Identification of plastic toys contaminated with volatile organic compounds using QCM gas sensor array.

In this paper, we propose a fast and easy-to-use analytical method to identify the children toys contaminated with potentially dangerous substances from the class of volatile organic compounds (VOCs). It is shown that the use of cross-sensitive gas sensor array based on piezoelectric sensors, modified with different sorbents, allows reliable recognition of items with the elevated levels of VOCs. Applying chemometric methods for processing of the sensor array data, it is possible to classify the toys into clean and hazardous ones with sensitivity and accuracy around 96%. Taking into account the simplicity of the suggested procedure, it appears to be an attractive option for cost-effective pre-screening of potentially dangerous plastic toys in comparison with the expensive and time-consuming chromatographic methods.

Systematic approach in Mg2+ ions analysis with a combination of tailored fluorophore design.

A systematic study of a series of diaza-18-crown-6 8-hydroxyquinoline (DCHQ) chemosensors, devoted to Mg(II) ion detection, was performed. Functionalization of DCHQ by peripheral substituents allowed the development of novel all-solid-state optodes via inclusion inside PVC-based polymeric films. The influence on the DCHQ-based optode response of the lipophilic sites functionalization and of the nature of the plasticizer, was investigated. Fluorimetric studies on optodes sensitivity towards a number of different metal cations (Ca2+, Na+, K+, Li+, Co2+, Cd2+, Pb2+, Cu2+, Hg2+, Zn2+) and NH4+ were carried out. The results demonstrated the suitability of the DCHQ optodes to perform fast monitoring (<10s) of magnesium (II) ions. Emission light signal was sufficiently brilliant to be captured by a low-cost computer webcam. The phenyl-substituted DCHQ-Ph derivative showed the best performance with a wide range for Mg(II) ion determination between 2.7 × 10-7 and 2.2 × 10-2 mol/L. It was possible, therefore, to determine the concentrations of Mg(II) in commercial fertilizer samples by DCHQ-Ph-based optodes with acceptable results: recoveries of 96.2-104.9% and relative standard deviation (RSD, n = 6) less than 5%. Moreover, in comparison to single sensors, the use of an array composed of five optodes (the ones showing the best performances in the preliminary tests) has allowed to reduce the RSD of magnesium determination in real samples (down to 3.7% with respect to 5.5% for single optodes) and to achieve a detection limit (estimated by s/n = 3 method) as low as 4.6 × 10-7 mol/L.

Three-point multivariate calibration models by correlation constrained MCR-ALS: A feasibility study for quantitative analysis of complex mixtures.

When it comes to address quantitative analysis in complex mixtures, Partial Least Squares (PLS) is often referred to as a standard first-order multivariate calibration method. The set of samples used to build the PLS regression model should ideally be large and representative to produce reliable predictions. In practice, however, the large number of calibration samples is not always affordable and the choice of these samples should be handled with care as it can significantly affect the accuracy of the predictive model. Correlation constrained multivariate curve resolution (CC-MCR) is an alternative regression method for first-order datasets where, unlike PLS, calibration and prediction stages are performed iteratively and optimized under constraints until the decomposition meets the convergence criterion. Both calibration and test samples are fitted into a unique bilinear model so that the number of calibration samples is no longer a critical issue. In this paper we demonstrate that under certain conditions CC-MCR models can provide for reasonable predictions in quantitative analysis of complex mixtures even when only three calibration samples are employed. The latter are defined as samples having the minimum, the maximum and the average concentration, providing for a simple and rapid strategy to build reliable calibration model. The feasibility of three-point multivariate calibration approach was assessed with several case studies featuring mixtures of different analytes in presence of interfering species. Satisfactory predictions with relative errors in the range 3-15% were achieved and good agreement with classical PLS models built from a larger set of calibration samples was observed.

Electronic tongue for microcystin screening in waters.

The potentiometric E-tongue system was employed for water toxicity estimation in terms of cyanobacterial microcystin toxins (MCs) detection. The data obtained from E-tongue were correlated to the MCs content detected by the standard chromatographic technique UHPLC-DAD (Ultra High Performance Liquid Chromatography with Diode Array Detector), as far as by the colorimetric enzymatic approach. The prediction of MCs released by toxic Microcystis aeruginosa strains was possible with Root Mean Squared Error of Validation (RMSEV) lower or very close to 1µg/L, the provisional guideline value of WHO for MCs content in potable waters. The application of E-tongue system opens up a new perspective offset for fast and inexpensive analysis in the field of environmental monitoring, offering also the possibility to distinguish toxin producing and non-toxic M. aeruginosa strains present in potable water.

