Andreu González-Calabuig

Crown ether-modified electrodes for the simultaneous stripping voltammetric determination of Cd(II), Pb(II) and Cu(II).

This work describes the immobilization of 4-carboxybenzo-18-crown-6 (CB-18-crown-6) and 4-carboxybenzo-15-crown-5 (CB-15-crown-5) assisted by lysine on aryl diazonium salt monolayers anchored to the surface of graphite-epoxy composite electrodes (GEC), and their use for the simultaneous determination of Cd(II), Pb(II) and Cu(II) by differential pulse anodic stripping voltammetry (DPASV). These modified electrodes display a good repeatability and reproducibility with detection and quantification limits at levels of µg L(-1) (ppb), confirming their suitability for the determination of Cd(II), Pb(II) and Cu(II) ions in environmental samples. The overlapped nature of the multimetal stripping measurements was resolved by employing the two-sensor array CB-15-crown-5-GEC and CB-18-crown-6-GEC, since the metal complex selectivity exhibited by the considered ligands could add some discrimination power. For the processing of the voltammograms, Discrete Wavelet Transform and Causal Index were selected as preprocessing tools for data compression coupled with an artificial neural network for the modeling of the obtained responses, allowing the resolution of mixtures of these metals with good prediction of their concentrations (correlation with expected values for an external test subset better than 0.942).

Electronic tongues to assess wine sensory descriptors

This work reports the application of an electronic tongue as a tool towards the analysis of wine in tasks such as its discrimination based on the maturing in barrels or the prediction of the global scores assigned by a sensory panel. To this aim, red wine samples were first analysed with the voltammetric sensor array, without performing any sample pretreatment. Afterwards, obtained responses were preprocessed employing fast Fourier transform (FFT) for the compression and reduction of signal complexity, and obtained coefficients were then used as inputs to build the qualitative and quantitative models employing either linear discriminant analysis (LDA) or partial least squares regression (PLS), respectively. Satisfactory results were obtained overall, with a classification rate of 100% in the discrimination of the type of barrel used during wine maturing, a normalized NRMSE of 0.077 in the estimation of ageing time (months) or 0.11 in the prediction of the scores (0-10) from a trained sensory panel (all for the external test subset).

Electronic tongue for nitro and peroxide explosive sensing

This work reports the application of a voltammetric electronic tongue (ET) towards the simultaneous determination of both nitro-containing and peroxide-based explosive compounds, two families that represent the vast majority of compounds employed either in commercial mixtures or in improvised explosive devices. The multielectrode array was formed by graphite, gold and platinum electrodes, which exhibited marked mix-responses towards the compounds examined; namely, 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), pentaerythritol tetranitrate (PETN), 2,4,6-trinitrotoluene (TNT), N-methyl-N,2,4,6-tetranitroaniline (Tetryl) and triacetone triperoxide (TATP). Departure information was the set of voltammograms, which were first analyzed by means of principal component analysis (PCA) allowing the discrimination of the different individual compounds, while artificial neural networks (ANNs) were used for the resolution and individual quantification of some of their mixtures (total normalized root mean square error for the external test set of 0.108 and correlation of the obtained vs. expected concentrations comparison graphs r>0.929).

A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures

This work reports the applicability of a voltammetric sensor array able to quantify the content of 2,4-dinitrophenol, 4-nitrophenol, and picric acid in artificial samples using the electronic tongue (ET) principles. The ET is based on cyclic voltammetry signals, obtained from an array of metal disk electrodes and a graphite epoxy composite electrode, compressed using discrete wavelet transform with chemometric tools such as artificial neural networks (ANNs). ANNs were employed to build the quantitative prediction model. In this manner, a set of standards based on a full factorial design, ranging from 0 to 300 mg·L−1, was prepared to build the model; afterward, the model was validated with a completely independent set of standards. The model successfully predicted the concentration of the three considered phenols with a normalized root mean square error of 0.030 and 0.076 for the training and test subsets, respectively, and r ≥ 0.948.

Voltammetric electronic tongue to identify Brett character in wines. On-site quantification of its ethylphenol metabolites

This work reports the applicability of a voltammetric sensor array able to evaluate the content of the metabolites of the Brett defect: 4-ethylphenol, 4-ethylguaiacol and 4-ethylcatechol in spiked wine samples using the electronic tongue (ET) principles. The ET used cyclic voltammetry signals, obtained from an array of six graphite epoxy modified composite electrodes; these were compressed using Discrete Wavelet transform while chemometric tools, among these artificial neural networks (ANNs), were employed to build the quantitative prediction model. In this manner, a set of standards based on a modified full factorial design and ranging from 0 to 25mgL-1 on each phenol, was prepared to build the model; afterwards, the model was validated with an external test set. The model successfully predicted the concentration of the three considered phenols with a normalized root mean square error of 0.02 and 0.05, for the training and test subsets respectively, and correlation coefficients better than 0.958.

Enhanced electrochemical response of carbon quantum dot modified electrodes

A glassy carbon electrode (GCE) was surface-modified with carbon quantum dots (CQDs) and applied for the effective enhancement of the electrochemical signal for dopamine and uric acid determination. CQDs were prepared from graphite by a green modification of the Hummers method. They were characterized by FTIR-ATR, XPS, solid-state NMR, fluorescence and Raman spectroscopies. TPD-MS analysis was applied to characterize the functionalization of the surface. The CQDs were assembled on the glassy carbon electrode by adsorption because of the large number of carboxy groups on their surface warrants effective adsorption. The modified GCE exhibits a sensitivity that is almost 10 times better than of the bare GCE. The lower limits of detection are 1.3μM for uric acid and 2.7μM for dopamine.

Voltammetric Resolution of Dopamine in Complex Mixtures Using Graphene-Modified Electrode and Artificial Neural Networks

Dopamine (DA) is an important catecholamine neurotransmitter that plays a relevant role in the human body’s function. [...]

Novel voltammetric electronic tongue approach using polyelectrolyte modifiers to detect charged species

A voltammetric electronic tongue has been devised through modification of electrode surface via a highly robust conducting graphite ink incorporating selected polyelectrolytes. These can be neutral (polystyrene or acrylamide), cationic (polyDADMAC) or anionic (EGMP), providing in this way differentiated electroactivity towards analytes having redox signal but with different net charge. In this manner, a voltammetric electronic tongue of this nature has been setup and used for the resolution of mixtures of acetaminophen, ascorbic acid and uric acid, species with different charge at the studied pHs (2.3, 4.8, 7.5 and 10.3). Final quantification of ternary mixtures of these compounds was achieved using the windowed sliced integral method to reduce the data dimensions followed by an artificial neural network model, achieving correlations r > 0.969 for the external test subset (n=10 samples).

Voltammetric Electronic Tongue for the Sensing of Explosives and Its Mixtures

This chapter presents recent work with electronic tongues, that is sensor analytical systems formed by an array of chemical sensors featuring low selectivity plus a chemometric tool to process the complex multivariate data that is generated. As the generic application covered is related to security, the described systems are those devised to identify and detect explosive compounds. These are characterized from their voltammetric features, whereas a particular fingerprint is used to identify particular compounds alone, or, in a more advanced application, to resolve mixtures of compounds, that is to quantify their presence in mixtures. Two are the main approaches shown, a first from the use of a voltammetric screen printed electrode, and a second one from an array of metallic electrodes. Detected compounds are different nitro-based energetic compounds, and later, also the identification of organic peroxide type compounds.