Metamaterial absorbers have recently attracted a lot of interest for applications spanning from microwave to terahertz, near infrared and optical frequencies, such as electromagnetic compatibility, thermal emitters, solar cells and micro-bolometers. In this paper, a procedure for the efficient design of metamaterial absorbers based on parametric macromodels is presented. These models are used to describe the frequency-domain behaviour of complex systems as a function of frequency and design parameters (e.g., layout features). Parametric macromodels are very efficient and can be used to speed up the design flow in comparison with using electromagnetic simulators for design tasks. The use of quasi-random sequences for the sampling of the design space and of radial basis functions and polynomial functions for the model construction is proposed. Numerical results validate the efficiency and accuracy of the proposed technique for multiple optimizations.
Efficient design of metamaterial absorbers using parametric macromodels / Antonini, G.; Astorino, M. D.; Ferranti, F.; Frezza, F.; Tedeschi, N.. - In: APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL. - ISSN 1054-4887. - 33:(2018), pp. 772-780.
Efficient design of metamaterial absorbers using parametric macromodels
M. D. Astorino;F. Frezza;N. Tedeschi
2018
Abstract
Metamaterial absorbers have recently attracted a lot of interest for applications spanning from microwave to terahertz, near infrared and optical frequencies, such as electromagnetic compatibility, thermal emitters, solar cells and micro-bolometers. In this paper, a procedure for the efficient design of metamaterial absorbers based on parametric macromodels is presented. These models are used to describe the frequency-domain behaviour of complex systems as a function of frequency and design parameters (e.g., layout features). Parametric macromodels are very efficient and can be used to speed up the design flow in comparison with using electromagnetic simulators for design tasks. The use of quasi-random sequences for the sampling of the design space and of radial basis functions and polynomial functions for the model construction is proposed. Numerical results validate the efficiency and accuracy of the proposed technique for multiple optimizations.File | Dimensione | Formato | |
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