This work describes the use of an array of potentiometric sensors and an artificial neural network response model to determine perchlorate and sulfide ions in polluted waters, by what is known as an electronic tongue. Sensors used have been all-solid-state PVC membrane selective electrodes, where their ionophores were different metal-phtalocyanine complexes with specific and anion generic responses. The study case illustrates the potential use of electronic tongues in the quantification of mixtures when interfering effects need to be counterbalanced: relative errors in determination of individual ions can be decreased typically from 25% to less than 5%, if compared to the use of a single proposed ion-selective electrode.

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Nanostructured ZrO 2 -based materials with their biocompatibility, excellent electrical, and surface charge properties became one of the best candidates for the electrochemical sensing applications. Here, synthesis of Zr 1-x Cu x La x O 2 compounds was achieved in nanoscale and fully characterized using XRD, TEM, DRS, and cyclic voltammetry. A mixture of monoclinic and cubic phases was detected for the undoped ZrO 2 (Z sample, x = 0). For the Cu-doped compounds, (ZFW1, x = 0.05 and ZFW2, x = 0.1), a combination of cubic fluorite and monoclinic phase were detected. The intensity of the monoclinic phase for the Cudoped was higher than that of the undoped ZrO 2 sample. Cu and La co-doped samples (ZL1C1, x = 0.05 and ZL2C2, x = 0.1) were stabilized in a single cubic phase structure. Therefore, their band gap dropped from (4.8 eV) for the undoped ZrO 2 to (1.49 eV) for the ZL1C1 sample and (2 eV) for the ZL2C2 sample. Voltammetric sensing of neurotransmitter metabolites (vanillylmandelic acid (VMA) and homovanillic acid (HVA)) was achieved using the modified electrodes due to their acquired high electrocatalytic and high electrochemical performance.