Interfacial self-assembly is a powerful technology for preparing large scale nanoparticle monolayers, but fabrication of highly repeatable large scale nanoparticle monolayers remains a challenge. Here we develop an oil/water/oil (O/W/O) threephase system based on the Marangoni effect to fabricate highly reproducible nanoparticle monolayers. Nanoparticles could be easily transferred and compressed from the lower O/W interface to the upper O/W interface due to the interfacial tension gradient. The O/W/O system can be constructed using different kinds of organic solvents. Through this approach, good uniformity and reproducibility of the nanoparticle monolayers could be guaranteed even using a wide range of nanoparticle concentrations. Furthermore, this strategy is generally applicable to various nanoparticles with different sizes, shapes, components, and surface ligands, which offers a facile and general approach to functional nanodevices.
The surface‐enhanced Raman scattering (SERS) technique with ultrahigh sensitivity has gained attention to meet the increasing demands for food safety analysis. The integration of machine learning and SERS facilitates the practical applicability of sensing devices. In this study, a machine learning‐driven 3D plasmonic cavity‐in‐cavity (CIC) SERS platform is proposed for sensitive and quantitative detection of antibiotics. The platform is prepared by transferring truncated concave nanocubes (NCs) to an obconical‐shaped template surface. Owing to the triple synergistic enhancement effect, the highly ordered 3D CIC arrays improve the simulated electromagnetic field intensity and experimental SERS activity, demonstrating a 33.1‐fold enhancement compared to a typical system consisting of Au NCs deposited on a flat substrate. The integration of machine learning and Raman spectroscopy eliminates subjective judgments on the concentration of detectors using a single feature peak and achieves accurate identification. The machine learning‐driven CIC SERS platform is capable of detecting ampicillin traces in milk with a detection limit of 0.1 ppm, facilitating quantitative analysis of different concentrations of ampicillin. Therefore, the proposed platform has potential applications in food safety monitoring, health care, and environmental sampling.
The
self-assembly of plasmonic nanoparticles into highly ordered
superlattices could pave the way toward novel nanomaterials for surface-enhanced
Raman scattering (SERS). Here, we propose the formation of large-area
superlattices of elongated rhombic dodecahedra in a vertical orientation
via a controlled droplet evaporation process. Expectedly, the constant
humidity of the experimental condition could control the evaporation
speed of droplets and this procedure promotes the balance between
driven depletion attraction and electrostatic repulsion in the system,
leading to the generation of well-organized three-dimensional (3D)
superlattices. The unique geometry of elongated rhombic dodecahedra
could establish the tetragonal superlattices, which breaks the conventional
hexagonal symmetry of gold nanorods. Specifically, the influence of
the type and concentration of surfactants, the concentration of nanoparticles,
and the amount of droplets on the preparation results were systematically
investigated to find the optimal assembly parameters. Remarkably,
such close-packed tetragonal arrays of vertically aligned elongated
rhombic dodecahedra exhibit more excellent SERS performance compared
with the traditional hexagonal superstructure of gold nanorods. Benefiting
from the high sensitivity and reproducibility of elongated rhombic
dodecahedron superlattices, their applications in the determination
of pesticide residues in apple and grape peels were successfully demonstrated.
As a result, this study may advance the production of innovative plasmonic
nanomaterials for a broad range of fields.
The nanoparticle density (PD) of the substrates is crucial for surface‐enhanced Raman scattering (SERS) performance. Here, bottom‐up SERS substrates based on rough gold nanorods (R‐Au NRs) with different PD are fabricated and their SERS property are investigated. In particular, R‐Au NRs are deposited on the Si wafer from sparse to dense through electrostatic interaction and from monolayer to multiple layers by interface self‐assembly technique. It is found that the SERS intensity increases dramatically with increasing PD and remains almost unchanged when the PD increases to 241.22 counts µm−2, and the limited penetration depth of laser is the reason for the intensity saturation. Additionally, similar results are observed in the smooth Au NRs substrates, re‐confirming the PD‐dependent SERS performance. Importantly, the SERS activity of R‐Au NRs substrates is higher than smooth Au NRs substrates in each PD, indicating that R‐Au NRs can produce stronger electromagnetic field enhancement, which is supported by the theoretical simulation results. Finally, it is demonstrated that the optimal SERS substrates can be effectively utilized for the quantitative measurement of thiram in soil. Briefly, the PD of substrates has a great impact on SERS activity, which offers an idea for the design of highly efficient SERS substrates.
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