| Autor: |
Ueno Akira, Lin Hung-I, Yang Fan, An Sensong, Martin-Monier Louis, Shalaginov Mikhail Y., Gu Tian, Hu Juejun |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Nanophotonics, Vol 12, Iss 17, Pp 3491-3499 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2192-8614 |
| DOI: |
10.1515/nanoph-2023-0329 |
| Popis: |
Metasurfaces, which consist of arrays of ultrathin planar nanostructures (also known as “meta-atoms”), offer immense potential for use in high-performance optical devices through the precise manipulation of electromagnetic waves with subwavelength spatial resolution. However, designing meta-atom structures that simultaneously meet multiple functional requirements (e.g., for multiband or multiangle operation) is an arduous task that poses a significant design burden. Therefore, it is essential to establish a robust method for producing intricate meta-atom structures as functional devices. To address this issue, we developed a rapid construction method for a multifunctional and fabrication-friendly meta-atom library using deep neural networks coupled with a meta-atom selector that accounts for realistic fabrication constraints. To validate the proposed method, we successfully applied the approach to experimentally demonstrate a dual-band metasurface collimator based on complex free-form meta-atoms. Our results qualify the proposed method as an efficient and reliable solution for designing complex meta-atom structures in high-performance optical device implementations. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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