Trace amounts determination of lead,zinc and copper by adsorptive stripping voltammetry in the presence of dopamine

A selective and sensitive method for simultaneous determination of lead, zinc and copper by adsorptive differential pulse cathodic stripping voltammetry is presented. The method is based on adsorptive accumulation of the complexes of Pb(II), Zn(II), and Cu(II) ions with dopamine onto hanging mercury drop electrode (HMDE), followed by reduction of adsorbed species by differential pulse cathodic stripping voltammetry. The effect of experimental parameters such as pH, dopamine concentration, accumulation time and potential and scan rate were examined. Under the optimized conditions, linear calibration curves were established for the concentration of Pb, Zn, and Cu in the ranges of 5–150, 5–250, and 1–150 ng/mL, respectively. Detection limits of 0.06, 0.25, and 0.04 ng/mL for Pb, Zn, and Cu were obtained. An application of the proposed method is reported for the determination of these elements in some real samples such as natural waters and alloys.     

Metallation of tetradentate N<Subscript>2</Subscript>O<Subscript>2</Subscript> Schiff base with Mn(II), Co(II), Cu(II) and Zn(II): synthesis,characterization and formation constants measurement

Four Schiff base ligands, salabza-H₂ = N,N′-bis(salicylidene)-2-aminobenzylamine, were synthesized by condensation of one mole of 2-aminobenzylamine and two moles of salicylaldehyde and/or two moles of substituted salicylaldehyde (5-OMe, 5-Br, 5-NO₂). All the four Schiff bases and their Mn(II), Co(II), Cu(II) and Zn(II) complexes are characterized by UV-Vis, FT-IR, ¹H NMR spectroscopy, mass spectrometry and elemental analysis. The formation constants and the Gibbs free energies were measured spectrophotometrically for 1:1 complexes in methanol in constant ionic strength (I = 0.1 mol dm⁻³ NaClO₄) and at 25°C. The data refinement was carried out with the SQUAD program. The trend of formation constants of H₂L¹ with M(II) follows the order: Mn(II) (3.97) < Zn(II) (4.30) < Co(II) (4.89) < Cu(II) (5.73)     

Determination of non-steroidal anti-inflammatory drugs in sewage sludge by direct hollow fiber supported liquid membrane extraction and liquid chromatography–mass spectrometry

In this study, a three-phase hollow fiber liquid-phase microextraction (HF-LPME) method combined with liquid chromatography–mass spectrometry was developed for direct determination of four non-steroidal anti-inflammatory drugs (ketoprofen, naproxen, diclofenac and ibuprofen) in sewage sludge. The drugs were extracted from non-spiked and spiked slurry samples with different amounts of sludge into an organic phase and then back-extracted into an aqueous phase held in the lumen of the hollow fiber. High enrichment factors ranging from 2761 to 3254 in pure water were achieved. In sludge samples, repeatability and inter-day precision were tested with relative standard deviation values between 10–18% and 7–15%, respectively. Average concentrations of 29 ± 9, 138 ± 2, 39 ± 5 and 122 ± 7 ng/g were determined in dried sludge from Källby sewage treatment plant (Sweden) for ketoprofen, naproxen, diclofenac and ibuprofen, respectively.     

Effect of Copper Substitution and Preparation Methods on the LaMnO3 Structure and Catalysis of Methane Combustion and CO Oxidation

 LaMn1-xCuxO3刡冊 perovskite oxides (x = 0, 0.2, 0.4, 0.6, 0.8, 1) were prepared by two different methods, the Pechini and sol-gel methods. The catalysts were characterized by Fourier transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), X-ray fluorescence spectroscopy, N2 adsorption, and temperature-programmed reduction. Their catalytic activity in the oxidation of methane and CO was evaluated. EDS and SEM results showed that the Pechini samples had more homogeneity and smaller particles (higher specific surface area). The catalytic activity for methane combustion was highest for x = 0.2. In CO oxidation, the oxides with x = 0.2 and x = 0.4 were the most active. The Pechini samples had higher activity and stability than the sol-gel samples.     

