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The detection of biomarkers in tears has aroused great interest owing to the advantages of non‐invasive and rapid collection. The combination of ultrasensitivity and label‐free detection of surface‐enhanced Raman spectroscopy (SERS) sensors is expected to achieve real‐time diagnosis in home medical care. However, the surface of SERS sensors is susceptible to biofouling and inactivation by biological impurities in tears, resulting in rapid degradation of sensitivity, limiting the commercialization of point‐of‐care devices. Herein, a binary nanosphere array with dual properties is constructed as a separation‐sensing platform for the diagnosis of target molecules in tears. The upper part of the structure is composed of Au nanoparticles (AuNPs) and a sputtering Au layer, which can bind the target molecules that interact with Au and provide high‐strength and high‐density SERS hotspots. The lower half is an inactive SiO2 nanosphere array with periodic large pores that allows biological impurities to penetrate the lower part and be separated from the target analyte. Furthermore, this substrate was integrated into homemade tear kits, enabling simultaneous tear collection, pre‐separation, and detection. Combined with the Raman spectra of tears and LDA analysis, we successfully identified patients with jaundice in clinics. This platform is expected to provide an opportunity for early disease screening based on biological fluids. [ABSTRACT FROM AUTHOR]

To detect biomarkers from human exhalation, air flow dynamics on the nanoparticle surface were explored by a surface‐enhanced Raman scattering (SERS) sensor. A hollow Co‐Ni layered double hydroxide (LDH) nanocage on Ag nanowires (Ag@LDH) was prepared. Ag nanowires provided amplified Raman signals for trace determination; hollow LDH nanocages served as the gaseous confinement cavity to improve capture and adsorption of gaseous analytes. The Raman intensity and logarithmic analyte concentration exhibit an approximately linear relationship; the detection limit of SERS sensors for aldehyde is 1.9×10−9 v/v (1.9 ppb). Various aldehydes in mixed mimetic gas are distinguished by Raman spectra statistical analysis assisted by multivariate methods, including principal component analysis and hierarchical cluster analysis. The information was recorded in a barcode, which can be used for the design and development of a desktop SERS sensor analysis system for large‐scale lung cancer detection. [ABSTRACT FROM AUTHOR]