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The intrinsic dielectric properties of Mediterranean bio-composites

  • Faris M. AL-Oqla ORCID logo EMAIL logo and Nashat Nawafleh ORCID logo
Published/Copyright: November 25, 2024
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Abstract

The environment is seriously threatened by the growing use and disposal of technological products since most of them include non-biodegradable components. One approach to reduce environmental impact of electronic devices is to use biodegradable electronic components derived from natural fibers like protein and cellulose. Actually, a lot of research has been done on the viability of producing electronic components out of materials obtained from natural fibers. Their inclusion of several changeable functional categories is another benefit. Dielectric materials are one of the several necessary and commonplace parts of technical devices. A thorough study on the varieties of natural fibers used to make dielectric materials and their electrical properties would be beneficial in selecting the appropriate fibers and conditions for certain applications. To make full use of new natural composite materials in growing sectors, their electric properties have to be examined. However, along with polypropylene, four different kinds of natural lignocellulosic fibers will be discussed in this work: black pepper, sumac, pomegranate, and lemon – as case studies. In specific, over a frequency range of 1 KHz to 4 MH, the AC conductivity and dielectric constant of the produced samples were measured using the method of parallel plate capacitors. After that, given the performance of sisal fibers, a comparison between them and a sisal natural fiber (a non-Mediterranean variety) will be made.


Corresponding author: Faris M. AL-Oqla, Department of Mechanical Engineering, Faculty of Engineering, The Hashemite University, P.O Box 330127, Zarqa 13133, Jordan, E-mail:

Acknowledgments

The authors would like to thank the editors for their guidance and review of this article before its publication.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2024-08-04
Accepted: 2024-10-08
Published Online: 2024-11-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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