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

Lyu Zhou, Nan Zhang, Chang Chieh Hsu, Matthew Singer, Xie Zeng, Yizheng Li, Haomin Song, Josep Jornet, Yun Wu, Qiaoqiang Gan

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.
Original languageEnglish (US)
JournalEngineering
DOIs
StatePublished - Jul 8 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-09-30
Acknowledgements: This work was partially supported by the National Science Foundation (ECCS-1807463 and PFI-1718177) and UB Blue Sky program. We appreciate Mr. Dylan Tua for helpful discussion on technical details. The authors also acknowledge funding support from National Cancer Institute (NCI) of the National Institutes of Health (NIH) (R21CA235305). Deidentified human serum samples and their clinical data for this study were provided by the Data Bank and BioRepository (DBBR), which is funded by NCI (P30CA16056) and is a Roswell Park Cancer Institute Cancer Center Support Grant shared resource. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH. The authors thank the support from National Science Foundation (CBET-1337860), which funds the nanoparticle tracking analysis system (NanoSight, LM10, Malvern Instruments, Ltd.).

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