Wearable Double Network Plasmonic Hydrogel for SERS Detection of Urea and Uric Acid in Sweat

Traditional wearable devices for sweat detection often face limitations such as low detection sensitivity, insufficient mechanical properties, and discomfort during use. To address these challenges, hydrogels are utilized as sensor patches to improve skin sensor contact and combined with surface enhanced Raman spectroscopy (SERS) to enable rapid and sensitive analysis of biomarkers in sweat. In this study, a mechanically flexible, rapid, and ultrasensitive wearable plasmonic double network (PDN) hydrogel sensor utilizing silver nanoparticles (AgNPs) in situ was developed to detect the SERS spectra of urea and uric acid in synthetic sweat. With the incorporation of poly(vinyl alcohol) (PVA), the PDN hydrogel can stretch repeatedly and even double in size, making it more suitable for wearable devices. The AgNPs were uniformly dispersed within the hydrogel, which reduced the dissociation of AgNPs and increased the sensitivity of SERS detection at 0.1 and 10 pM for 4-mercaptobenzoic acid (4-MBA) and 4-aminothiophene (4-ATP), respectively. In sweat analysis, the concentration reached 10 pM for urea and 1 nM for uric acid. The PDN hydrogel worked well at different pH levels to adapt to a complex sweat environment. Combined with the Raman characteristic vibration peak, the important analysis of the machine learning model demonstrated that urea and uric acid play important roles in the identification of biomarkers in sweat. The data illustrated that this PDN hydrogel facilitates the exploration of wearable sweat devices and has significant potential for clinical applications in the early diagnosis of diseases.