Development of a 3D Hydrogel SERS Chip for Noninvasive, Real-Time pH and Glucose Monitoring in Sweat.

Traditional diagnostic methods, such as blood tests, are invasive and time-consuming, while sweat biomarkers offer a rapid physiological assessment. Surface-enhanced Raman spectroscopy (SERS) has garnered significant attention in sweat analysis because of its high sensitivity, label-free nature, and nondestructive properties. However, challenges related to substrate reproducibility and interference from the biological matrix persist with SERS.

Ultrasensitive detection of SARS-CoV-2 S protein with aptamers biosensor based on surface-enhanced Raman scattering.

A rapid and accurate diagnostic modality is essential to prevent the spread of SARS-CoV-2. In this study, we proposed a SARS-CoV-2 detection sensor based on surface-enhanced Raman scattering (SERS) to achieve rapid and ultrasensitive detection. The sensor utilized spike protein deoxyribonucleic acid aptamers with strong affinity as the recognition entity to achieve high specificity.

Manipulating the light-matter interactions in plasmonic nanocavities at 1 nm spatial resolution.

The light-matter interaction between plasmonic nanocavity and exciton at the sub-diffraction limit is a central research field in nanophotonics. Here, we demonstrated the vertical distribution of the light-matter interactions at ~1 nm spatial resolution by coupling A excitons of MoS and gap-mode plasmonic nanocavities. Moreover, we observed the significant photoluminescence (PL) enhancement factor reaching up to 2800 times, which is attributed to the Purcell effect and large local density of states in gap-mode plasmonic nanocavities.

A New Approach for Quantitative Surface-Enhanced Raman Spectroscopy through the Kinetics of Chemisorption.

Surface enhanced Raman spectroscopy (SERS) is a non-destructive, highly sensitive, and rapid analytical tool, which has been widely used in different fields, especially for trace quantities of analyte. However, using SERS for reliable quantitative sample analysis is still a great challenge. Herein, a new approach to quantitative SERS analysis at nanostructured substrates that does not require an internal standard or well-ordered nanostructured SERS substrates is developed.