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<p>This scientific research systematically investigates the mechanical and tribological behavior of AA332 aluminium alloy composites reinforced with 0-7.5 wt% zirconium diboride (ZrB<sub>2</sub>) particles, synthesized via stir casting. Qualitative microstructural analysis revealed a uniform dispersion of ZrB<sub>2</sub> particles and strong interfacial bonding, which quantitatively resulted in a significant grain refinement of 46.6%. Mechanical characterization demonstrated substantial quantitative improvements: Brinell hardness increased by 33.0% (from 92.0 to 122.4 BHN), ultimate tensile strength by 32.9% (from 155 to 206&#xa0;MPa), and yield strength by 67.4% (from 92 to 154&#xa0;MPa). A characteristic strength-toughness trade-off was observed, characterized by an impact energy reduction from 3.8 to 2.0&#xa0;J and a qualitative transition from ductile to mixed-mode fracture mechanisms. Tribological performance was evaluated and optimized using Response Surface Methodology (RSM), identifying that a combination of 7.5 wt% ZrB<sub>2</sub>, 200&#xa0;rpm sliding speed, and 25&#xa0;N load yields a minimal specific wear rate of 0.843 × 10⁻⁴ mm³/Nm. This represents an 80.4% reduction in wear rate compared to the maximum wear condition observed in the 2.5 wt% ZrB<sub>2</sub> composite. Predictive modeling using Artificial Neural Networks (ANN) validated the RSM findings, achieving superior predictive accuracy (Testing R² = 0.9947), with feature importance analysis quantitatively establishing ZrB<sub>2</sub> content as the dominant predictor (68.3%) of wear behavior. This integrated experimental and data-driven approach highlights the potential of ZrB<sub>2</sub>-reinforced AA332 composites for structural applications requiring elevated strength and wear resistance.</p>

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Enhanced mechanical and tribological performance of AA332 aluminium alloy reinforced with ZrB2 using integrated experimental and machine learning approaches

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月21日

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  • Palanisamy Pugalenthi,
  • R. Prabu,
  • Sivakumar Ponmalai,
  • Saravana Murthi Chinnasamy,
  • S. N. Vijayan,
  • A. Saiyathibrahim,
  • A. Johnson Santhosh

摘要

This scientific research systematically investigates the mechanical and tribological behavior of AA332 aluminium alloy composites reinforced with 0-7.5 wt% zirconium diboride (ZrB2) particles, synthesized via stir casting. Qualitative microstructural analysis revealed a uniform dispersion of ZrB2 particles and strong interfacial bonding, which quantitatively resulted in a significant grain refinement of 46.6%. Mechanical characterization demonstrated substantial quantitative improvements: Brinell hardness increased by 33.0% (from 92.0 to 122.4 BHN), ultimate tensile strength by 32.9% (from 155 to 206 MPa), and yield strength by 67.4% (from 92 to 154 MPa). A characteristic strength-toughness trade-off was observed, characterized by an impact energy reduction from 3.8 to 2.0 J and a qualitative transition from ductile to mixed-mode fracture mechanisms. Tribological performance was evaluated and optimized using Response Surface Methodology (RSM), identifying that a combination of 7.5 wt% ZrB2, 200 rpm sliding speed, and 25 N load yields a minimal specific wear rate of 0.843 × 10⁻⁴ mm³/Nm. This represents an 80.4% reduction in wear rate compared to the maximum wear condition observed in the 2.5 wt% ZrB2 composite. Predictive modeling using Artificial Neural Networks (ANN) validated the RSM findings, achieving superior predictive accuracy (Testing R² = 0.9947), with feature importance analysis quantitatively establishing ZrB2 content as the dominant predictor (68.3%) of wear behavior. This integrated experimental and data-driven approach highlights the potential of ZrB2-reinforced AA332 composites for structural applications requiring elevated strength and wear resistance.