Mixed-Ligand gold nanoparticles based optical sensor array for the recognition and quantification of seven toxic metals

Abstract

Sensor arrays use pattern recognition for the identification and quantification of analytes. In the presented work, a gold nanoparticle (GNP) based optical sensor array was employed to classify and quantify seven toxic metals (arsenic, barium, cadmium, cerium, chromium, lead, and mercury). The sensor array receptors were GNPs functionalized by mercaptoundecanoic acid, 2-mercaptoethanesulfonate, and a 1:1 mixture of the two ligands. The mixed-ligand particle responds to the same analytes as the mono-ligand particles but in a distinctive way. This behavior demonstrates the high potential of mixed-ligand particles in the fabrication of sensor array receptors. The responses of the GNPs to different concentrations of the seven metal ions were analyzed, and a unique “classification trajectory” was produced for every metal. Samples of different metal concentrations were then measured and identified using the “classification trajectories”. Once sample composition has been identified, a PLSR model, produced from the concatenated sensor array spectra of four calibration samples for each nanoparticle, was used to determine the metal concentration.