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.

In this feature article, we discuss the significant role of the pre-oxidation reaction during urea electro-oxidation, and summarize the detailed strategies and recent advances in promoting the pre-oxidation reaction.

Electroreduction of nitrates to other essential fertilizers is becoming an important method for the treatment of nitrate contamination. In this study, Ag nanocrystal catalyst on the quasi-cavity architecture of ZnO nanowalls has been rationally designed and synthesized. This hierarchical structure can efficiently catalyze nitrate reduction as well as a sensitive surface-enhanced Raman signals (SERS)-active substrate, which make it possible to figure out the mechanism for Ag-catalyzed electroreduction process at the atomic level. The catalyst exhibits an ammonia production of 516 mmol g_cat ⁻¹ h⁻¹ and a Faradaic efficiency of about 66% at −0.6 V vs. reversible hydrogen electrode (RHE). The in situ Raman spectra clearly show SERS signals of NO, HNH and NH₃, which provide direct evidences to analyze the final production of ammonia and nitrite during the electroreduction process. This work can offer a fundamental understanding of the mechanism of the electroreduction process and further design strategies for other energy-related catalysts.