2021
DOI: 10.1002/adom.202100695
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Rainbows at the End of Subwavelength Discontinuities: Plasmonic Light Trapping for Sensing Applications

Abstract: Surface plasmon polaritons (SPPs) which exist at the metal-dielectric interface are guided by the coupling of electromagnetic waves to oscillations in the electron gas plasma created at metal surfaces. Plasmonics, a subset of the field of nanophotonics pertaining to all things beyond the diffraction limit, has flourished and evolved significantly over the past decade offering practical utility to a variety of applications. [1] Notwithstanding the ohmic loss in metals and commensurate limited propagation length… Show more

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Cited by 12 publications
(13 citation statements)
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References 155 publications
(254 reference statements)
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“…Additionally, PEGylated phospholipids are excellent bilayer and liposome formulations for drug and vaccine delivery. Hence, the detection of DPPE-PEG is helpful for accurate prognoses and advancing therapeutic approaches 52 .…”
Section: Resultsmentioning
confidence: 99%
“…Additionally, PEGylated phospholipids are excellent bilayer and liposome formulations for drug and vaccine delivery. Hence, the detection of DPPE-PEG is helpful for accurate prognoses and advancing therapeutic approaches 52 .…”
Section: Resultsmentioning
confidence: 99%
“…Here we will first employ the rainbow trapping effect 28 31 to develop an on-chip spectrometer system (e.g., refs. 32 34 ). As proof of concept, Fig.…”
Section: Resultsmentioning
confidence: 99%
“…12 The amorphous NPs with a wide distribution of sizes offer broadband plasmonic field enhancement which allows for multiwavelength SERS characterization of serum samples at 532, 633, and 785 nm. This can help determine if: (1) ML accuracy depends on interrogation wavelength, which has not yet been evaluated, 11,[13][14][15]17,18,21 and (2) multiwavelength SERS can lead to a more accurate characterization in comparison to single-wavelength SERS 31 due to a wider range of vibrational modes and molecular resonances that can be extracted from the CVD biomarkers to provide the ML model with more learning inputs from each sample. At each SERS excitation wavelength, 12 spectra were collected on each serum sample at different points spaced 100 μm apart, which were averaged to produce one spectrum per sample at each wavelength.…”
Section: ■ Introductionmentioning
confidence: 99%