4.7 Article

Enhanced Tb(III) fluorescence on gelatin-coated silver nanoparticles in dopamine detection

Journal

TALANTA
Volume 231, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.talanta.2021.122334

Keywords

Metal enhanced fluorescence; Gelatin-coated silver nanoparticles; Tb(III); Dopamine

Funding

  1. Shandong Provincial Natural Science Foundation, China [ZR2018MB031]
  2. National Natural Science Foundation of China [21545001, U1906221]

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A composite fluorescent nanoprobe based on metal enhanced fluorescence effect of gelatin-coated silver nanoparticles was developed for selective and sensitive detection of dopamine. The probe showed a low detection limit and good selectivity, making it a promising approach for dopamine detection in human serum samples.
A composite fluorescent nanoprobe based on metal enhanced fluorescence (MEF) effect of gelatin-coated silver nanoparticles (AgNPs@gel) was developed for selective and sensitive detection of dopamine (DA). The characteristic fluorescence of Tb(III) was using as the detection signal and AgNPs@gel served as substrates of the MEF. Gelatin with rich amine and carboxylic groups was used not only as a co-ligand of Tb(III) complex, but also as a bridging substance and a spacing material for improving the MEF of AgNPs@gel on the intrinsic luminescent intensity of Tb(III). Under the optimal conditions, the increment of the fluorescence intensity (measured at 307/544 nm as excitation/emission wavelength) of the system increased linearly with the concentration of DA in the range of 0.80-100 nM (R-2 = 0.9937) and 100-1000 nM (R-2 = 0.9978). The fluorescent probe greatly improved Tb(III) luminescence, which paved the way for sensitive detection with a low detection limit of 0.54 nM. It also showed good selectivity among other neurotransmitters. This work was successfully applied to the determination of DA in human serum samples with recoveries ranging from 99.8 to 102.2%. We believe that the Tb(III)-DA-AgNPs@gel composite fluorescent probe can be developed as a new approach for DA detection.

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