| Issue |
J. Eur. Opt. Society-Rapid Publ.
Volume 22, Number 1, 2026
|
|
|---|---|---|
| Article Number | 20 | |
| Number of page(s) | 12 | |
| DOI | https://doi.org/10.1051/jeos/2026018 | |
| Published online | 03 April 2026 | |
Research Article
Negative-refractive-index behavior in a periodic photonic metamaterial: unit-cell topology tailoring for broadband response
1
Department of Physics, Faculty of Sciences, Gazi University, Ankara, Türkiye
2
Department of Physics, Graduate School of Natural and Applied Sciences, Gazi University, Ankara, Türkiye
* Corresponding author. This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
21
January
2026
Accepted:
24
February
2026
Abstract
This paper examines how systematic control of unit-cell topology governs dispersion characteristics and bandwidth stability in configured periodic structures with numerical simulations. Distinct from the existing literature, the study targets a negative refractive index over a broad frequency range, while neural network–based optimization is used as a supporting tool to efficiently guide for bandwidth maximization. Comprehensive analysis is employed to optimize bandwidth effectively and validate the applicability of the resulting low-dispersion periodic structures. For the optimized unit cell, the third photonic band spans a wavelength range 1388–1631 nm (after model enhancement 1429–1578 nm) covering the S, C, and L optical communication bands, demonstrating broadband and stable dispersive behavior beyond a narrow resonance regime. The obtained results are thus expected to enhance the performance of negative-index based photonic components used in optical and photonic communication systems, compact antenna architectures, and advanced material engineering.
Key words: Metamaterials / Photonic crystals / Negative refractive index / Neural network / Machine learning
© The Author(s), published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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