Back to Search
Start Over
Deep learning approach for inverse design of metasurfaces with a wider shape gamut.
- Source :
-
Optics letters [Opt Lett] 2022 May 15; Vol. 47 (10), pp. 2586-2589. - Publication Year :
- 2022
-
Abstract
- While the large design degrees of freedom (DOFs) give metasurfaces a tremendous versatility, they make the inverse design challenging. Metasurface designers mostly rely on simple shapes and ordered placements, which restricts the achievable performance. We report a deep learning based inverse design flow that enables a fuller exploitation of the meta-atom shape. Using a polygonal shape encoding that covers a broad gamut of lithographically realizable resonators, we demonstrate the inverse design of color filters in an amorphous silicon material platform. The inverse-designed transmission-mode color filter metasurfaces are experimentally realized and exhibit enhancement in the color gamut.
Details
- Language :
- English
- ISSN :
- 1539-4794
- Volume :
- 47
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- Optics letters
- Publication Type :
- Academic Journal
- Accession number :
- 35561407
- Full Text :
- https://doi.org/10.1364/OL.458746