Finite element analysis of particle weight fraction & size effects in graphene-silicon carbide reinforced aluminium nanocomposites

This work has great potential for enhancing the mechanical performance of nanostructured lightweight materials. It uses the finite element method (FEM) to investigate the effects of variation in silicon carbide (SiC) particle size on the elastic modulus, yield strength, and hardness of graphene–SiC reinforced aluminium hybrid nanocomposites (GSANs). The present study examines the SiC weight percentage (0, 2, 4 and 8%) and particle size (nanoparticle lengths of l = 60, 80, and 100 nm at a fixed d=80 nm) effects on the mechanical behaviour of the GSANs. Results indicate that the addition of SiC increases the elastic modulus from approximately 70 GPa to 80 GPa and improves the ultimate tensile strength from about 220 MPa to nearly 310 MPa compared with the base aluminium matrix. 2 wt% SiC + 1 wt% GNP is the practical optimum, offering an effective compromise. With a constant 2 wt% SiC, the yield strength and hardness of the composites have again enhanced by ∼15–20% when reducing the particle size from 100 nm to 60 nm, owing to their higher interfacial area density and decreased interparticle spacing, which promotes load transfer. These results indicate that both the SiC amount and size have a crucial effect on the mechanical properties, whereas hybrid reinforcement with GNPs enables the maximum synergy between strength and ductility. The findings are useful to tailor GSANs for aerospace, automobile and structural purposes.

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Publication Details

Journal
Next Nanotechnology
Published
2026-03-31
DOI
https://doi.org/10.1016/j.nxnano.2026.100445
Primary Topic
Aluminum Alloys Composites Properties
Type
article
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article

Finite element analysis of particle weight fraction & size effects in graphene-silicon carbide reinforced aluminium nanocomposites

Mamta Dahiya, Virat Khanna, Sandeep Bansal, Mayank Choubey
Next Nanotechnology
Aluminum Alloys Composites Properties
article

Finite element analysis of particle weight fraction & size effects in graphene-silicon carbide reinforced aluminium nanocomposites

Mamta Dahiya, Virat Khanna, Sandeep Bansal, Mayank Choubey
article en

Abstract

This work has great potential for enhancing the mechanical performance of nanostructured lightweight materials. It uses the finite element method (FEM) to investigate the effects of variation in silicon carbide (SiC) particle size on the elastic modulus, yield strength, and hardness of graphene–SiC reinforced aluminium hybrid nanocomposites (GSANs). The present study examines the SiC weight percentage (0, 2, 4 and 8%) and particle size (nanoparticle lengths of l = 60, 80, and 100 nm at a fixed d=80 nm) effects on the mechanical behaviour of the GSANs. Results indicate that the addition of SiC increases the elastic modulus from approximately 70 GPa to 80 GPa and improves the ultimate tensile strength from about 220 MPa to nearly 310 MPa compared with the base aluminium matrix. 2 wt% SiC + 1 wt% GNP is the practical optimum, offering an effective compromise. With a constant 2 wt% SiC, the yield strength and hardness of the composites have again enhanced by ∼15–20% when reducing the particle size from 100 nm to 60 nm, owing to their higher interfacial area density and decreased interparticle spacing, which promotes load transfer. These results indicate that both the SiC amount and size have a crucial effect on the mechanical properties, whereas hybrid reinforcement with GNPs enables the maximum synergy between strength and ductility. The findings are useful to tailor GSANs for aerospace, automobile and structural purposes.

Next NanotechnologyVol. 9
Chandigarh University (IN), Manav Bharti University (IN), Shree Guru Gobind Singh Tricentenary University (IN)
Openalex Percentile: Top 27%
Aluminum Alloys Composites Properties
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Finite element analysis of particle weight fraction & size effects in graphene-silicon carbide reinforced aluminium nanocomposites — Mamta Dahiya, Virat Khanna, et al. · Next Nanotechnology (2026) | TGRS Research Map | TGRS