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Optimal geometry for plasmonic sensing with non-interacting Au nanodisk arrays

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Abstract

Combining finite elements method electrodynamic simulations and cost-effective and scalable nanofabrication techniques, we carried out a systematic investigation and optimization of the sensing properties of non-interacting gold nanodisk arrays. Such plasmonic nanoarchitectures offer a very effective platform for fast and simple, label-free, optical bio- and chemical-sensing. We varied their main geometrical parameters (diameter and height) to monitor the plasmonic resonance position and to find the configurations that maximize the sensitivity to small layers of an analyte (local sensitivity) or to the variation of the refractive index of an embedding medium (bulk sensitivity). The spectral position of the plasmonic resonance can be tuned over a wide range from the visible to the near-IR region (500–1300 nm) and state-of-the-art performances can be obtained using the optimized nanodisks; we obtained local and bulk sensitivities of S0 = 11.9 RIU−1 and Sbulk = 662 nm RIU−1, respectively. Moreover, the results of the simulations are compared with the performances of experimentally synthesized non-interacting Au nanodisk arrays fabricated by combining sparse colloidal lithography and hollow mask lithography, with the parameters obtained by the sensitivity numerical optimization. An excellent agreement between the experimental and the simulated results is demonstrated, confirming that the optimization performed with the simulations is directly applicable to nanosensors realized with cost-effective methods, due to the quite large stability basin around the maximum sensitivities.

Graphical abstract: Optimal geometry for plasmonic sensing with non-interacting Au nanodisk arrays

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Article information


Submitted
12 Mar 2020
Accepted
03 Jun 2020
First published
03 Jun 2020

This article is Open Access

Nanoscale Adv., 2020, Advance Article
Article type
Paper

Optimal geometry for plasmonic sensing with non-interacting Au nanodisk arrays

N. Michieli, I. G. Balasa, B. Kalinic, T. Cesca and G. Mattei, Nanoscale Adv., 2020, Advance Article , DOI: 10.1039/D0NA00208A

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