Sonochemical syntheses of a new nano-plate cadmium(II) coordination polymer as a precursor for the synthesis of cadmium(II) oxide nanoparticles

Nanoplates of the three-dimensional coordination polymer, {[Cd(3)(3-pyc)(4)(N(3))(2)(H(2)O)](n) (1), 3-pyc(-)=pyridine-3-carboxylate), have been synthesized by a sonochemical process and characterized by scanning electron microscopy, X-ray powder diffraction, IR spectroscopy and elemental analyses. Cadmium(II) oxide nanoparticles were prepared from thermal decomposition in oleic acid and direct calcination of compound 1 at different temperatures. The thermal stability of nano-sized compound 1 was studied by thermal gravimetric (TG) and differential thermal analyses (DTA). Results show that the size and morphology of the CdO nanoparticles are dependent upon the particles size of compound 1 and the thermolysis temperature. A decrease in the particle size of compound 1 leads to a decrease in the particle size of the CdO, while an increase in the processing temperature leads to an increase in the particle size of the produced cadmium(II) oxide nano-particles.     

Effect on photophysical properties of colloidal ZnS quantum dots by doping with cobalt, copper, and cobalt�Ccopper mixtures

Colloidal ZnS quantum dots (QDs) are prepared by passing H₂S gas through a solution of Zn(CH₃COO)₂ in acetonitrile. Photophysical properties are investigated using UV?CVisible and photoluminescence (PL) spectroscopy. The spectrum shows an absorption shoulder at 271 nm representing a band gap of 4.6 eV. The doping of ZnS QDs with Co, Cu, and a mixture of Co and Cu not only increased the band gap to 0.2 eV but also turns these otherwise colorless QDs to blue in color due to cobalt, and green due to Cu. The observed emission in the visible region suggests that the dopants may have induced additional excited states to the ZnS QDs. This absorbance in the visible region can be utilized in the optoelectronic applications.     

Fabrication, characterization, and measurement of viscosity of α-Fe2O3-glycerol nanofluids

Magnetic nanofluids, ferrofluids, are a special category of smart nanomaterials, consisting of stable dispersion of magnetic nanoparticles in different fluids. In this study, magnetic nanoparticles of hematite, α-Fe₂O₃, were prepared by solvothermal method using Fe(NO₃)₃ as a starting material. The nanoparticles were characterized by X-ray diffraction (XRD) and transmission electronic microscope (TEM).To the best of our knowledge, this is the first research on the rheological properties of nanofluids of α-Fe₂O₃ nanoparticles and glycerol. The experimental results showed that the viscosity of α-Fe₂O₃-glycerol nanofluids increases with increasing the particle volume fraction and decreases with increasing temperature. Our results clearly showed that the α-Fe₂O₃-glycerol nanofluids are non-Newtonian shear-thinning and their shear viscosity depends strongly on temperature. The experimental data were compared with some theoretical models. The measured values of the effective viscosity of nanofluids are underestimated by the theoretical models.     

Estimation of mutual information by the fuzzy histogram

Mutual Information (MI) is an important dependency measure between random variables, due to its tight connection with information theory. It has numerous applications, both in theory and practice. However, when employed in practice, it is often necessary to estimate the MI from available data. There are several methods to approximate the MI, but arguably one of the simplest and most widespread techniques is the histogram-based approach. This paper suggests the use of fuzzy partitioning for the histogram-based MI estimation. It uses a general form of fuzzy membership functions, which includes the class of crisp membership functions as a special case. It is accordingly shown that the average absolute error of the fuzzy-histogram method is less than that of the naïve histogram method. Moreover, the accuracy of our technique is comparable, and in some cases superior to the accuracy of the Kernel density estimation (KDE) method, which is one of the best MI estimation methods. Furthermore, the computational cost of our technique is significantly less than that of the KDE. The new estimation method is investigated from different aspects, such as average error, bias and variance. Moreover, we explore the usefulness of the fuzzy-histogram MI estimator in a real-world bioinformatics application. Our experiments show that, in contrast to the naïve histogram MI estimator, the fuzzy-histogram MI estimator is able to reveal all dependencies between the gene-expression data.     

Evaluation of fuzzy regression models by fuzzy neural network

In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy linear and nonlinear regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.