Optimizing mechanical performance: Epoxy-graphene oxide nanocomposites for enhanced strength in lattice structure
The potential of epoxy-graphene oxide (GO) nanocomposites to improve the mechanical characteristics of conventional epoxy resins is causing them to gain prominence. This makes them appropriate for advanced engineering applications, including structural materials, automotive, and aerospace. This stud...
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Veröffentlicht in: | Heliyon 2025-01, Vol.11 (2), p.e41576, Article e41576 |
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Sprache: | eng |
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Zusammenfassung: | The potential of epoxy-graphene oxide (GO) nanocomposites to improve the mechanical characteristics of conventional epoxy resins is causing them to gain prominence. This makes them appropriate for advanced engineering applications, including structural materials, automotive, and aerospace. This study aimed to develop an epoxy/GO composite with improved mechanical properties through synthesizing epoxy/GO samples with varying GO content (from 0.1 to 0.5 wt%), oxidation degree (from 3 to 9 g), and homogenization time (from 90 to 150 min). To do so, nine epoxy/GO composites were synthesis based on Taguchi method of experiment design (L9 (33) orthogonal array) followed by conducting tensile strength tests. Using Taguchi method, optimal values of 0.25 wt%, 6 g, and 150 min were determined for GO content, oxidation degree, and homogenization time, respectively. Compared to tensile strength of the pure epoxy (about 38 MPa), the superior tensile strength of 73 MPa obtained for the optimal composite showcased an impressive 92 % improvement. Additionally, analysis of variance indicated the predominant role of GO's content than other parameters in improving the epoxy/GO composite's tensile strength. Finally, non-linear regression analysis was applied to develop a semi-empirical quadratic model for predicting the composite's tensile strength. The R2 value of 99.55 % as well as a negligible AARD of 1.13 % in the optimal condition, implied the highest accuracy of developed model inside the design space. |
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ISSN: | 2405-8440 2405-8440 |
DOI: | 10.1016/j.heliyon.2024.e41576 |