On-line electrochemically controlled in-tube solid phase microextraction of inorganic selenium followed by hydride generation atomic absorption spectrometry

In this work, for the first time, a rapid, simple and sensitive microextraction procedure is demonstrated for the matrix separation, preconcentration and determination of inorganic selenium species in water samples using an electrochemically controlled in-tube solid phase microextraction (EC-in-tube SPME) followed by hydride generation atomic absorption spectrometry (HG-AAS). In this approach, in which EC-in-tube SPME and HG-AAS system were combined, the total analysis time, was decreased and the accuracy, repeatability and sensitivity were increased. In addition, to increases extraction efficiency, a novel nanostructured composite coating consisting of polypyrrole (PPy) doped with ethyleneglycol dimethacrylate (EGDMA) was prepared on the inner surface of a stainless-steel tube by a facile electrodeposition method. To evaluate the offered setup and the new PPy-EGDMA coating, it was used to extract inorganic selenium species in water samples. Extraction of inorganic selenium species was carried out by applying a positive potential through the inner surface of coated in-tube under flow conditions. Under the optimized conditions, selenium was detected in amounts as small as 4.0 parts per trillion. The method showed good linearity in the range of 0.012–200 ng mL⁻¹, with coefficients of determination better than 0.9996. The intra- and inter-assay precisions (RSD%, n = 5) were in the range of 2.0–2.5% and 2.7–3.2%, respectively. The validated method was successfully applied for the analysis of inorganic selenium species in some water samples and satisfactory results were obtained.     

Synthesis of Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>@PPy–MWCNT nanocomposite and its application for extraction of ultra-trace amounts of PAHs from various samples

In the present study, multi-walled carbon nanotube oxide was immobilized on the pyrrole magnetic nanoparticles. Application of the synthesized material was investigated for the magnetic solid-phase extraction (MSPE) of polycyclic aromatic hydrocarbons (PAHs), from the environmental samples. Determinations of the analytes were performed with gas chromatography–mass spectrometry. The structure and morphology of Fe₃O₄@PPy–MWCNT were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, thermal gravimetric analysis, and vibrating sample magnetometer. Performance of MSPE is mainly affected by extraction time, sorbent amount, sample solution volume, and eluent type and volume. In this study, the best possible performance of MSPE has been achieved using a combination of central composite design and Bayesian regularized artificial neural network technique. Under the optimum extraction conditions, linear range between 0.5 and 250 µg L^?1 (R ² > 0.994), preconcentration factors from 232 to 403 and limits of detection ranging from 0.1 to 0.3 µg L^?1 were obtained. Relative standard deviations for intra-day and inter-day precision were 3.3–5.1% and 3.7–5.6%, respectively. In addition, feasibility of the method was demonstrated by extraction and determination of PAHs from some real samples containing tap water, hookah water as well as soil samples, and relative recovery in the range of 85.4–106.8% was obtained. This MSPE method provides several advantages, such as high extraction efficiency, minimum sorbent for extraction of the analytes from high sample volumes, convenient extraction procedure, and short analysis times.     

LDPE/EVA/graphene nanocomposites with enhanced mechanical and gas permeability properties

In the present work, graphene oxide (GO) and reduced graphene oxide (RGO) were incorporated at low‐density polyethylene (LDPE)/ethylene vinyl acetate (EVA) copolymer blend using solution casting method. Monolayer GO with 1‐nm thickness and good transparency was synthesized using the well‐known Hummers's method. Fourier transform infrared and X‐ray photoelectron spectroscopy data exhibited efficient reduction of GO with almost high C/O ratio of RGO. Scanning electron microscopy showed the well distribution of GO and RGO within LDPE/EVA polymer matrix. The integrating effects of GO and RGO on mechanical and gas permeability of prepared films were examined. Young's modulus of nanocomposites are improved 65% and 92% by adding 7 wt% of GO and RGO, respectively. The tensile measurements showed that maximum tensile strength emerged in 3 wt% of loading for RGO and 5 wt% for GO. The measured oxygen and carbon dioxide permeability represented noticeably the attenuation of gas permeability in composite films compared with pristine LDPE/EVA blend. Copyright © 2015 John Wiley & Sons, Ltd.     

