Modified C/SiC composites with high ablation resistance: Data‐driven intelligent design and experimental validation

Abstract Improving the ablation resistance of carbon fiber‐reinforced silicon carbide (C/SiC) composites is essential to meet the stringent demands of ultra‐high‐temperature applications, but traditional empirical design approaches are resource‐intensive and time‐consuming. This study presents a novel data‐driven methodology integrating machine learning (ML) with experimental validation to optimize C/SiC composite ablation resistance. Through systematic data preprocessing and feature analysis of 102 experimental samples, an XGBoost regression model was developed, achieving satisfactory prediction accuracy (mean absolute error < ∼0.075, mean squared error < ∼0.015, and coefficient of determination [R 2 ] > ∼0.75) for ablation rate. SHapley Additive exPlanations (SHAP) analysis revealed that modifier properties, particularly standard enthalpy and melting point, predominantly influence ablation resistance. The ML‐guided design strategy, implemented through Bayesian optimization, led to the successful fabrication of ZrB 2 ‐modified C/SiC composites with exceptional ablation resistance. The optimized composite, containing approximately 20.0 vol.% ZrB 2 , achieved a linear ablation rate of 2.083 µm/s under oxyacetylene torch testing, representing a significant improvement over conventional compositions. Microstructural analysis confirmed the formation of a dense SiO 2 ‒B 2 O 3 protective layer, validating the predicted mechanism of enhanced ablation resistance. This work establishes a robust framework for accelerated development of ultra‐high‐temperature ceramics and demonstrates the efficacy of ML‐driven approaches in materials design optimization. An object‐oriented software with interactive graphical user interface has been developed. These methodologies have been integrated into an interactive software, Modified C/SiC Ablation Rate intelligent design Software (MARS), creating an efficient tool for the accelerated design of C/SiC composites with tailored ablation performance.