Cobalt promoted Ni/MgAl2O4 catalyst in lean methane catalytic oxidation

In the present research, magnesium aluminate spinel was prepared as catalyst support using a novel, facile, and efficient mechanochemical method. The Co-promoted catalysts with 20 wt.% of Ni were fabricated using an impregnation route and the samples were analyzed by the X-ray diffraction (XRD), N₂ adsorption/desorption (BET), temperature-programmed reduction and desorption (H₂-TPR and O₂-TPD), and field emission scanning electron microscopy (FESEM) tests. The results confirmed that all samples have a mesoporous structure with a high specific surface area and the presence of cobalt caused complete CH₄ oxidation at low temperatures, and no side reactions were observed. The results indicated that the 3%Co-20%Ni/MgAl₂O₄ catalyst was the optimal sample among the prepared catalysts, owing to the improvement of reduction features and oxygen mobility. The 50 and 90% of methane conversion was obtained at 530 and 600 °C, respectively. Also, the influence of calcination temperature, GHSV, and feed ratio was determined on the catalytic activity. The obtained outcomes revealed that the calcination temperature has a significant effect on the textural properties and catalytic efficiency. The sample calcined at 700 °C showed the weakest performance, which was related to the sintering of particles at high temperatures. The catalytic stability showed that the 3%Co-20%Ni/MgAl₂O₄ has acceptable stability during 600 min time of reaction.

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Patterns and Symmetries in the Visual Cortex and in Natural Images

As borders between different entities, lines are an important element of natural images. Indeed, the neurons of the mammalian visual cortex are tuned to respond best to lines of a given orientation. This preferred orientation varies continuously across most of the cortex, but also has vortex-like singularities known as pinwheels. In attempting to describe such patterns of orientation preference, we are led to consider underlying rotation symmetries: Oriented segments in natural images tend to be collinear; neurons are more likely to be connected if their preferred orientations are aligned to their topographic separation. These are indications of a reduced symmetry requiring joint rotations of both orientation preference and the underlying topography. This is verified by direct statistical tests in both natural images and in cortical maps. Using the statistics of natural scenes we construct filters that are best suited to extracting information from such images, and find qualitative similarities to mammalian vision. PACS84.35+i 89.70.+c 87.57.Nk     

A new approach based on the surrogating method in the project time compression problems

This paper develops a mathematical model for project time compression problems in CPM/PERT type networks. It is noted this formulation of the problem will be an adequate approximation for solving the time compression problem with any continuous and non-increasing time-cost curve. The kind of this model is Mixed Integer Linear Program (MILP) with zero-one variables, and the Benders' decomposition procedure for analyzing this model has been developed. Then this paper proposes a new approach based on the surrogating method for solving these problems. In addition, the required computer programs have been prepared by the author to execute the algorithm. An illustrative example solved by the new algorithm, and two methods are compared by several numerical examples. Computational experience with these data shows the superiority of the new approach.     

Semideterministic Global Optimization Method: Application to a Control Problem of the Burgers Equation

This paper has two objectives. We introduce a new global optimization algorithm reformulating optimization problems in terms of boundary-value problems. Then, we apply this algorithm to a pointwise control problem of the viscous Burgers equation, where the control weight coefficient is progressively decreased. The results are compared with those obtained with a genetic algorithm and an LM-BFGS algorithm in order to check the efficiency of our method and the necessity of using global optimization techniques.     

Solid Phase Extraction and Simultaneous Spectrophotometric Determination of Trace Amounts of Copper and Iron Using Mixture of Ligands

 A novel sensitive and simple method for rapid and selective extraction, preconcentration and determination of iron (as its bathophenanthroline complex) and copper (as its neocuproine complex) using octadecyl silica cartridges and dual wavelength spectrophotometry is presented. The dual wavelength method (533 nm for the iron-bathophenanthroline and 454 nm for the copper-neocuproine as the analytical wavelength) is used to eliminate spectral interferences. Extraction efficiency and the influence of flow rates of sample solution and eluent, pH, amount of neocuproine, bathophenanthroline and hydroxylamine hydrochloride, type and least amount of eluent for elution of iron and copper complexes from cartridge, break-through volume and limit of detection are evaluated. The effects of various cationic and anionic interferences on percent recovery of iron and copper are also studied. Extraction efficiencies >95% are obtained by elution of cartridges with minimal amount of organic solvent. Iron and copper were determined in the range of 3–100 ng mL⁻¹. The limits of detection are 0.98 and 1.13 ng mL⁻¹ for iron and copper, respectively. The proposed method is applied successfully to the determination of both analytes in river, tap and well water samples. Author for correspondence. E-mail: yyamini@modares.ac.ir Received September 18, 2002; accepted December 12, 2002 Published online May 5, 2003     

Design and optimization of on-chip capillary electrophoresis

We present a systematic, experimentally validated method of designing electrokinetic injections for on-chip capillary electrophoresis applications. This method can be used to predict point-wise and charge-coupled device (CCD)-imaged electropherograms using estimates of species mobilities, diffusivities and initial sample plug parameters. A simple Taylor dispersion model is used to characterize electrophoretic separations in terms of resolution and signal-to-noise ratio (SNR). Detection convolutions using Gaussian and Boxcar detector response functions are used to relate optimal conditions for resolution and signal as a function of relevant system parameters including electroosmotic mobility, sample injection length, detector length scale, and the length-to-detector. Analytical solutions show a tradeoff between signal-to-noise ratio and resolution with respect to dimensionless injection width and length to the detector. In contrast, there is no tradeoff with respect to the Peclet number as increases in Peclet number favor both SNR and separation solution (R). We validate our model with quantitative epifluorescence visualizations of electrophoretic separation experiments in a simple cross channel microchip. For the pure advection regime of dispersion, we use numerical simulations of the transient convective diffusion processes associated with electrokinetics together with an optimization algorithm to design a voltage control scheme which produces an injection plug that has minimal advective dispersion. We also validate this optimal injection scheme using fluorescence visualizations. These validations show that optimized voltage scheme produces injections with a standard deviation less than one-fifth of the width of the microchannel.