Optimization by a genetic algorithm of nanopyramidal broadband quasi-perfect absorbers with deeper insight into the stability of optimal solutions

Alexandre Mayer; Olivier Deparis; Michaël Lobet

doi:10.1117/12.3012796

18 June 2024 Optimization by a genetic algorithm of nanopyramidal broadband quasi-perfect absorbers with deeper insight into the stability of optimal solutions

Alexandre Mayer, Olivier Deparis, Michaël Lobet

Author Affiliations +

Proceedings Volume 13017, Machine Learning in Photonics; 1301707 (2024) https://doi.org/10.1117/12.3012796
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

We use a genetic algorithm to optimize periodic arrays of truncated square-based pyramids made of alternating stacks of metal/dielectric layers. The objective is to achieve broadband quasi-perfect absorption of normally incident radiations in the visible and near-infrared ranges (wavelengths comprised between 420 and 1600nm). We compare the results one can obtain by considering one, two or three stacks of (i) Ni, Ti, Al or Cu for the metal, and (ii) poly(methyl methacrylate) (PMMA) for the dielectric. The parameters to determine for each metal/dielectric combination are (i) the period of the system, (ii) the lateral dimensions of each stack of metal/dielectric layers and (iii) the width of each dielectric layer. The Rigorous CoupledWaves Analysis (RCWA) is used to compute the absorptance spectrum of these different structures. The Genetic Algorithm is used to find the geometrical parameters that maximize the integrated absorptance. This approach provides stability maps with respect to the geometrical parameters, which leads to additional physical insight regarding practical implementation. The study shows that Ni/PMMA and Ti/PMMA provide high-quality solutions associated with broad optima (stability with respect to variations of the geometrical parameters). On the contrary, Al/PMMA and Cu/PMMA provide poor-quality solutions associated with sharp optima. We find an interesting correlation between the robustness of the solutions found by the genetic algorithm (stability with respect to variations of the geometrical parameters) and the stability of these solutions with respect to the number of plane waves used in the RCWA calculations.

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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Alexandre Mayer, Olivier Deparis, and Michaël Lobet "Optimization by a genetic algorithm of nanopyramidal broadband quasi-perfect absorbers with deeper insight into the stability of optimal solutions", Proc. SPIE 13017, Machine Learning in Photonics, 1301707 (18 June 2024); https://doi.org/10.1117/12.3012796

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