Suppression of coffee-ring effect via periodic oscillation of substrate for ultra-sensitive enrichment towards surface-enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) has attracted extensive interest due to excellent molecule recognition and sensitive concentration detection. Nevertheless, the coffee ring effect (CR) during the analyte evaporation always causes an uneven distribution of the assembled hot-spots, and hence the unreliable SERS signal is produced. In this study, for the first time, we present a suppressed coffee ring (SCR) system via a combination of a magnetically functionalized membrane and reciprocating magnetic field to dynamically suppress the CR for highly reliable and ultra-sensitive SERS detection. The enrichment mechanism of the nanoparticles and the analyte molecules within the sessile droplet based on the proposed system was studied. We experimentally observed that the driving frequency could well affect the final pattern, and typically a higher driving frequency facilitated a smaller coverage area with better enrichment performance. With the use of R6G molecule and (100 nm) gold nanoparticles, we examined the uniformity and SERS of the assembled 'hot-spots' in the SCR system. The results indicate that the uniformity can be greatly improved via SCR in comparison of ring stain, with the RSD of a Raman signal as low as 7.1% even at a low concentration of 10^-12 mol L^-1. Such system also enables the further enhancement in the SERS signal, with the detection limit down to 10^-16 mol L^-1, the enhancement factor magnitude up to 10¹³, and the linear relationship between the SERS intensity and the analyte concentrations within the range of 10^-6-10^-12 and 10^-12-10^-16 mol L^-1, respectively. The applicability of the SCR-based SERS detection for diverse analytes was also proved with a similar but further enhanced signal of MB and 4-ATP. We believe that the excellent SCR-based SERS performance via the proposed system has great potentials for ultra-sensitive detection and/or precise quantitative analysis in various research fields and applications.