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<p>In this study, the effect of microstructural parameters, including grain size (<i>D</i>) and crystallographic texture, on the coercivity of 1.2% Si electrical steel was investigated using response surface methodology (RSM). Samples with varying antimony content (0.002%, 0.012%, and 0.026%) were cast and processed through unidirectional and cross-rolling routes. Coercivity was measured using a vibrating sample magnetometer, and a mathematical model was developed to predict coercivity based on grain size and texture parameters. The results indicate that antimony addition reduces grain size and enhances the intensity of the <i>θ</i>-fiber texture. The strain path significantly influences texture evolution, with unidirectional rolling promoting stronger desired texture components. RSM analysis revealed that grain size has a dominant effect on coercivity, as reflected in the <i>F</i>-value coefficient. A mathematical model was proposed to predict coercivity, demonstrating that larger grain sizes and higher intensities of desired textures lead to improved magnetic properties.</p>

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Modeling Coercivity in 1.2% Si Electrical Steel with Antimony Additions: A Response Surface Methodology Approach to Grain Size and Crystallographic Texture Effects

  • 期刊论文

  • 发表日期：

    2025年2月7日

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  • Amin Babapour,
  • Seyed Jamal Hosseinipour,
  • Roohollah Jamaati,
  • Majid Abbasi

摘要

In this study, the effect of microstructural parameters, including grain size (D) and crystallographic texture, on the coercivity of 1.2% Si electrical steel was investigated using response surface methodology (RSM). Samples with varying antimony content (0.002%, 0.012%, and 0.026%) were cast and processed through unidirectional and cross-rolling routes. Coercivity was measured using a vibrating sample magnetometer, and a mathematical model was developed to predict coercivity based on grain size and texture parameters. The results indicate that antimony addition reduces grain size and enhances the intensity of the θ-fiber texture. The strain path significantly influences texture evolution, with unidirectional rolling promoting stronger desired texture components. RSM analysis revealed that grain size has a dominant effect on coercivity, as reflected in the F-value coefficient. A mathematical model was proposed to predict coercivity, demonstrating that larger grain sizes and higher intensities of desired textures lead to improved magnetic properties.