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

Waqas W. Ahmed; Haicheng Cao; Changqing Xu; Mohamed Farhat; Muhammad Amin; Xiaohang Li; Xiangliang Zhang; Ying Wu

doi:10.1038/s41377-024-01723-8

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

Original Articles

- Machine learning assisted plasmonic metascreen for enhanced broadband absorption in ultra-thin silicon films
- Light: Science & Applications Vol. 14, Issue 2, Pages: 411-421(2025)
- Affiliations：
  
  1.Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
  2.College of Engineering, Taibah University, Madinah 42353, Saudi Arabia
  3.Division of Physical Science and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
  4.Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
- Author bio：
  
  Xiangliang Zhang (xzhang33@nd.edu)
  Ying Wu (ying.wu@kaust.edu.sa)
- Funds：
- DOI：10.1038/s41377-024-01723-8
  CLC：
- Received：20 March 2024，
  
  Revised：04 November 2024，
  
  Accepted：2024-12-16，
  
  Published Online：09 January 2025，
  
  Published：28 February 2025
- Accepted：
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Ahmed, W. W. et al. Machine learning assisted plasmonic metascreen for enhanced broadband absorption in ultra-thin silicon films. Light: Science & Applications, 14, 411-421 (2025).
DOI：

Ahmed, W. W. et al. Machine learning assisted plasmonic metascreen for enhanced broadband absorption in ultra-thin silicon films. Light: Science & Applications, 14, 411-421 (2025). DOI： 10.1038/s41377-024-01723-8.

摘要

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 enhancement of light absorption. This enhancement arises from the interaction between the resonant cavity modes and localized plasmonic modes

requiring precise tuning of plasmon resonances to match the absorption region of the silicon active layer. To facilitate the device design and improve light absorption without increasing the thickness of the active layer

we develop a deep learning framework

which learns to map from the absorption spectra to the design space. This inverse design strategy helps to tune the absorption for selective spectral functionalities. Our optimized design surpasses the bare silicon planar device

exhibiting a remarkable enhancement of over 100%. Experimental validation confirms the broadband enhancement of light absorption in the proposed configuration. The proposed metascreen absorber holds great potential for light harvesting applications and may be leveraged to improve the light conversion efficiency of ultra-thin silicon solar cells

photodetectors

and optical filters.

关键词

Keywords

references

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