Investigation of thermal conductivity of Prosopis juliflora / Acacia leucophloea / Acacia nilotica fibers / ceramic fillers / epoxy composites
Growing economic awareness and rising prices of synthetic fibers have increased the need for natural fibres. In recent years, an expanding number of publications reflects the growing significance of natural fiber-reinforced composites. Investigating the thermal behaviours of these fibers is crucial...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025003111 |
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| Summary: | Growing economic awareness and rising prices of synthetic fibers have increased the need for natural fibres. In recent years, an expanding number of publications reflects the growing significance of natural fiber-reinforced composites. Investigating the thermal behaviours of these fibers is crucial to using them effectively. The novelty of this study lies in influencing the underutilised biobased fibres like Acacia leucophloea (AL), Prosopis juliflora (PJ) and Acacia nilotica (AN) with varying fibre quantities, and ceramic filler hexagonal Boron Nitride (h-BN), Aluminium Oxide (Al2O3) and Silicon Carbide (SiC) to estimate the thermal conductivity of epoxy composites. Samples are fabricated by the Hand layup method varying the fiber quantity and different fillers at 1 wt.%. The prepared samples are tested for thermal conductivity and the optimisation of parameters is scrutinized using the Box–Behnken Design (BBD). ANOVA via Minitab is used to develop regression correlation and for optimization respectively. The chosen natural fiber Prosopis juliflora of (6 wt.%) gains a prominent thermal conductivity (1.52 W/m K) with a filler boron nitride (1 %). SEM image shows the surface morphology of the composite with fibre and matrix bonding that enhances thermal conductivity. A study using the RSM is carried out to obtain the optimum values for these parameters. The statistical findings are obtained using ANOVA from analysing the BBD data. This research contributes to sustainable materials for applications in electrical components such as socket pins and switchboards. |
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| ISSN: | 2590-1230 |