Shear behavior of SiC_f/SiC interface under the thermo-chemo-mechanical influence and machine-learning-based interfacial microstructure design

Abstract

The mechanical behavior of composite interface can be influenced by multiple factors, including the morphological roughness, the structure of coating interphase, and the temperature. Here, high-throughput molecular dynamics (MD) simulations are carried out to investigate the entangled effects of these factors on the shear stiffness G, the friction coefficient μ, the debonding strain ϵ_d and stress τ_d, of SiCf/SiC interface. We find that G is maximized by small roughness and high temperature for the optimal chemical bonding effect; μ and ϵ_d are maximized by large roughness and low temperature, taking advantage of the mechanical interlocking effect while avoiding cusp softening; τ_d demonstrates two local maxima which result from the competition between chemical bonding and mechanical interlocking. Provided the MD simulation results, a variational autoencoder (VAE) model is proposed to design the microstructure of SiCf/SiC interface for desired shear properties. According to the validations, the VAE-predicted interfacial configuration demonstrates highly similar shear properties to the reference one, justifying its potential for the microstructure design of composite interface. The results of this work can be employed to facilitate the development of SiCf/SiC composite by taking advantage of the synergistic effects of multiple designable factors.