Imaging-based intelligent spectrometer on a plasmonic rainbow chip

Dylan Tua; Ruiying Liu; Wenhong Yang; Lyu Zhou; Haomin Song; Leslie Ying; Qiaoqiang Gan

doi:10.1038/s41467-023-37628-0

Nature Communications (Apr 2023)

Imaging-based intelligent spectrometer on a plasmonic rainbow chip

Dylan Tua,
Ruiying Liu,
Wenhong Yang,
Lyu Zhou,
Haomin Song,
Leslie Ying,
Qiaoqiang Gan

Affiliations

Dylan Tua: Electrical Engineering, University at Buffalo, The State University of New York
Ruiying Liu: Electrical Engineering, University at Buffalo, The State University of New York
Wenhong Yang: Material Science Engineering, Physical Science Engineering Division, King Abdullah University of Science and Technology
Lyu Zhou: Electrical Engineering, University at Buffalo, The State University of New York
Haomin Song: Material Science Engineering, Physical Science Engineering Division, King Abdullah University of Science and Technology
Leslie Ying: Electrical Engineering, University at Buffalo, The State University of New York
Qiaoqiang Gan: Electrical Engineering, University at Buffalo, The State University of New York

DOI: https://doi.org/10.1038/s41467-023-37628-0
Journal volume & issue: Vol. 14, no. 1
pp. 1 – 9

Abstract

Read online

The authors develop an imaging-based intelligent spectrometer on a plasmonic “rainbow” chip. It can accurately and precisely determine the spectroscopic and polarimetric information of the illumination spectrum using a single image assisted by suitably trained deep learning algorithms.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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