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A dynamically tunable polarization-insensitive broadband vanadium dioxide-assisted absorber for terahertz applications

  • Mahesh Valathuru , Pokkunuri Pardhasaradhi ORCID logo EMAIL logo , Boddapati Taraka Phani Madhav ORCID logo and Prasad Nagandla
Published/Copyright: April 29, 2025

Abstract

Research into tunable broadband absorbers has recently grown in popularity due to the terahertz technology’s spectacular development. This article proposes and analyzes a metamaterial structure based on vanadium dioxide (VO2) that can be used as a broadband terahertz absorber, which is tuned dynamically. The upper layer of the absorber is made of VO2, the ground is composed of gold, and middle dielectric substrate is made of polyimide. The prescribed design provides more than 95 % of absorption with 4 THz bandwidth from 3.3 to 7.3 THz. Moreover, absorption peak intensity can be constantly enhanced from 5 % to 97 % when the VO2’s conductivity varies from 200 to 2 × 105 S/m. This transition enables dynamic control between high absorption and high reflection states. This research endeavours to thoroughly investigate VO2-based THz Metamaterial Absorber (MMA), encompassing all aspects of the design validation and modelling using an electronic equivalent lumped design. The conductive phenomena of VO2 radiating patch to achieve a high percentage absorption for the relevant absorption frequency band is very useful to understand. Additionally, it has been verified that the polarization angle has no effect on the absorptance. The prescribed absorber has potential applications including terahertz imaging, sensing, detection, electromagnetic cloaking, and optoelectronic switches.


Corresponding author: Pokkunuri Pardhasaradhi, ALRC Research Centre, Department of ECE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India, E-mail: 

Acknowledgments

Koneru Lakshmaiah Education Foundation.

  1. Research ethics: This research did not involve human participants, animals, or biological samples, and therefore did not require ethical approval.

  2. Informed consent: Not applicable. No human subjects or personal data were used in this study.

  3. Author contributions: Mahesh Valathuru: Conceptualization, Simulation, and Manuscript Drafting. Pokkunuri Pardhasaradhi: Methodology, Validation, and Manuscript Review. Boddapati Taraka Phani Madhav: Supervision, Resources, and Technical Guidance. Nagandla Prasad: Data Analysis and Final Review.

  4. Use of Large Language Models, AI and Machine Learning Tools: The authors did not use large language models, AI, or machine learning to generate or edit the manuscript content. All work was conducted and written by the authors.

  5. Conflict of interest: The authors declare that they have no conflict of interest related to this work.

  6. Research funding: This research received no specific grant from any funding agency.

  7. Data availability: All relevant data analyzed during this study are included in the manuscript. Additional supporting data can be made available upon reasonable request from the corresponding author.

  8. Trial registration: Not applicable.

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Received: 2025-02-12
Accepted: 2025-04-10
Published Online: 2025-04-29
Published in Print: 2025-06-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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