Quantitative detection of trace small-sized nanoplastics (<100 nm) remains a significant challenge in surface-enhanced Raman scattering (SERS). To tackle this issue, we developed a hydrophobic CuO@Ag nanowire substrate and introduced a multiplex-feature analysis strategy based on the coffee ring effect. This substrate not only offers high Raman enhancement but also exhibits a high probability of detection (POD), enabling rapid and accurate identification of 50 nm polystyrene nanoplastics over a broad concentration range (1–10⁻¹⁰ wt%). Importantly, experimental results reveal a strong correlation between the coffee ring formation and the concentration of nanoplastic dispersion. By incorporating Raman signal intensity, coffee ring diameter, and POD as combined features, we established a machine learning-based mapping between nanoplastic concentration and coffee ring characteristics, allowing precise predictions of dispersion concentration. The mean squared error of these predictions is remarkably low, ranging from 0.21 to 0.54, representing a 19 fold improvement in accuracy compared to traditional linear regression-based methods. This strategy effectively integrates SERS with wettability modification techniques, ensuring high sensitivity and fingerprinting capabilities, while addressing the limitations of Raman signal intensity in accurately reflecting concentration changes at ultra-low levels, providing a new idea for precise SERS measurements of nanoplastics.

Regulation of hot spots exhibits excellent potential in many applications including nanolasers, energy harvesting, sensing, and subwavelength imaging. Here, hat‐shaped hierarchical nanostructures with different space curvatures have been proposed to enhance hot spots for facilitating surface‐enhanced Raman scattering (SERS) and plasmon‐driven catalysis applications. These novel nanostructures comprise two layers of metal nanoparticles separated by hat‐shaped MoS ₂ films. The fabrication of this hybrid structure is based on the thermal annealing and thermal evaporation of self‐assembled polystyrene spheres, which are convenient to control the metal particle size and the curvature of hat‐shaped nanostructures. Based on the narrow gaps produced by the MoS ₂ films and the curvature of space, the constructed platform exhibits superior SERS capability and achieves ultrasensitive detection for toxic molecules. Furthermore, the surface catalytic conversion of p‐nitrothiophenol (PNTP) to p, p′‐dimercaptobenzene (DMAB) was in situ monitored by the SERS substrate. The mechanism governing this regulation of hot spots is also investigated via theoretical simulations.

It is very vital to construct the dense hot spots for the strong surface-enhanced Raman scattering (SERS) signals. We take full advantage of the MoS₂ edge-active sites induced from annealing the Ag film on the surface of the MoS₂. Furthermore, the composite structure of Au-Ag bi-metal nanoparticles (NPs)/MoS₂ hybrid with pyramid structure is obtained by the in situ grown AuNPs around AgNPs, which serves the optimal SERS performance (enhancement factor is ~9.67 × 10⁹) in experiment. Due to the introduction of AuNPs with the simple method, the denser hot spots contribute greatly to the stronger local electric field, which is also confirmed by the finite-different time-domain (FDTD) simulation. Therefore, the ultralow limit of detection (the LOD of 10⁻¹³ and 10⁻¹² M respectively for the resonant R6G and non-resonant CV), quantitative detection and excellent reproducibility are achieved by the proposed SERS substrate. For practical application, the melamine molecule is detected with the LOD of 10⁻¹⁰ M using the proposed SERS substrate that has the potential to be a food security sensor.