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<p>This study presents an integrated experimental and simulation approach to investigate the potential of strengthening Polyamide 6 (PA6) through reinforcement with graphene, multi-walled carbon nanotubes (MWCNT), and their hybrid combinations. Twelve distinct nanocomposite configurations were examined. Material properties such as density, Young’s modulus, shear modulus, and Poisson’s ratio were predicted using Digimat 2017. These properties were then used as input for Finite Element Analysis (FEA) performed in CATIA V5R19 to analyze the deflection and Max Von Mises stress on standard ASTM D638 tensile specimens. A thorough mesh convergence study and sensitivity analysis validated the robustness of the FEA model. Experimental validation, including tensile testing and microstructural analysis (SEM/TEM), was conducted on selected optimal configurations. The findings indicate that MWCNT and hybrid (H 2:1) nanocomposites consistently exhibited superior mechanical performance, characterized by lower deflection and higher Von Mises stress, directly correlating with their excellent nanofiller dispersion and strong interfacial bonding observed in SEM and TEM. This comprehensive understanding of reinforcement mechanisms and mechanical behaviour provides critical information for material selection and design optimization, particularly for lightweight structural components in automotive, aerospace, and high-performance equipment applications.</p>

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Investigating the Microstructure and Mechanical Performance of PA6-Graphene, PA6-MWCNT, and Hybrid Nanocomposites for Engineering Applications: An Integrated Experimental and Simulation Approach

  • 期刊论文

  • 发表日期：

    2025年7月20日

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  • Suyog B. Rayjadhav,
  • Pravin R. Kubade

摘要

This study presents an integrated experimental and simulation approach to investigate the potential of strengthening Polyamide 6 (PA6) through reinforcement with graphene, multi-walled carbon nanotubes (MWCNT), and their hybrid combinations. Twelve distinct nanocomposite configurations were examined. Material properties such as density, Young’s modulus, shear modulus, and Poisson’s ratio were predicted using Digimat 2017. These properties were then used as input for Finite Element Analysis (FEA) performed in CATIA V5R19 to analyze the deflection and Max Von Mises stress on standard ASTM D638 tensile specimens. A thorough mesh convergence study and sensitivity analysis validated the robustness of the FEA model. Experimental validation, including tensile testing and microstructural analysis (SEM/TEM), was conducted on selected optimal configurations. The findings indicate that MWCNT and hybrid (H 2:1) nanocomposites consistently exhibited superior mechanical performance, characterized by lower deflection and higher Von Mises stress, directly correlating with their excellent nanofiller dispersion and strong interfacial bonding observed in SEM and TEM. This comprehensive understanding of reinforcement mechanisms and mechanical behaviour provides critical information for material selection and design optimization, particularly for lightweight structural components in automotive, aerospace, and high-performance equipment applications.