Electromagnetic and microwave absorption properties of MWCNTs based polymer nanocomposites

材料科学 复合材料 介电损耗 微波食品加热 反射损耗 纳米复合材料 碳纳米管 耗散因子 电介质 复合数 介电常数 光电子学 量子力学 物理
作者
G. Satish,Aditya Kolakoti
出处
期刊:World Journal of Engineering [Emerald Publishing Limited]
卷期号:18 (6): 817-825 被引量:5
标识
DOI:10.1108/wje-11-2020-0589
摘要

Purpose The purpose of the present work is to fabricate composite with strong absorbing nature and with more strength. The usage of wireless communication is increasing day by day, electromagnetic absorbing material is required to reduce this pollution. In the present experimental investigation, composites were fabricated for zero and 45° fiber orientation and as a filler material of Multiwall Carbon Nanotubes (MWCNTs) for the proposed percentage in the composites. Microwave absorbing properties were investigated for both perfect electric conductor (PEC)-backed composites and without PEC-backed composites. Design/methodology/approach The electromagnetic absorbing performance was analyzed based on complex permeability, complex permittivity, dielectric tangent and magnetic tangent losses. The experimentation was done by Vector Network Analyzer in the frequency range of 8.2 to 12.4 GHz by X-band. The surface morphological study was done. The mechanical and thermal properties are also investigated for these composites. Findings By investigating the experimental values, the induced percentage of MWCNTs and PEC of composites affects the electromagnetic and microwave absorption properties of the composites. The microwave absorption properties improved when the composites were able to absorb wide bandwidth and low reflection loss. The best results are obtained for PEC-backed composites for 5%, which is about −43.56 dB at 11.1 GHz compared to without PEC-backed composites. The reflection loss is developed by the dielectric loss initiated from MWCNTs and by PEC. Originality/value To the best of the authors’ knowledge, no work was reported on hand lay-up method and PEC-backed composites in electromagnetic absorption properties with regression analysis.

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