Multi-scale imaging of anticancer platinum(iv) compounds in murine tumor and kidney.

Nano-scale secondary ion mass spectrometry (NanoSIMS) enables trace element and isotope analyses with high spatial resolution. This unique capability has recently been exploited in several studies analyzing the subcellular distribution of Au and Pt anticancer compounds. However, these studies were restricted to cell culture systems. To explore the applicability to the in vivo setting, we developed a combined imaging approach consisting of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), NanoSIMS and transmission electron microscopy (TEM) suitable for multi-scale detection of the platinum distribution in tissues. Applying this approach to kidney and tumor samples upon administration of selected platinum(iv) anticancer prodrugs revealed uneven platinum distributions on both the organ and subcellular scales. Spatial platinum accumulation patterns were quantitatively assessed by LA-ICP-MS in histologically heterogeneous organs (e.g., higher platinum accumulation in kidney cortex than in medulla) and used to select regions of interest for subcellular-scale imaging with NanoSIMS. These analyses revealed cytoplasmic sulfur-rich organelles accumulating platinum in both kidney and malignant cells. Those in the tumor were subsequently identified as organelles of lysosomal origin, demonstrating the potential of the combinatorial approach for investigating therapeutically relevant drug concentrations on a submicrometer scale.

Evaluation of the feasibility of the electronic tongue as a rapid analytical tool for wine age prediction and quantification of the organic acids and phenolic compounds. The case-study of Madeira wine.

A set of fourteen Madeira wines comprising wines produced from four Vitis vinifera L. varieties (Bual, Malvasia, Verdelho and Tinta Negra Mole) that were 3, 6, 10 and 17 years old was analysed using HPLC and an electronic tongue (ET) multisensor system. Concentrations of 24 organic acids, phenolic and furanic compounds were determined by HPLC. The ET consisting of 26 potentiometric chemical sensors with plasticized PVC and chalcogenide glass membranes was used. Significance of the effects of age and variety on the ET response and wine composition with respect to the organic acids, phenolics and furanic derivatives were evaluated using ANOVA-Simultaneous Component Analysis (ASCA). Significance of the effects was estimated using a permutation test (1000 permutations). It was found that effects of age, grape variety and their interaction were significant for the HPLC data set and only the effect of age was significant for the ET data. Calibration models of the HPLC and ET data with respect to the wine age and of the ET data with respect to the concentration of the organic acids and phenolics were calculated using PLS1 regression. Models were validated using cross-validation. It was possible to predict wine age from HPLC and ET data with the accuracy in cross-validation of 2.6 and 1.8 years respectively. The ET was capable of detecting the following components (mean relative error in cross-validation is shown in the parentheses): tartaric (8%), citric (5%), formic (12%), protocatehuic (5%), vanillic (18%) and sinapic (14%) acids, catechin (6%), vanillin (12%) and trans-resveratrol (5%). The ET capability of predicting Madeira wine age with good accuracy (1.8 years) as well as quantify of some organic acids and phenolic compounds was demonstrated.

Study of the influence of micro-oxygenation and oak chip maceration on wine composition using an electronic tongue and chemical analysis.

The influence of micro-oxygenation (MOX) and maceration with oak chips treatments on wine was studied on wine samples from three vintages produced in the Yarra Valley, Australia. A full factorial design was employed where two factors (MOX and oak chips treatments) had two levels and one factor (vintage) had three levels. Three replicated treatments were run for each factor's setting. Wine samples were analysed using conventional laboratory methods with respect to the phenolic wine compounds and colour attributes since the phenolic fraction of wine is most affected by both MOX and oak maceration treatments. The same wine samples were measured with an electronic tongue based on potentiometric chemical sensors. The significance of treatments and vintage effects on wine phenolic compounds was assessed using ANOVA and ANOVA-Simultaneous Component Analysis (ASCA). Cross-validation was used for the ASCA sub-model optimisations and permutation test for evaluations of the significance of the factors. Main effects of vintage and maceration with oak chips were found to be significant for both physicochemical and the ET data. Main effect of MOX treatment was also found significant for the physicochemical parameters. The largest effect on the phenolic composition of wine was due to its vintage, which accounted for 70% and 33% of total variance in the physicochemical and ET data respectively. The ET was calibrated with respect to the total phenolic content, colour density and hue and chemical ages 1 and 2 and could predict these parameters of wine with good precision.

