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<p>The performance of metal matrix composites (MMCs) is strongly influenced by the distribution and volume fraction of reinforcement particles within the matrix. Among MMCs, aluminum-based composites, especially those reinforced with zirconium carbide (ZrC), have attracted significant attention due to their superior strength, wear resistance, and thermal stability. Accurate quantification of the reinforcement and matrix phases is essential to understand and tailor the composite’s mechanical behavior. In this study, a&#xa0;fully automated image processing methodology is proposed for the segmentation and calculation of the volume fractions of ZrC and aluminum (AA7075) phases from the scanning electron microscopy-backscattered electron (SEM-BSE) images. This approach utilizes a&#xa0;systematic imaging pipeline involving grayscale conversion, Gaussian blurring for noise reduction, and Otsu’s thresholding for optimal phase separation. The colored masks are generated to visually differentiate between the matrix (green) and reinforcement (red) phases, followed by the formation of combined overlay images for an effective phase visualization. The automated algorithm accurately computes the area-based volume fractions, showing a&#xa0;significant variation across the samples with different ZrC contents. It is shown that the use of BSE imaging enhances the phase contrast, enabling precise detection and quantification. This method demonstrates a&#xa0;rapid, reproducible, and operator-independent approach for microstructural characterization, offering valuable insights for optimizing the fabrication of composites and their property control.</p>

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Automated phase segmentation and volume fraction analysis of ZrC-reinforced aluminum matrix composites using image processing techniques

  • 期刊论文

  • 发表日期：

    2025年8月1日

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  • Mrudula Gudla,
  • S. Sarveswara Reddy,
  • Prakash Putta

摘要

The performance of metal matrix composites (MMCs) is strongly influenced by the distribution and volume fraction of reinforcement particles within the matrix. Among MMCs, aluminum-based composites, especially those reinforced with zirconium carbide (ZrC), have attracted significant attention due to their superior strength, wear resistance, and thermal stability. Accurate quantification of the reinforcement and matrix phases is essential to understand and tailor the composite’s mechanical behavior. In this study, a fully automated image processing methodology is proposed for the segmentation and calculation of the volume fractions of ZrC and aluminum (AA7075) phases from the scanning electron microscopy-backscattered electron (SEM-BSE) images. This approach utilizes a systematic imaging pipeline involving grayscale conversion, Gaussian blurring for noise reduction, and Otsu’s thresholding for optimal phase separation. The colored masks are generated to visually differentiate between the matrix (green) and reinforcement (red) phases, followed by the formation of combined overlay images for an effective phase visualization. The automated algorithm accurately computes the area-based volume fractions, showing a significant variation across the samples with different ZrC contents. It is shown that the use of BSE imaging enhances the phase contrast, enabling precise detection and quantification. This method demonstrates a rapid, reproducible, and operator-independent approach for microstructural characterization, offering valuable insights for optimizing the fabrication of composites and their property control.