Deep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface

Metasurfaces analogues of Fano resonances provide a powerful platform for high sensitivity sensing, nonlinear optics, and light manipulation. However, previous Fano-resonant metasurfaces usually are not compatible with silicon complementary metal-oxide semiconductor circuits due to their hybrid mate...

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Autores principales:	Zan Hui Chen, Weicheng Chen, Zhenzhou Cheng, Guo-Wei Lu, Jiaqi Wang
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2022
Materias:	Neural networks refractive index sensing metamaterials silicon-on-insulator Applied optics. Photonics TA1501-1820 Optics. Light QC350-467
Acceso en línea:	https://doaj.org/article/caf2f1d9ca1f46948a61a951f078d728
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spelling	oai:doaj.org-article:caf2f1d9ca1f46948a61a951f078d7282021-12-01T00:00:11ZDeep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface1943-065510.1109/JPHOT.2021.3127220https://doaj.org/article/caf2f1d9ca1f46948a61a951f078d7282022-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9612031/https://doaj.org/toc/1943-0655Metasurfaces analogues of Fano resonances provide a powerful platform for high sensitivity sensing, nonlinear optics, and light manipulation. However, previous Fano-resonant metasurfaces usually are not compatible with silicon complementary metal-oxide semiconductor circuits due to their hybrid material structures and large non-radiative loss. Herein, we theoretically demonstrate a silicon-on-insulator metasurface (SOIM) enhancing Fano resonances by using a tandem neural network design. Multiple Fano resonances with high Q-factor have been observed in the symmetry-breaking SOIM. The Fano-resonant mechanism of the SOIM is analyzed. Additionally, the spectral features of the Fano-resonant SOIM as a function of the symmetry tuning factor of the double silicon nanobars and the environment refractive index are also investigated. The result shows that the Fano-resonant SOIM as a methanol sensor with a sensitivity of 310 nm/RIU can achieve an overall figure of merit of 195 in the near-infrared spectral regime. The designed Fano-resonant SOIM shows enormous potential applications in highly sensitive sensors and light-matter interaction enhancement.Zan Hui ChenWeicheng ChenZhenzhou ChengGuo-Wei LuJiaqi WangIEEEarticleNeural networksrefractive index sensingmetamaterialssilicon-on-insulatorApplied optics. PhotonicsTA1501-1820Optics. LightQC350-467ENIEEE Photonics Journal, Vol 14, Iss 1, Pp 1-7 (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	Neural networks refractive index sensing metamaterials silicon-on-insulator Applied optics. Photonics TA1501-1820 Optics. Light QC350-467
spellingShingle	Neural networks refractive index sensing metamaterials silicon-on-insulator Applied optics. Photonics TA1501-1820 Optics. Light QC350-467 Zan Hui Chen Weicheng Chen Zhenzhou Cheng Guo-Wei Lu Jiaqi Wang Deep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface
description	Metasurfaces analogues of Fano resonances provide a powerful platform for high sensitivity sensing, nonlinear optics, and light manipulation. However, previous Fano-resonant metasurfaces usually are not compatible with silicon complementary metal-oxide semiconductor circuits due to their hybrid material structures and large non-radiative loss. Herein, we theoretically demonstrate a silicon-on-insulator metasurface (SOIM) enhancing Fano resonances by using a tandem neural network design. Multiple Fano resonances with high Q-factor have been observed in the symmetry-breaking SOIM. The Fano-resonant mechanism of the SOIM is analyzed. Additionally, the spectral features of the Fano-resonant SOIM as a function of the symmetry tuning factor of the double silicon nanobars and the environment refractive index are also investigated. The result shows that the Fano-resonant SOIM as a methanol sensor with a sensitivity of 310 nm/RIU can achieve an overall figure of merit of 195 in the near-infrared spectral regime. The designed Fano-resonant SOIM shows enormous potential applications in highly sensitive sensors and light-matter interaction enhancement.
format	article
author	Zan Hui Chen Weicheng Chen Zhenzhou Cheng Guo-Wei Lu Jiaqi Wang
author_facet	Zan Hui Chen Weicheng Chen Zhenzhou Cheng Guo-Wei Lu Jiaqi Wang
author_sort	Zan Hui Chen
title	Deep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface
title_short	Deep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface
title_full	Deep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface
title_fullStr	Deep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface
title_full_unstemmed	Deep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface
title_sort	deep learning-assisted enhanced fano resonances in symmetry-breaking soi metasurface
publisher	IEEE
publishDate	2022
url	https://doaj.org/article/caf2f1d9ca1f46948a61a951f078d728
work_keys_str_mv	AT zanhuichen deeplearningassistedenhancedfanoresonancesinsymmetrybreakingsoimetasurface AT weichengchen deeplearningassistedenhancedfanoresonancesinsymmetrybreakingsoimetasurface AT zhenzhoucheng deeplearningassistedenhancedfanoresonancesinsymmetrybreakingsoimetasurface AT guoweilu deeplearningassistedenhancedfanoresonancesinsymmetrybreakingsoimetasurface AT jiaqiwang deeplearningassistedenhancedfanoresonancesinsymmetrybreakingsoimetasurface
_version_	1718406228056473600

Deep Learning-Assisted Enhanced Fano Resonances in Symmetry-Breaking SOI Metasurface

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