Poster + Paper
28 November 2023 Deep-learning based design and modeling for chiro-optical dielectric metasurfaces
Sadia Noureen, Hafiz Saad Khaliq, Muhammad Fizan, Muhammad Zubair, Muhammad Qasim Mehmood, Yehia Massoud
Author Affiliations +
Conference Poster
Abstract
Nanophotonics employ chiro-optical effects for a variety of applications, including advanced imaging and molecular detection and separation. Due to their outstanding qualities in light-matter interactions, planar metasurfaces comprised of subwavelength meta-atoms have attracted a lot of attention. Despite of the vast potential of metasurfaces, achievement of large chiro-optical effects compactly on-chip at the visible wavelengths is still hindered by its complex design and optimization procedure. Deep-learning (DL) based modelling techniques have been put out as an alternative to the time-consuming and computationally demanding traditional design and optimization procedure of metasurfaces during the past few years. In this work, we have employed deep-learning based forward and inverse models to design and optimize achiral nano-fins to achieve giant chiro-optical affects at the visible wavelengths. A regression based forward neural network is proposed, that takes all the structural dimensions of the achiral nano-fins as input and trained separately to predict three different types of asymmetric transmissions i.e., TLL, TLR and TRL and circular dichroism. An inverse design model is also demonstrated that simultaneously considers all the three target transmissions and optimizes the dimensions of the achiral nano-fins in such a way that they experience constructive and destructive interference, resulting in an average circular dichroism of more than 60% and 70% asymmetric transmission. With potential applications in chiral polarizers for optical displays, flat integrated polarization shifter’s exhibiting high efficiency, chiral-metasurface sensors and chiral beam splitters, the suggested DL-enabled design techniques ease the realization of op-chip giant chiro-optical response through planar metasurface.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Sadia Noureen, Hafiz Saad Khaliq, Muhammad Fizan, Muhammad Zubair, Muhammad Qasim Mehmood, and Yehia Massoud "Deep-learning based design and modeling for chiro-optical dielectric metasurfaces", Proc. SPIE 12773, Nanophotonics and Micro/Nano Optics IX, 127731F (28 November 2023); https://doi.org/10.1117/12.2685855
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KEYWORDS
Design and modelling

Modeling

Dielectrics

Mathematical optimization

Dichroic materials

Optical transmission

Nanophotonics

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