Abstract
We propose an efficient and versatile optimization scheme, based on the combination of multi-objective genetic algorithms and neural-networks, to reproduce specific colors through the optimization of the geometrical parameters of metal-dielectric diffraction gratings. To illustrate and assess the performance of this approach, we tailor the chromatic response of a structure composed of three adjacent hybrid V-groove diffraction gratings. To be close to the experimental situation, we include the feasibility constraints imposed by the fabrication process. The strength of our approach lies in the possibility to simultaneously optimize different contradictory objectives, avoiding time-consuming electromagnetic calculations.
Highlights
The generation of structural colors using metallic, dielectric or hybrid nanostructures is currently the subject of a significant amount of research works [1,2,3]
Since several iterations are needed to search for the optimal solutions, one strategy proposed to avoid time-consuming electromagnetic calculations is to replace them with approximations based on meta-models
We found throughout our numerical simulations that the optimization algorithm, which was the Particle Swarm Optimization (PSO) [30] coupled with the meta-model presented earlier, converged to similar results
Summary
The generation of structural colors using metallic, dielectric or hybrid nanostructures is currently the subject of a significant amount of research works [1,2,3]. The chromatic response of the structures used for color generation is characterized through parametric studies based on the systematic variation of their different geometrical parameters This approach has proven successful, it can be very time consuming and does not necessarily provide the optimal solutions that best match the searched colors. In that case there is not a single optimal solution but multiple trade-off solutions among the searched objectives, making necessary to resort to more sophisticated strategies like multi-objective optimization This approach has been explored by Wiecha et al to design colour pixels based on silicon nano-structures [9] and by J.Jung to simultaneously improve the performance and robustness of a plasmonic wave-guide [10]. We make use of the meta-model to replace the time-consuming electromagnetic method, required to compute the spectral data related to the colors generated with the grating This contribution is organized as follows: In Sect.
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