A dual-signal sensing strategy based on ratiometric fluorescence and colorimetry for determination of Cu2+ and glyphosate

Herein, a dual-signal sensing strategy based on ratiometric fluorescence and colorimetry for Cu2+ and glyphosate determination was constructed. Fluorescence silicon nanoparticles (SiNPs) were prepared by hydrothermal reaction, which has maximum fluorescence intensity under the excitation of 355 nm. o-Phenylenediamine (OPD) was oxidized through Cu2+ to generate 2,3-diaminophenazine (oxOPD). The obtained oxOPD showed a strong absorption peak at 417 nm and quenched the fluorescence of SiNPs at 446 nm due to fluorescence resonance energy transfer (FRET). Meanwhile, oxOPD produced a new fluorescence emission at 556 nm forming a ratiometric state. With increasing Cu2+, the original solution changed from colorless to yellow. When glyphosate was present, the interaction between Cu2+ and the functional groups of glyphosate could reduce the oxidation of oxOPD, resulting in the enhancement of fluorescence at 446 nm and the decrease of fluorescence at 556 nm. Furthermore, the addition of glyphosate changed yellow solution to colorless. Under the optimal conditions of OPD (1 mM), 20 mM Tris-HCl buffer (pH 7.5), and incubation time (4 h), the ratiometric fluorescence sensor had good selectivity and showed a wide linear range of 0.025-20 mu M with the LOD of 0.008 mu M for Cu2+ and 0.15-1.5 mu g/mL with the LOD of 0.003 mu g/mL for glyphosate, respectively. Besides, it is worth mentioning that this developed sensing system showed good performance in real samples, providing a simple and reliable dual-signal detection strategy.

Automated summary

A dual-signal sensing strategy based on ratiometric fluorescence and colorimetry has been developed for the detection of Cu2+ and glyphosate. This strategy utilizes the fluorescence resonance energy transfer and absorption characteristics of specific substances generated through oxidation reactions. Under the optimized conditions, this sensing system demonstrates good selectivity and sensitivity, and performs well in real samples.