PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 4, 2026Polymers1 citationsOpen Access

Synergistic Enhancement of HCF Lifespan in Carbon–Kevlar/Epoxy Hybrid Composites UsingSilica and Graphene Nanoparticles

View Full Paper
IVIman VoghofiShahid Rajaee Teacher Training UniversityFGFaramarz Ashenai GhasemiShahid Rajaee Teacher Training UniversityKKKazem Reza KashyzadehPeoples' Friendship University of Russia

Key Points

  • The research aims to optimize the high-cycle fatigue (HCF) performance of carbon–Kevlar/epoxy hybrid composites using silica and graphene nanoparticles.
  • Fabrication of laminates using hand lay-up and press molding processes.
  • Application of Taguchi design of experiments to study 16 material configurations with varying nanoparticle percentages.
  • Conducting axial fatigue tests at a constant frequency of 5 Hz and stress ratios at different levels.
  • Scanning electron microscopy (SEM) analysis to evaluate fracture surfaces and microstructural features.
  • The optimal hybrid formulation achieved a significant increase in fatigue life compared to the baseline composite.
  • Maximum stress levels for the optimal hybrid reached 253 MPa, compared to 137 MPa for the baseline at 65% UTS.
  • SEM revealed that uniform dispersion of nSiO2 and full matrix coverage on fibers contributed to enhanced performance.
  • Sub-optimal formulations showed agglomeration, which negatively influenced fatigue performance despite high static strength.

Abstract

High-cycle fatigue (HCF) behavior of multi-scale hybrid composites remains a critical area of investigation for advanced applications in aerospace and automotive industries. This study aims to experimentally investigate and optimize the HCF performance of carbon–Kevlar/epoxy hybrid composites through synergistic incorporation of nano-silica (nSiO2) and nano-graphene (nGr). Laminates were fabricated using a hand lay-up process followed by press molding, with a 2 carbon fiber/4 Kevlar fiber/2 carbon fiber stacking sequence. Sixteen material configurations were investigated based on a Taguchi design of experiment (DOE), with two input parameters (nanoparticle percentages) at four different levels each. Following tensile screening tests, three optimal formulations were selected for fatigue evaluation alongside a non-reinforced baseline. Axial fatigue tests were conducted under load-controlled conditions with a stress ratio of R = 0.01 at a constant frequency of 5 Hz. Stress levels were set at 65%, 70%, and 75% of the ultimate tensile strength (UTS), which ranged from 211 MPa for the baseline composite to 390 MPa for the optimal hybrid formulation (1.2 wt.% nSiO2 and 0.75 wt.% nGr). Scanning electron microscopy (SEM) analysis of fracture surfaces was performed to correlate microstructural features with fatigue performance. The results demonstrate a remarkable synergistic effect. The optimal hybrid nanocomposite exhibited superior fatigue life, sustaining significantly higher maximum stress (253 MPa vs. 137 MPa at 65% UTS) and achieving a life increase of several-fold compared to the non-modified baseline. SEM observations revealed that this enhancement stems from complementary microstructural mechanisms: nSiO2 particles are uniformly dispersed without agglomeration, providing matrix toughening through crack deflection, while nGr sheets enhance interfacial adhesion, as evidenced by complete matrix coverage on fiber surfaces. The optimal formulation uniquely displays both mechanisms operating simultaneously, creating a true multi-scale reinforcement architecture. In contrast, sub-optimal formulations showed nanoparticle agglomerations that acted as stress concentrators under cyclic loading, explaining their intermediate fatigue performance despite high static strength.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Voghofi et al. (2026) studied this question.

synapsesocial.com/papers/69d0aefd659487ece0fa4d5fhttps://doi.org/10.3390/polym18070866
Ask AI
Helpful
Bookmark
Share
View Full Paper