetic Crystals, 2026, 55(2): 291-300.

Figures/Tables 6

Fig.1 Schematic diagram of atomic structure and phononic crystal pores of SiC NHs. （a） Atomic structure of SiC NHs；（b） nano phonon pores

Fig.2 Stress-strain curves of SiC NHs at armchair interface under different sizes （2×2，2×3，2×4，3×2，3×3，3×4，4×2，4×3，and 4×4） of phononic crystals

Fig.3 Stress-strain curves of SiC NHs at zigzag interface under different sizes （2×2，2×3，2×4 3×2，3×3，3×4，4×2，4×3，and 4×4） of phononic crystals

Fig.4 Initial crack diagrams of SiC NHs at armchair and zigzag interfaces under different sizes （2×2，2×3，2×4，3×2，3×3，3×4，4×2，4×3，and 4×4） of phononic crystals

Fig.5 Calculate fracture strain-temperature and fracture stress-temperature for SiC NHs at armchair and zigzag interface with different temperatures

Fig.6 Prediction model and result analysis of mechanical properties of SiC NHs based on random forest. （a） Schematic diagram of search algorithm based on random forest model；（b） sensitivity of eigenvalues to objective function；（c） fracture strain of SiC NHs；（d） fitting results of fracture stress on test set

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