Publication Cover
Plastics, Rubber and Composites
Macromolecular Engineering
Volume 50, 2021 - Issue 2
283
Views
9
CrossRef citations to date
0
Altmetric
Research Articles

X-band radar-absorbing structures based on MWCNTs/NiZn ferrite nanocomposites

, , &
Pages 71-82 | Received 18 Mar 2020, Accepted 08 Oct 2020, Published online: 27 Oct 2020
 

ABSTRACT

Microwave absorbers present a wide range of applications in radar and telecommunications. To improve the microwave absorption characteristics of radar-absorbing structures (RASs), magnetic and dielectric materials are blended in different proportions because the impedance mismatch of dielectric materials, resulting from poor permeability, can be eliminated by a combination with magnetic loss fillers. Herein, E-glass/epoxy composites were prepared by blending multi-walled carbon nanotubes (MWCNTs) with Ni0.5Zn0.5Fe2O4 (NZF) nanopowder to enhance the composites’ microwave absorption. Nanocomposite laminates with different filler contents were fabricated by a simple and low-cost process of in situ polymerisation. The dielectric characteristics were estimated in the X-band, and possible loss mechanisms were studied. A two-layered RAS exhibited a reflection loss of −16 dB for a bandwidth of 2.2 GHz with a matching thickness of 3 mm. The resulting mechanical and thermal properties suggest that the proposed MWCNTs/NZF composite exhibiting good microwave absorption properties can be used in high-performance RASs.

Acknowledgements

We would like to thank Dr. Ch. Subrahmanyam, professor, Dr. K. Krushna Murthy, research associate, Department of Chemistry, IITH, and Dr.V.V.S.S.Srikanth, professor, SEST, UOH for providing fabrication and testing facilities at their institutes.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.