journal article·2026-01-27Open access

Multi-functional log-periodic graphene antennas for ultra-wideband systems

V. Govindaraj, C. Ramesh, S. Dhanasekar, Binay Kumar Pandey, Digvijay Pandey, Mesfin Esayas Lelisho

Discover Nano· Volume 21· Issue 1

Abstract

Abstract Ultra-wideband (UWB) technology has garnered significant interest from researchers worldwide. Reducing antenna size, guaranteeing radiation stability, attaining impedance matching, and keeping costs down are recent challenges.The adaptability, compactness, and wideband performance of log-periodic sawtooth planar antennas for UWB applications show great potential. There is much potential for improvement, especially in high-gain and multi-band settings, as indicated by the current research and advancements in resonator structures, reconfigurability, and meta surface designs. These advancements guarantee that log-periodic architectures will remain relevant and it targets wideband sub-GHz applications that complement 5G networks, including control, broadcast, and backward-compatibility services. A toothed log-periodic antenna based on graphene is proposed in this study to operate in the 0.1–1.3 GHz frequency range. In proposed method by varying the DC voltage applied to the graphene, the antenna’s bandwidth, radiation pattern, and operating frequency range is dynamically adjusted. The graphene’s chemical potential, surface conductivity, and surface impedance, this voltage control makes it possible to create a reconfigurable antenna design is adjusted. A log-periodic graphene lattice coupled to a 50-ohm feed line makes up the antenna’s radiating element. Simulation and implementation results demonstrate that the antenna generates stable, directional radiation patterns over a wide frequency range from 0.1 to 1.3 GHz when the chemical potential of graphene is set to 1 eV.
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Research context

OpenAlex topics: Antenna Design and Analysis · Graphene and Nanomaterials Applications · Graphene research and applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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