Cross-sensitive rare-earth metal sensors based on bidentate neutral organophosphorus compounds and chlorinated cobalt dicarbollide.

A variety of new chemical sensors (ion selective electrodes) for determination of rare-earth (RE) and trivalent metal cations such as yttrium(III), lanthanum(III), praseodymium(III), neodymium(III) and europium(III) that are commonly present in aqueous radiological samples, e.g. in high-level liquid waste (HLW) and solutions from reprocessing spent nuclear fuel, have been developed and studied. The sensors are based on bidentate neutral organophosphorus compounds, such as methylene bridged diphosphine dioxides and carbamoylmethylphosphine oxides, which are efficient extractants, especially when used in conjunction with chlorinated cobalt dicarbollide, for recovery and concentration of the RE and actinide elements from acidic HLW derived from the nuclear fuel cycle. The sensors exhibit remarkable sensitivity to RE cations and indicate promise for HLW analysis.

Differentiation of four Aspergillus species and one Zygosaccharomyces with two electronic tongues based on different measurement techniques.

Two electronic tongues based on different measurement techniques were applied to the discrimination of four molds and one yeast. Chosen microorganisms were different species of Aspergillus and yeast specie Zygosaccharomyces bailii, which are known as food contaminants. The electronic tongue developed in Linköping University was based on voltammetry. Four working electrodes made of noble metals were used in a standard three-electrode configuration in this case. The St. Petersburg electronic tongue consisted of 27 potentiometric chemical sensors with enhanced cross-sensitivity. Sensors with chalcogenide glass and plasticized PVC membranes were used. Two sets of samples were measured using both electronic tongues. Firstly, broths were measured in which either one of the molds or the yeast grew until late logarithmic phase or border of the stationary phase. Broths inoculated by either one of molds or the yeast was measured at five different times during microorganism growth. Data were evaluated using principal component analysis (PCA), partial least square regression (PLS) and linear discriminant analysis (LDA). It was found that both measurement techniques could differentiate between fungi species. Merged data from both electronic tongues improved differentiation of the samples in selected cases.

Multicomponent analysis of fermentation growth media using the electronic tongue (ET).

A potentiometric electronic tongue (ET) consisting of eight cross-sensitive chemical sensors and a standard pH electrode has been applied for analysis of simulated fermentation solutions typical for fermentation processes with Aspergillus niger. The electronic tongue has been found capable of simultaneous determination of ammonium, citrate and oxalate in complex media with good precision (typical error within 8%). The system preserved high sensitivity to the targeted substances also in the presence of sodium azide, which is commonly used for suppressing microbial activity in real-world fermentation samples. Sensor performance was fast and reproducible which promises well for routine application of the electronic tongue for fermentation process monitoring.

Multisensor system on the basis of an array of non-specific chemical sensors and artificial neural networks for determination of inorganic pollutants in a model groundwater.

The application of a multisensor system to groundwater monitoring is investigated. The sensor system is based on an array of non-specific potentiometric chemical sensors with data processing by artificial neural networks and includes 13 sensors with PVC membranes and 12 solid-state ones. Results of measurements in model solutions containing heavy metals, alkali- and alkali-earth cations and inorganic anions at concentrations typical for groundwater near the city of Braunschweig, Germany, are presented. Both the response of the whole sensor array and the responses of subsystems consisting only of PVC and only of solid-state sensors, respectively, are investigated. It is shown that both subsystems can be used for determination of described ions and that the best results are obtained if the whole array of sensors is used.

Chalcogenide glass chemical sensors: Research and analytical applications.

The paper is devoted to research and development in the field of chalcogenide glass chemical sensors for determination of heavy metal ions in solution. The overview of the solid-state scientific approach and research design of the sensing materials is followed by the original results of the analytical application of the chalcogenide glass sensors for laboratory analysis, industrial control and environmental monitoring.