This work demonstrates dynamic recrystallization and flow stress analysis in B4C/Al composites, suggesting optimized hot deformation strategies.
In this study, a 15 wt% B4C/7093Al composite was fabricated via powder metallurgy, and its hot deformation behavior and microstructural evolution were systematically investigated at temperatures ranging from 300 °C to 500 °C and strain rates between 0.001s−1 and 10 s−1. The composite exhibited pronounced sensitivity to both temperature and strain rate. At a given temperature, dynamic recovery dominated at lower strain rates, while dynamic recrystallization was markedly enhanced at higher rates. A back-propagation neural network optimized using the Sparrow Search Algorithm (SSA–BP) was established and demonstrated excellent predictive accuracy for flow stress (R2 = 0.996). Electron backscatter diffraction (EBSD) analysis revealed a distinct transition from recovery-dominated to recrystallization-dominated mechanisms with increasing temperature. The B4C particles exerted a dual regulatory effect—promoting recrystallization through particle-stimulated nucleation (PSN) while simultaneously inhibiting grain growth via the Zener pinning effect—resulting in a refined grain size range of 2.07–7.58 μm. Furthermore, the incorporation of B4C significantly weakened texture intensity (f(g) < 2.5), leading to a more randomized orientation distribution. Transmission electron microscopy (TEM) characterization confirmed the dynamic precipitation of η' (Al4Mg2Zn3, AlZnMgCu) and η (MgZn2) phases during deformation. These findings provide a scientific basis for optimizing hot working parameters and establish a solid theoretical foundation for the industrial application of B4C-reinforced aluminum matrix composites.
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Wu et al. (2025) studied this question.
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