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Engineering >> 2022, Volume 17, Issue 10 doi: 10.1016/j.eng.2022.03.018

Super-Resolution Displacement Spectroscopic Sensing over a Surface “Rainbow”

a Department of Electrical Engineering, The State University of New York at Buffalo, Buffalo, NY 14260, USA
b Department of Biomedical Engineering, The State University of New York at Buffalo, Buffalo, NY 14260, USA
c Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA
d Material Science Engineering Program, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia

# These authors contributed equally to this work.

Received: 2021-10-05 Revised: 2022-02-03 Accepted: 2022-03-01 Available online: 2022-07-08

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Abstract

Subwavelength manipulation of light waves with high precision can enable new and exciting applications in spectroscopy, sensing, and medical imaging. For these applications, miniaturized spectrometers are desirable to enable the on-chip analysis of spectral information. In particular, for imaging-based spectroscopic sensing mechanisms, the key challenge is to determine the spatial-shift information accurately (i.e., the spatial displacement introduced by wavelength shift or biological or chemical surface binding), which is similar to the challenge presented by super-resolution imaging. Here, we report a unique “rainbow” trapping metasurface for on-chip spectrometers and sensors. Combined with super-resolution image processing, the low-setting 4× optical microscope system resolves a displacement of the resonant position within 35 nm on the plasmonic rainbow trapping metasurface with a tiny area as small as 0.002 mm2. This unique feature of the spatial manipulation of efficiently coupled rainbow plasmonic resonances reveals a new platform for miniaturized on-chip spectroscopic analysis with a spectral resolution of 0.032 nm in wavelength shift. Using this low-setting 4× microscope imaging system, we demonstrate a biosensing resolution of 1.92 × 109 exosomes per milliliter for A549-derived exosomes and distinguish between patient samples and healthy controls using exosomal epidermal growth factor receptor (EGFR) expression values, thereby demonstrating a new on-chip sensing system for personalized accurate bio/chemical sensing applications.

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