Gold nanoclusters/graphene quantum dots complex-based dual-emitting ratiometric fluorescence probe for the determination of glucose.

Herein, we report the design of a single-excitation/double-emission ratiometric fluorescence nanosensor for the determination of glucose. The sensing system combines glucose oxidation catalyzed by glucose oxidase, Fenton chemistry, Fe3+-sensitive fluorescent gold nanoclusters (AuNCs), and Fe3+-inert fluorescent graphene quantum dots (GQDs). We used orange-fluorescent AuNCs co-modified with bovine serum albumin and 3-mercaptopropionic acid as the indicator probe, and GQDs with the same excitation wavelength as the BSA/MPA-AuNCs, but with different emission wavelength, as the reference probe. The fluorescence intensity-ratio between 420 nm and 575 nm (F420/F575) was used to quantitatively determine glucose with a low detection limit of 0.18 µM, and the nanosensor was successfully used to detect glucose in human serum. This ratiometric fluorescence sensing system, based on AuNCs and GQDs, ensures sensitive and convenient determination of glucose, and has broad application prospects for biomedical-analysis applications.

Sensitive and selective nitrite assay based on fluorescent gold nanoclusters and Fe2+/Fe3+ redox reaction.

In recent years, gold nanoclusters (AuNCs) have received considerable attention as optical transducers in chemo/biosensors. Herein, a facile and efficient assay for NO2- has been successfully developed based on the fluorescence quenching of AuNCs co-modified by bovine serum albumin and 3-mercaptopropionic acid (BSA/MPA-AuNCs). In the presence of NO2- under acidic conditions, Fe2+ can be readily oxidized and transformed to Fe3+, which can significantly suppress the fluorescence of BSA/MPA-AuNCs via non-radiative electron-transfer mechanism. The linear range and detection limit for this system were found to be 5-30 µM (r = 0.9975) and 0.7 µM, respectively. Other common anions and cations showed only very minor interference with the NO2- detection. Furthermore, the effectiveness of the proposed sensing strategy was validated by the demonstration of good performance in the determination of the amount of NO2- in ham samples, rendering it a powerful tool for the assessment of food security and water quality.