Correction to: 1H-imidazol-3-ium tricyanomethanide {[HIM]C(CN)3} as a nanostructured molten salt catalyst: application to the synthesis of pyrano[4,3‐b]pyrans

Research on Chemical Intermediates - Since it has been cleared that a fake compound has been sold to us as cyanoform.     

Intra-group and inter-group trading differentiation analysis: A new approach for detecting the effect of trading volume on stock market fluctuations

Analyzing statistical properties of stock market data using statistical physics has received much attention from physicists and economists in recent years. Although some statistical characteristics of stock market data such as power-low tails of stock returns have become established fact, behavior of other related variables such as trading volume are less studied. In this paper, in order to examine the impact of trading volume on statistical properties of stock market returns, different trading behavior of different traders in Tehran Stock Exchange is analyzed. We define a new coefficient which measures the equilibrium between these different forces affecting the market at any given trading day. By adjusting market returns by this coefficient, we also assessed the impact of these forces on the statistical properties of stock market returns.     

Numerical study on the effect of the injection pressure on spray penetration length

This paper investigates the fuel spray behavior and variation of the spray characteristics under different injection pressures in internal combustion engines. In diesel engines the fuel spray is affected by the cavitation phenomenon which occurs in the injector orifice. The cavitation is one of the important phenomena which has a significant effect on the fuel spray characteristics. In this paper, for a specified geometry of the nozzle and the combustion chamber, the effect of the cavitation phenomenon on the spray characteristics, i.e. spray penetration length, the Sauter main diameter and evaporation are studied numerically for different values of the injection pressures. High injection pressure causes high velocity of the fuel in the injector orifice which leads to an effective atomization process with small and dispersed fuel droplets. The fluid flow equations are calculated in the combustion chamber to obtain the spray model. Since it is known that, high injection pressure together with low discharge pressure leads to creation of cavitation phenomenon inside the injector orifice, then for having cavitation phenomenon inside the injector orifice and consequently for investigating the cavitation phenomenon effects on the spray characteristics, the injection pressure values of 10–150 MPa are considered while the discharge pressure remains constant. The injector and combustion chamber are simulated in separated regions and the results of the outlet of the nozzle are used as the boundary conditions for solving the fuel flow inside the combustion chamber to achieve the spray simulation. The results of this study show that by increasing the injection pressure, the value of the spray penetration length increases and the Sauter main diameter decreases for constant discharge pressure. The Hydraulic Flip phenomenon occurs after the injection pressure of 120 MPa on the base of the results of this work.     

A locally linear neuro-fuzzy model for supplier selection in cosmetics industry

Supplier selection and evaluation is a complicated and disputed issue in supply chain network management, by virtue of the variety of intellectual property of the suppliers, the several variables involved in supply demand relationship, the complex interactions and the inadequate information of suppliers. The recent literature confirms that neural networks achieve better performance than conventional methods in this area. Hence, in this paper, an effective artificial intelligence (AI) approach is presented to improve the decision making for a supply chain which is successfully utilized for long-term prediction of the performance data in cosmetics industry. A computationally efficient model known as locally linear neuro-fuzzy (LLNF) is introduced to predict the performance rating of suppliers. The proposed model is trained by a locally linear model tree (LOLIMOT) learning algorithm. To demonstrate the performance of the proposed model, three intelligent techniques, multi-layer perceptron (MLP) neural network, radial basis function (RBF) neural network and least square-support vector machine (LS-SVM) are considered. Their results are compared by using an available dataset in cosmetics industry. The computational results show that the presented model performs better than three foregoing techniques.     

Improvement of the thermoelectric efficiency of pyrene-based molecular junction with doping engineering

In this study, the thermoelectric properties of pyrene molecule doped with boron and nitrogen atom at different sites of molecule are investigated using density functional theory and none-equilibrium Green's function formalism in the linear response regime. Our calculations show that when the impurities are added to the edge of the molecule, the anti-resonant peaks will appear in the transmission diagram in the vicinity of the Fermi energy level. So it increases the thermoelectric figure of merit of the system in comparison with the one that the impurity is located in the center of molecule. Additionally,the seebeck coefficient signs are not the same among the B, N, and N B doped devices, indicating that the types of the carriers can be changed with different types of doping.