Mechanical properties evaluation on hybrid AA6026 composites added with nanoclay and carbon fibers

서지정보

ㆍ발행기관 : 한국탄소학회 ㆍ수록지정보 : Carbon letters / 33권 / 3호
ㆍ저자명 : Pon Azhagiri, N. Senthilkumar, K. Palanikumar, B. Deepanraj

목차

Mechanical properties evaluation on hybrid AA6026 composites added with nanoclay and carbon fibers
Abstract
1 Introduction
2 Materials and methods
3 Results and discussion
3.1 Metallography depiction of HANCs
4 Conclusions
References

영어 초록

With a strive to develop light-weight material for automotive and aerospace applications, aluminum-based hybrid nanocomposites (AHNCs) were manufactured utilizing the compocasting approach in this study. Chopped carbon fibers (CFs) are reinforced along with different weight fractions of nanoclay (1–5%) in the matrix of AA6026 forming AHNCs. The AHNCs specimens were examined by microstructural analysis, mechanical characterization, fatigue, and corrosion strength as per ASTM guidelines. Electroless plating method is adopted for coating CFs with copper to improve the wettability with matrix. SEM pictures of manufactured composites reveal thin inter-dendritic aluminum grains with precipitate particle of eutectic at intergranular junctions, as well as nanoclay particles that have precipitated in the matrix. Tensile strength (TS) rises with inclusion of nanoclay up to a maximum of 212.46 MPa for 3% nanoclay reinforcement, after which the TS is reduced due to non-homogeneity in distribution, agglomeration and de-bonding of nanoparticles. Similarly, micro-hardness increases with addition of 3% nanoclay after which it decreases. Higher energy absorption was achieved with 3% nanoclay reinforced hybrid and a significant improvement in flexural strength was obtained. With addition of both CFs and nanoclay, the fatigue strength of the hybrid composite tends to increase due to flexible CFs and high surface area nanoclays which strengthen the grain boundaries until 3% addition. Addition of nanoclay lowers the corrosion rate with nanoclays filling the crevices and voids in the matrix.

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