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Updated: Dec 15, 2025

Plasmonic Trapping and Release of Nanoparticles in a Monitoring Environment
Published on: April 4, 2017
Entangled Nanoplasmonic Cavities for Estimating Thickness of Surface-Adsorbed Layers
Amideddin Mataji-Kojouri1,2, Mehmet Ozgun Ozen2, Mahmoud Shahabadi1
1Photonics Research Laboratory, Center of Excellence on Applied Electromagnetic Systems, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran 1439957131, Iran.
Abstract:
Plasmonic sensors provide real-time and label-free detection of biotargets with unprecedented sensitivity and detection limit. However, they usually lack the ability to estimate the thickness of the target layer formed on top of the sensing surface. Here, we report a sensing modality based on reflection spectroscopy of a nanoplasmonic Fabry-Perot cavity array, which exhibits characteristics of both surface plasmon polaritons and localized plasmon resonances and outperforms its conventional counterparts by providing the thickness of the surface-adsorbed layers. Through numerical simulations, we demonstrate that the designed plasmonic surface resembles two entangled Fabry-Perot cavities excited from both ends. Performance of the device is evaluated by studying sensor response in the refractive index (RI) measurement of aqueous glycerol solutions and during formation of a surface-adsorbed layer consisting of protein (i.e., NeutrAvidin) molecules. By tracking the resonance wavelengths of the two modes of the nanoplasmonic surface, it is therefore possible to measure the thickness of a homogeneous adsorbed layer and RI of the background solution with precisions better than 4 nm and 0.0001 RI units. Using numerical simulations, we show that the thickness estimation algorithm can be extended for layers consisting of nanometric analytes adsorbed on an antibody-coated sensor surface. Furthermore, performance of the device has been evaluated to detect exosomes. By providing a thickness estimation for adsorbed layers and differentiating binding events from background RI variations, this device can potentially supersede conventional plasmonic sensors.

