Abstract
ESAM as fluorescent probes for Hg(ii) ions were developed. The adsorption process involved in analyte-solid probe interaction was studied by monitoring fluorescence quenching.
Highlights
Fluorescent chemical sensors and probes have found wide applications in several elds, such as environmental monitoring, food and biochemical analysis, medical diagnosis
The adsorption process of mercury ions on porphyrin-based films was described by the pseudo-second-order equation and the kinetic parameters were correlated with the initial concentrations of the metal ions in aqueous solution
We show how the electrostatically self-assembled technique can be employed in order to reduce the typical tendency of porphyrins to aggregation, through the choice of appropriate building blocks and experimental conditions of preparation
Summary
Fluorescent chemical sensors and probes have found wide applications in several elds, such as environmental monitoring, food and biochemical analysis, medical diagnosis. The development of electrostatically selfassembled multilayers (ESAM), prepared by alternate adsorption of 5,10,15,20-tetrakis(4-sulfonatophenyl)porphyrin (TPPS) with poly(diallyldimethylammonium chloride), able to act as efficient uorescent probes for mercury(II) ions, is reported. The analysis of the adsorption kinetics based on the study of uorescence intensity quenching offers an alternative to equilibrium measurements, overcoming the problem of long equilibration times. Mercury ion detection was performed by immersion of TPPS lms in 1 cm path-length quartz cuvettes containing various metal ion solutions, whose concentrations ranged from 3.3 Â 10À5 M to 3.3 Â 10À8 M; the corresponding absorption, excitation and emission uorescence spectra were recorded at different time delays. In adsorption isotherms the equilibrium concentrations of mercury ions were obtained as follows: the TPPS total amounts (in mol) in ESAM were calculated from absorbance measurements and total surface of the lms: TPPS amount ðmolÞ. The experimental kinetic and equilibrium data were tted by means of a nonlinear least-squares algorithm
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