New approach to unsupported ReS2 nanorod catalyst for upgrading of heavy crude oil using methane as hydrogen source

Highly active ReS₂ nanocatalysts were prepared by CVD method and characterized by XRD, BET -BJH, Raman spectroscopy, XPS, TPR, NH₃-TPD, SEM, and HRTEM techniques. Catalytic activities were used in upgrading heavy crude oil using methane as hydrogen source. The results showed a significant increase in API and decrease in sulfur and nitrogen content of crude oil. RSM technique was used to investigate the interactive effects of temperature (200–400 °C), pressure (20–40 bar) and dosage of nanocatalyst (0.5–2 wt. %) on the performance of HDS reaction. The results represent that the maximum predicted HDS activity (74.375%) was estimated under the optimal conditions (400 °C, 20 bars, and 2 wt % of nanocatalyst). Also, the effect of reaction temperature, pressure and dosage of ReS₂ nanorods catalyst on HDN of heavy crude oil was investigated and highest efficiency in the HDN process (93%) occurred at 400 °C and 40 bar using 2 wt % ReS₂.     

Characterization of titania thin films grown by dip-coating technique

A dip-coating technique was employed to prepare anatase phase of titania thin films. Fluorine doped tin oxide substrates were used to prepare titania thin films. The samples were annealed at 550 °C for 18 h. X-ray diffraction results revealed the amorphous and anatase phases of TiO₂ for as-synthesized and annealed samples, respectively. The crystallite size of anatase TiO₂ thin films was almost 25 nm for annealed samples. UV–visible confirmed the energy band gap 3.86 and 3.64 eV for as-prepared and calcinated titania thin films. The reduction in the energy band gap could be due to the change in crystallization and agglomeration of small grains after calcination. The morphology of the prepared films was investigated by field emission scanning electron microscopy which demonstrated the agglomeration of spherical particles of TiO₂ with average particle size of about 30 nm. The molecular properties (chemical bonding) of the samples were investigated by means of Fourier Transform Infrared (FTIR) spectroscopy. FTIR analysis exhibited the formation of titania, functional group OH, hydroxyl stretching vibrations of the C–OH groups, bending vibration mode of H–O–H, alkyl C–H stretch, stretching band of Ti–OH, CN asymmetric band stretching, and C=O saturated aldehyde.     

Biosynthesised AgCl NPs using Bacillus sp. 1/11 and evaluation of their cytotoxic activity and antibacterial and antibiofilm effects on multi‐drug resistant bacteria

Silver nanoparticles (AgNPs) have attracted the attention of researchers due to their properties. Biological synthesis of AgNPs is eco‐friendly and cost‐effective preferred to physical and chemical methods, which utilize environmentally harmful agents and large amounts of energy. Microorganisms have been explored as potential biofactories to synthesize AgNPs. Bacterial NP synthesis is affected by Ag salt concentration, pH, temperature and bacterial species. In this study, Bacillus spp., isolated from soil, were screened for AgNP synthesis at pH 12 with 5 mM Ag nitrate (AgNO₃) final concentration at room temperature. The isolate with fastest color change and the best ultraviolet‐visible spectrum in width and height were chosen as premier one. AgNO₃ and citrate salts were compared in terms of their influence on NP synthesis. Spherical Ag chloride (AgCl) NPs with a size range of 35–40 nm were synthesized in 1.5 mM Ag citrate solution. Fourier transform infrared analysis demonstrated that protein and carbohydrates were capping agents for NPs. In this study, antimicrobial and antitumor properties of the AgNP were investigated. The resulting AgCl NPs had bacteriostatic activity against four standard spp. And multi‐drug resistant strain of Pseudomonas aeruginosa. These NPs are also cytotoxic to cancer cell lines MCF‐7, U87MG and T293.Inspec keywords: silver compounds, nanoparticles, nanomedicine, nanofabrication, particle size, biomedical materials, microorganisms, ultraviolet spectra, visible spectra, Fourier transform infrared spectra, proteins, macromolecules, antibacterial activity, tumours, cancer, cellular biophysics, toxicologyOther keywords: citrate salts, spherical Ag chloride, particle size, Ag citrate solution, Fourier transform infrared analysis, protein, carbohydrates, capping agents, antitumour properties, bacteriostatic activity, Pseudomonas aeruginosa, multidrug resistant strain, cancer cell lines MCF‐7,U87MG, size 35 nm to 40 nm, temperature 293 K to 298 K, AgCl, ultraviolet‐visible spectrum, colour change, room temperature, Ag nitrate final concentration, soil, bacterial species, temperature effect, pH, Ag salt concentration, biofactories, microorganisms, environmentally harmful agents, chemical methods, physical methods, antibacterial properties, electrical properties, mechanical properties, silver nanoparticles, multidrug resistant bacteria, antibiofilm effects, antibacterial effects, cytotoxic activity, Bacillus sp. 1/11, biosynthesised AgCl NPs     

A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality

Managing service quality is vital to retain customer satisfaction and augment revenues for any business organization. Often it is difficult to assess service quality due to lack of quantifiable measures and limited data. In this paper, we present a hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating service quality of urban transportation systems. The proposed approach consists of three steps. The first step involves development of a SERVQUAL based questionnaire to collect data for measuring transportation service quality. The participants provide linguistic assessments to rate the service quality criteria and the alternatives. In step 2, the linguistic ratings are combined through fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is finally chosen. In step 3, sensitivity analysis is conducted to evaluate the influence of criteria weights on the decision making process.The strength of the proposed approach is its practical applicability and ability to provide solution under partial or lack of quantitative information. An application of the proposed approach for evaluation of service quality of metro in Montreal is provided.     

