ABSTRACT
Semiconductor quantum dots (QDs) have demonstrated a great potential as fluorescent probes for heavy metals monitoring. However, their great reactivity, whose tunability could be difficult to attain, could impair selectivity yielding analytical results with poor accuracy. In this work, the combination in the same analysis of multiple QDs, each with a particular ability to interact with the analyte, assured a multi-point detection that was not only exploited for a more precise analyte discrimination but also for the simultaneous discrimination of multiple mutually interfering species, in the same sample. Three different MPA-CdTe QDs (2.5, 3.0 and 3.8nm) with a good size distribution, confirmed by the FWHM values of 48.6, 55.4 and 80.8nm, respectively, were used. Principal component analysis (PCA) and partial least squares regression (PLS) were used for fluorescence data analysis. Mixtures of two MPA-CdTe QDs, emitting at different wavelength namely 549/566, 549/634 and 566/634nm were assayed. The 549/634nm emitting QDs mixture provided the best results for the discrimination of distinct ions on binary and ternary mixtures. The obtained RMSECV and R2CV values for the binary mixture were good, namely, from 0.01 to 0.08mgL-1 and from 0.74 to 0.89, respectively. Regarding the ternary mixture the RMSECV and R2CV values were good for Hg(II) (0.06 and 0.73mgL-1, respectively) and Pb(II) (0.08 and 0.87mg L-1, respectively) and acceptable for Cu(II) (0.02 and 0.51mgL-1, respectively). In conclusion, the obtained results showed that the developed approach is capable of resolve binary and ternary mixtures of Pb (II), Hg (II) and Cu (II), providing accurate information about lead (II) and mercury (II) concentration and signaling the occurrence of Cu (II).
