Fabrication of flower-like silver nanostructures for rapid detection of caffeine using surface enhanced Raman spectroscopy

Abstract

Flower-like silver nanoparticles, with diameters of 450~500 nm and protrusions on the surface up to 10~15 nm, have been successfully synthesized via liquid phase reduction method, by using ascorbic acid as a reductant and polyvinyl pyrrolidone (PVP) as a surfactant. It is found that the proper coating degree of PVP on silver nuclei leads to anisotropic growth of the silver nuclei resulting to the formation of flower-like structure with more protrusions. Furthermore, when the obtained flower-like silver nanostructure is used as Surface Enhanced Raman Scattering(SERS) substrates, SERS signal is still clearly even if the concentration of R6G solution is reduced down to 10-8 M. The SERS enhancement mechanism of flower-like silver nanostructures in SERS spectroscopy has been further discussed. SERS technology based on the obtained flower-like silver nanostructure substrates can be also used as an effective way to detect caffeine. In this work, it is found that the average intensity of SERS signals at 807 cm-1 (N-C-H), 958 cm-1 (Pyrimidine ring) and 1327 cm-1 (Imidazole trigonal ring) linear decreased with the-log 10 C (C is the concentration of caffeine), and the coefficient of determination (R 2) is as high as 0.975. This work provides a new way for the quantitative detection of caffeine based on SERS spectroscopy.

Part-Per-Billion Level Chemical Sensing with a Gold-Based SERS-Active Substrate

“…In this study, the drug caffeine was selected as a probe molecule to evaluate this sensor, as it generates a strong SERS response at 785 nm. The SERS of caffeine has been reported for various substrates, mostly silver colloids in water, in extracts from tea and coffee, and in biofluids [24][25][26][27][28][29][30][31][32][33][34][35]. Caffeine SERS has been measured and reported at 1 ppb on silver colloids [24] and 100 ppm on gold colloids [28].…”

SERS multiplexing of methylxanthine drug isomers via host–guest size matching and machine learning

“…Au NPs and Ag NPs) via their vibrational fingerprints, with additional advantages such as rapid response, high sensitivity, selectivity and reproducibility. Surprisingly, most of the previous SERS studies on MeX detection were based on Ag NPs [18][19][20][21][22][23][24][25][26][27] for their relatively strong signals despite Au NPs having higher chemical stability, reproducibility and biocompatibility. 28 This is probably due to the poor sensitivity and reproducibility of the SERS signals resulted from bare Au NPs or uncontrolled aggregation triggered by NaCl.…”

Qualitative and Quantitative Analysis of Caffeine in Medicines by Terahertz Spectroscopy Using Machine Learning Method

“…In the quantitative detection of caffeine, colloidal preparation of silver or gold nanoparticles is usually used, but there is a problem of poor reproducibility. [16,17] Therefore, we need a nondestructive, fast, accurate, low-cost, qualitative and quantitative detection method for caffeine medicines.…”