Predicting the spontaneous termination of atrial fibrillation based on poincare section in the electrocardiogram phase space

Atrial fibrillation (AF) is a commonly encountered cardiac arrhythmia. Predicting the conditions under which AF terminates spontaneously is an important task that would bring great benefit to both patients and clinicians. In this study, a new method was proposed to predict spontaneous AF termination by employing the points of section (POS) coordinates along a Poincare section in the electrocardiogram (ECG) phase space. The AF Termination Database provided by PhysioNet for the Computers in Cardiology Challenge 2004 was applied in the present study. It includes one training dataset and two testing datasets, A and B. The present investigation was initiated by producing a two-dimensional reconstructed phase space (RPS) of the ECG. Then, a Poincare line was drawn in a direction that included the maximum point distribution in the RPS and also passed through the origin of the RPS coordinate system. Afterward, the coordinates of the RPS trajectory intersections with this Poincare line were extracted to capture the local behavior related to the arrhythmia under investigation. The POS corresponding to atrial activity were selected with regard to the fact that similar ECG morphologies such as P waves, which are corresponding to atrial activity, distribute in a specific region of the RPS. Thirteen features were extracted from the selected intersection points to quantify their distributions. To select the best feature subset, a genetic algorithm (GA), in combination with a support vector machine (SVM), was applied to the training dataset. Based on the selected features and trained SVM, the performance of the proposed method was evaluated using the testing datasets. The results showed that 86.67% of dataset A and 80% of dataset B were correctly classified. This classification accuracy is in the same range as or higher than that of recent studies in this area. These results show that the proposed method, in which no complicated QRST cancelation algorithm was used, has the potential to predict AF termination.     

In situ solvent formation microextraction based on a new ionic liquid for green preconcentration of trace amount of Cu (II) ions in water samples

A simple, fast, and effective analytical technique known as in situ solvent formation microextraction was used to preconcentrate/separate trace amounts of Cu(II) ions in water samples prior to determination by flame atomic absorption spectroscopy. In the present method, 6,6′-(1Z,1′Z)(butane-1,4-diylbis(azan-1-yl-1-ylidene)bis(methan-1-yl-1-ylidene)bis-3-bromophenol (Schiff base ligand) as the complexing agent and 1-methyl-3-pentylimidazolium bromide (ionic liquid) as an extracting agent were successfully synthesized and characterized by FTIR, C-NMR, and H-NMR spectroscopies. The effects of several analytical parameters on the method were studied and optimized, and the merits of the method, such as LDR (0.2–1000 µg L^?1), LOD (0.12 µg L^?1), RSD (4.1%), and preconcentration factor (70) were evaluated.     

Self-Consistent Model for Planar Ferrite Growth in Fe-C-X Alloys

A self-consistent model for non-partitioning planar ferrite growth from alloyed austenite is presented. The model captures the evolution with time of interfacial contact conditions for substitutional and interstitial solutes. Substitutional element solute drag is evaluated in terms of the dissipation of free energy within the interface, and an estimate is provided for the rate of buildup of the alloying element “spike” in austenite. The transport of the alloying elements within the interface region is modeled using a discrete-jump model, while the bulk diffusion of C is treated using a standard continuum treatment. The model is validated against ferrite precipitation and decarburization kinetics in the Fe-Ni-C, Fe-Mn-C, and Fe-Mo-C systems.     

Application of artificial neural network for vapor liquid equilibrium calculation of ternary system including ionic liquid: Water, ethanol and 1-butyl-3-methylimidazolium acetate

A feed forward three-layer artificial neural network (ANN) model was developed for VLE prediction of ternary systems including ionic liquid (IL) (water+ethanol+1-butyl-3- methyl-imidazolium acetate), in a relatively wide range of IL mass fractions up to 0.8, with the mole fractions of ethanol on IL-free basis fixed separately at 0.1, 0.2, 0.4, 0.6, 0.8, and 0.98. The output results of the ANN were the mole fraction of ethanol in vapor phase and the equilibrium temperature. The validity of the model was evaluated through a test data set, which were not employed in the training case of the network. The performance of the ANN model for estimating the mole fraction and temperature in the ternary system including IL was compared with the non-random-two-liquid (NRTL) and electrolyte non-random-two-liquid (eNRTL) models. The results of this comparison show that the ANN model has a superior performance in predicting the VLE of ternary systems including ionic liquid.     

A crossover‐UNIQUAC model for critical and noncritical LLE calculations

A new model, named the crossover‐UNIQUAC model, has been proposed based on the crossover procedure for predicting constant‐pressure liquid–liquid equilibria (LLE). In this manner, critical fluctuations were incorporated into the classical UNIQUAC equation. Coexistence curves were estimated for systems having a diverse range of asymmetries. These systems included the LLE of five different mixtures, composed of nitrobenzene with one of the members of the alkane homologous family (either pentane, octane, decane, dodecane, or tetradecane), as well as an extra system having a different chemical nature, namely the mixture of n‐perfluorohexane and hexane, to further check the validity of the proposed approach. Using these nonideal mixtures, the validity of the new model was investigated within wide ranges, covering near‐critical to regions falling far away from the critical point. The graphical trends, as well as the quantitative comparison with experimental data indicated the good agreement of the proposed model results with the experimental data. A maximum AARD% value of 3.97% was obtained in calculating molar compositions by the proposed model for such challenging systems covering noncritical, as well as critical regions. In addition, to show the strength of the proposed crossover approach to describe properties other than LLE, molar heat capacities were investigated for the system of nitrobenzene + dodecane. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3094–3103, 2015