Well-dispersed and dense layers of gold nanorods (AuNRs) on optical fibers are shown to regulate the longitudinal peak wavelength and enhance the sensing performances of localized surface plasmon resonance (LSPR) biosensors. A simple self-assembly method relying on a brush-like monolayer of poly(styrene)-b-poly(acrylic acid) (PS-b-PAA) diblock copolymer was used to immobilize AuNRs with various aspect ratios from 2.33 to 4.60 on optical fibers. Both the experimental and simulation results illustrated that the particle aspect ratio, deposition time (related to the coverage of AuNRs), and interparticle gap significantly affected the optical properties of the fiber-based LSPR biosensors. The highest refractive index (RI) sensitivity of the sensor was 753 nm/RIU, while the limit of detection for human IgG was as low as 0.8 nM. Compared with standard nanoparticle deposition methods of polyelectrolytes or alkoxysilanes, the RI sensitivity of the PS-b-PAA dip-coating method was approximately 3-fold better, a consequence of the higher particle coverage and fewer AuNR aggregates. The presented AuNR-based LSPR sensors could regulate the detection range by tuning the aspect ratios of AuNRs. Applicability is demonstrated via quantitative analysis of antigen−antibody interactions, DNA sensing, and surface-enhanced Raman scattering.
2D nanoplasmonic substrates excited in transmission spectroscopy are ideal for several biosensing, metamaterial, and optical applications. We show that their excellent properties can be further improved with plasmonic coupling of Au nanoparticles (AuNPs) on gold-coated nanodisk arrays excited at large incidence angles of up to 50°. The Bragg modes (BM) thereby strongly couple to AuNP immobilized on the plasmonic substrate due to shorter decay length of the plasmon at higher incidence angles, leading to a further enhanced field between the AuNP and the plasmonic substrate. The field was highest and two hotspots were created at orthogonal positions for AuNP located close to the corner of the Au film and Au nanodisk, which was also observed for AuNP dimers. Hybridization between single-stranded DNA (ssDNA) immobilized on the surface of the AuNPs and the capture ssDNA on the gold-coated nanodisk arrays led to at least a 5-fold signal improvement and a 7-fold lower limit of detection at 7 pM for ssDNA-functionalized AuNPs at large incident angles. Thus, we demonstrate that higher field strength can be accessed and the significant advantages of working with high incidence angles with AuNP on a 2D plasmonic crystal in plasmonic sensing.
We report the crowding of Au nanoparticles
(Au NPs) on a surface-enhanced
Raman scattering (SERS) 2D array substrate with high nanoparticle
surface coverage in a combined approach for the identification of
cyanobacteria with machine learning. By simply using the screening
effect of NaCl, the crowding effect of PEG to overcome the repulsion
between nanoparticles, and different dithiol chain lengths during
the deposition process of Au NPs on a substrate, we provide a general
approach to increase the deposition density of nanoparticles on the
films over nanodisk-array SERS substrates. The optimized substrate
was subsequently utilized for the discrimination of wild-type (WT)
and mutant cyanobacteria using SERS and machine learning methods (principal
component analysis, logistic model, Gaussian naïve Bayes model,
K-nearest-neighbor model, and a support vector classifier model with
radial basis function). The best performance to discriminate between
WT and mutant cyanobacteria was achieved by using the support vector
classifier (SVC) with a positive rate as high as 97% using five repeat
tests for the congeneric cells. These results indicate that highly
sensitive SERS substrates, in combination with efficient data analysis,
can be employed in mutant identification by SERS, enabling high-throughput
screening in the current biological research.
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