journal article·2017-12

High-sensitivity molecular sensing using plasmonic nanocube chains in classical and quantum coupling regimes

Nasrin Hooshmand, Hamed Shams Mousavi, Sajanlal R. Panikkanvalappil, Ali Adibi, Mostafa A. El-Sayed

Nano Today· Volume 17
Publisher page

Abstract

Abstract One-dimensional plasmonic nanoparticle arrays have intriguing optical properties that can be utilized in a number of applications, including molecular sensing. In this paper, firstly, we studied the plasmonic coupling behavior in chains of gold and silver plasmonic nanocubes of 21 nm edge length arranged in both face-to-face and edge-to-edge configurations at large separation distance (8.5 nm), where the classical electromagnetic coupling is dominant. Interestingly, an increase in the sensitivity factor was observed when increasing the number of nanocubes in the chain and by orienting them in edge-to-edge configuration, with a few exceptions. Additionally, linear chains of edge-to-edge and face-to-face assembled gold nanocube with sub-nanometer interparticle distances (0.2 nm), where the effect of tunneling-induced charge transfer plasmons (tCTPs) becomes significant, was studied using a quantum-corrected model. In comparison to the face-to-face orientation, the changes in optical properties were more prominent in the edge-to-edge configuration. Our results suggest that plasmonic coupling in linearly assembled nanoparticles becomes extremely important at sub-nanometer interparticle distances. It can significantly modify the optical properties of the nanocubes chains, especially spectral line shape and electric-field distribution, which might help designing more advanced sensing devices for chemical and bio-sensing applications.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Gold and Silver Nanoparticles Synthesis and Applications · Plasmonic and Surface Plasmon Research · Molecular Junctions and Nanostructures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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