Imaging-based intelligent spectrometer on a plasmonic rainbow chip

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

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: Abstract Compact, lightweight, and on-chip spectrometers are required to develop portable and handheld sensing and analysis applications. However, the performance of these miniaturized systems is usually much lower than their benchtop laboratory counterparts due to oversimplified optical architectures. Here, we develop a compact plasmonic “rainbow” chip for rapid, accurate dual-functional spectroscopic sensing that can surpass conventional portable spectrometers under selected conditions. The nanostructure consists of one-dimensional or two-dimensional graded metallic gratings. By using a single image obtained by an ordinary camera, this compact system can accurately and precisely determine the spectroscopic and polarimetric information of the illumination spectrum. Assisted by suitably trained deep learning algorithms, we demonstrate the characterization of optical rotatory dispersion of glucose solutions at two-peak and three-peak narrowband illumination across the visible spectrum using just a single image. This system holds the potential for integration with smartphones and lab-on-a-chip systems to develop applications for in situ analysis.

Date: 2023
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DOI: 10.1038/s41467-023-37628-0

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