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Silica‐Coated Gold Nanorod Supraparticles: A Tunable Platform for Surface Enhanced Raman Spectroscopy
Author(s) -
Hoeven Jessi E.S.,
Gurunarayanan Harith,
Bransen Maarten,
Winter D.A. Matthijs,
Jongh Petra E.,
Blaaderen Alfons
Publication year - 2022
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.202200148
Subject(s) - materials science , nanorod , raman spectroscopy , plasmon , surface enhanced raman spectroscopy , nanotechnology , colloidal gold , porosity , surface plasmon resonance , nanoparticle , raman scattering , optoelectronics , optics , composite material , physics
Plasmonic nanoparticle assemblies are promising functional materials for surface‐enhanced Raman spectroscopy (SERS). Gold nanorod (AuNR) assemblies are of particular interest due to the large, shape‐induced local field enhancement and the tunable surface plasmon resonance of the AuNRs. Designing the optimal assembly structure for SERS, however, is challenging and requires a delicate balance between the interparticle distance, porosity, and wetting of the assembly. Here, a new type of functional assemblies–called supraparticles–fabricated through the solvent‐evaporation driven assembly of silica‐coated gold nanorods into spherical ensembles, in which the plasmonic coupling and the mass transport is tuned through the thickness and porosity of the silica shells are introduced. Etching of the AuNRs allowed fine‐tuning of the plasmonic response to the laser excitation wavelength. Using a correlative SERS‐electron microscopy approach, it is shown that all supraparticles successfully amplified the Raman signal of the crystal violet probe molecules, and that the Raman signal strongly increased when decreasing the silica shell thickness from 35 to 3 nm, provided that the supraparticles have a sufficiently high porosity. The supraparticles introduced in this study present a novel class of materials for sensing, and open up a wide parameter space to optimize their performance.