Comparative Analysis of Processing-Property Relationships in Metal and Polymer Matrix Composites: A Unified Statistical Framework for Hardness Characterization

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Year : 2026 | Volume : 14 | 02 | Page :
    By

    Charan Gopi Krishna Kondapalli,

  • S. N. Padhi,

  • Shaik Nagoor Baba,

  1. M Tech Student, Department of Mechanical Engineering, Koneru Laksmaiah Education Foundation, Vaddeswaram, Guntur District, Andhra Pradesh, India
  2. Professor, Department of IRD & Mechanical Engineering, Koneru Laksmaiah Education Foundation, Vaddeswaram, Guntur District, Andhra Pradesh, India
  3. M Tech Student, Department of Mechanical Engineering, Koneru Laksmaiah Education Foundation, Vaddeswaram, Guntur District, Andhra Pradesh, India

Abstract

Composite materials, encompassing both metal matrix composites (MMCs) and polymer matrix composites (PMCs), exhibit complex processing-property relationships that fundamentally govern their mechanical performance across diverse applications. This study presents a unified statistical framework for analyzing hardness characteristics in composite systems, using aluminum-tungsten carbide (Al-WC) metal matrix composites as a representative model system while establishing connections to polymer matrix composite behavior. The investigation employed comprehensive processing parameter optimization, microstructural characterization, and advanced statistical analysis to quantify processing-property relationships and their variability across composite types. Al-WC composites were fabricated through powder metallurgy with WC reinforcement levels of 2-6 wt% and sintering temperatures of 400-600°C. Results demonstrate that hardness enhancement in Al-WC composites follows predictable trends governed by volume fraction and processing parameters, achieving maximum hardness values of 83.8 HRB for 6% WC content sintered at 600°C. Comparative analysis with polymer composite literature reveals analogous behavior patterns, where both systems exhibit similar volume fraction dependencies (Hc ∝ Vf0.4-0.6) and processing sensitivity despite fundamentally different enhancement mechanisms—dislocation blocking in MMCs versus stress transfer optimization in PMCs. Statistical modeling successfully captures property variability across both composite types, with correlation coefficients exceeding 0.85 for hardness prediction models. The developed framework provides quantitative tools for processing optimization in both metal and polymer matrix systems, contributing to fundamental composite science understanding while offering practical guidelines for material design across diverse composite applications.

Keywords: Composite materials, aluminum matrix composites, polymer matrix composites, tungsten carbide, powder metallurgy, hardness analysis, statistical modeling, processing-property relationships.

How to cite this article:
Charan Gopi Krishna Kondapalli, S. N. Padhi, Shaik Nagoor Baba. Comparative Analysis of Processing-Property Relationships in Metal and Polymer Matrix Composites: A Unified Statistical Framework for Hardness Characterization. Journal of Polymer & Composites. 2026; 14(02):-.
How to cite this URL:
Charan Gopi Krishna Kondapalli, S. N. Padhi, Shaik Nagoor Baba. Comparative Analysis of Processing-Property Relationships in Metal and Polymer Matrix Composites: A Unified Statistical Framework for Hardness Characterization. Journal of Polymer & Composites. 2026; 14(02):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=239792


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Ahead of Print Subscription Original Research
Volume 14
02
Received 15/10/2025
Accepted 29/12/2025
Published 07/04/2026
Publication Time 174 Days
25

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