Digital nanophotonic biosensing empowered by silicon Mie voids
Daniil Riabov, Abtin Saateh, Wenhong Yang, Ivan Sinev, Yuri Kivshar, and Hatice Altug

TL;DR
This paper introduces a scalable, silicon-based digital nanophotonic biosensor using Mie voids and deep learning for ultrasensitive detection of biomarkers at single-molecule levels.
Contribution
It presents a novel dielectric Mie void design combined with deep learning for highly sensitive, scalable, and low-cost digital biosensing of disease biomarkers.
Findings
Detected interleukin-6 at 1.84 pg/ml concentration.
Achieved high-contrast digital signals for single nanoparticle counting.
Demonstrated scalable fabrication using DUV lithography.
Abstract
Optical biosensors are indispensable in medical and environmental diagnostics, yet existing approaches are fundamentally limited in their sensitivity due to ensemble-averaged measurements. Digital biosensing has emerged as a promising solution for resolving individual binding events, thereby providing signals at very low analyte concentrations down to the single-molecule level. Here, we present a novel concept for digital optical biosensing empowered by dielectric Mie voids, combining nanoparticle-based contrast enhancement and deep learning for ultrasensitive biomarker detection. The resonantly trapped light in the air cavities of the periodic Mie void arrays ensures strong overlap between the near-fields and the single gold nanoparticles that are captured on the surface in the presence of the protein biomarker. Remarkably, this strong interaction creates high-contrast digital signals…
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