Machine learning assisted plasmonic metascreen for enhanced broadband absorption in ultra-thin silicon films

Machine learning assisted plasmonic metascreen for enhanced broadband absorption in ultra-thin silicon films

Abstract We propose and demonstrate a data-driven plasmonic metascreen that efficiently absorbs incident light over a wide spectral range in an ultra-thin silicon film. By embedding a double-nanoring silver array within a 20 nm ultrathin amorphous silicon (a-Si) layer, we achieve a significant enhan...

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Bibliographic Details
Main Authors: Waqas W. Ahmed, Haicheng Cao, Changqing Xu, Mohamed Farhat, Muhammad Amin, Xiaohang Li, Xiangliang Zhang, Ying Wu
Format: Article
Language:English
Published: Nature Publishing Group 2025-01-01
Series:Light: Science & Applications
Online Access:https://doi.org/10.1038/s41377-024-01723-8

Internet

https://doi.org/10.1038/s41377-024-01723-8

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