Chemometric Analysis of Excitation Emission Matrices of Fluorescent Nanocomposites

Abstract

The performance of multivariate curve resolution (MCR-ALS) to decompose sets of excitation emission matrices of fluorescence (EEM) of nanocomposite materials used as analytical sensors was assessed. The two fluorescent nanocomposite materials were: NH(2)-polyethylene glycol (PEG200) functionalized carbon dots, sensible to aqueous Hg(II) (CD); and, CdS quantum dots attached to the dendrimer DAB, sensible to the ionic strength of the aqueous medium (CdS-DAB). The structures of these sets of EEM, obtained as function of the Hg(II) concentration and ionic strength, are characterized by collinear properties (CD) and non-linear spectral variations (CdS-DAB). MCR-ALS was able to detect that the source of the collinearities is the presence of different size CD that show similar affinity towards Hg(II). Moreover, MCR-ALS was able to model the non-linear spectral variations of the CdS-DAB that are induced by varying ionic strength. The chemometric preprocessing of the fluorescent data sets using soft-modelling multivariate curve resolution like MCR-ALS is a critical step to transform these nanocomposites with interesting fluorescent proprieties into analytical useful nanosensors.