Abstract
This study aims to investigate the synergistic effects of graphene, aluminum oxide (Al2O3), and silicon oxide (SiO2) nanofillers on the mechanical and thermal properties of epoxy composites. The objectives were to enhance the performance of epoxy resins by incorporating these nanofillers at varying weight fractions (0.5 %, 1 %, and 1.5 %) using ultrasonication for uniform dispersion. Standard ASTM tests, including tensile, flexural, and impact strength tests, along with thermal conductivity measurements, were conducted to evaluate the properties of the nanocomposites. The results revealed that graphene-reinforced composites exhibited the most significant improvements, with tensile strength increasing by 32 %, flexural strength by 21 %, and thermal conductivity by over 300 % compared to neat epoxy. Alumina and silica also enhanced the composite properties but to a lesser extent. Scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR) analyses showed key differences in the dispersion of nanoparticles and the interactions between the nanofillers and the epoxy matrix, with graphene demonstrating superior interfacial bonding. These findings highlight graphene’s exceptional potential for enhancing the mechanical and thermal properties of epoxy composites, making them suitable for applications in thermal management and structural components in advanced engineering fields. The study provides valuable insights into optimizing nanocomposite formulations to achieve multifunctional performance.
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Research ethics: Not applicable.
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Informed consent: Informed consent was obtained from all subjects involved in the study.
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Author contributions: Vijendra Rajendra Chaudhari: conceptualization, methodology, investigation, data curation, writing original draft; R.S.N. Sahai: review & editing. The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interests: The authors declare no competing interests.
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Research funding: Not applicable.
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Data availability: Data supporting the research of this study are available from the corresponding author upon reasonable request.
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© 2025 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Material Properties
- Polymer electrolytes for enhanced mechanical integrity in lithium-ion batteries: a review of recent progress and future directions
- Enhancement of some mechanical and thermal properties of epoxy nanocomposites via hybrid nanofiller reinforcement: graphene, alumina, and silica
- Preparation and Assembly
- Preparation and performance of hydrophilic PES blend membranes modified by Pluronic F127 and tannic acid based on RTIPS
- Fabrication and characterization of boron doped carbon dots@chitosan/polyvinyl alcohol hydrogels for methylene blue adsorption
- Sodium-alginate/poly (acrylamide co-acrylic acid) semi-interpenetrating hydrogels for removal of heavy metals from aqueous solutions
- Engineering and Processing
- Optimization of pullulan fiber processing parameters via the Forcespinning method
- Comparing pretraining methods with different fidelities for a 2D cooling problem in injection molding
Artikel in diesem Heft
- Frontmatter
- Material Properties
- Polymer electrolytes for enhanced mechanical integrity in lithium-ion batteries: a review of recent progress and future directions
- Enhancement of some mechanical and thermal properties of epoxy nanocomposites via hybrid nanofiller reinforcement: graphene, alumina, and silica
- Preparation and Assembly
- Preparation and performance of hydrophilic PES blend membranes modified by Pluronic F127 and tannic acid based on RTIPS
- Fabrication and characterization of boron doped carbon dots@chitosan/polyvinyl alcohol hydrogels for methylene blue adsorption
- Sodium-alginate/poly (acrylamide co-acrylic acid) semi-interpenetrating hydrogels for removal of heavy metals from aqueous solutions
- Engineering and Processing
- Optimization of pullulan fiber processing parameters via the Forcespinning method
- Comparing pretraining methods with different fidelities for a 2D cooling problem in injection molding