Oxidative decomposition of naphthalene by supported metal catalysts

A fixed-bed reactor was utilized to investigate the activities of six metal catalysts (1% Pt, 1% Pd, 1% Ru, 5% Co, 5% Mo and 5% W on γ-Al₂O₃ support) in decomposing naphthalene, based on the production of carbon dioxide and the disappearance of naphthalene. The Pt and Pd catalysts were found to exhibit higher naphthalene oxidizing activity than other catalysts tested. The Co catalysts, whose activity is similar to that of the Ru catalysts, are promising for naphthalene oxidation. The kinetic results of naphthalene oxidation over 1% Pt/γ-Al₂O₃ catalysts are reported for the first time. A first-order reaction with respect to P_naphthalene was found, while the reaction order with respect to P_O2 decreased with increasing reaction temperatures. A Langmuir–Hinshelwood model was used to describe the observed kinetic behavior. Oxygen adsorption dominates at higher reaction temperatures (>140 °C), and consequently the oxidation of naphthalene over the Pt catalysts appeared to be insensitive to P_O2.     

Optimization of reactive SMB and Varicol systems

A comprehensive optimization study on a simulated moving bed reactor (SMBR) system is reported in this article for the direct synthesis of methyl tertiary butyl ether (MTBE) from tertiary butyl alcohol (TBA) and methanol. The applicability of the Varicol process, which is based on non-synchronous shift of the inlet and outlet ports, is explored for the first time for a reactive system. Multi-objective (two and three objective functions) optimization has been performed for both existing as well as design stage for SMBR and Varicol systems and their efficiencies are compared. The optimization problem involves relatively large number of decision variables; both continuous variables, such as flow rates in various sections and length of the columns and discrete variables, such as number of columns and column configuration. Pareto optimal solutions are obtained. It is observed that a five-column Varicol performs better than an equivalent five-column SMBR and its performance is nearly equal to that of a six-column SMBR in terms of purity and yield of MTBE and minimal eluent consumption. This is an important inference as it enables the reduction of fixed and operating costs while at the same time helps to achieve high purity and yield of the desired product and conversion of the limiting reactant. A state-of-the-art optimization technique, viz., non-dominated sorting genetic algorithm (NSGA), which allows handling of these complex optimization problems, is employed for this study. This is the first time that, not only the separating potential of Varicol has been extended to reaction systems, but also was optimized for multiple objectives.     

Multiobjective Optimization of Simulated Moving Bed Reactor and its Modification — Varicol Process

A comprehensive optimization study on a Simulated Moving Bed Reactor (SMBR) system is reported in this article for the direct synthesis of Methyl Tertiary Butyl Ether (MTBE). In addition, the SMB technology, which is based on synchronous switching of ports, was modified to a new more flexible Varicol process based on non‐synchronous switching. Multi‐objective optimization has been performed for both SMBR and Varicol and their efficiencies were compared. A state‐of‐the‐art optimization technique, viz., Non‐dominated Sorting Genetic Algorithm (NSGA) that allows handling of these complex optimization problems is employed in this study.     

Experimental and theoretical analysis of particle distribution in particulate metal matrix composites

Particle distribution in particulate metal matrix composites was investigated experimentally and theoretically. SiC reinforced Pb 20%Sn alloy mechanically was stirred and cast into a cylindrical mold by an inert gas pressure. Particle distribution in the cast is determined at several locations by sectioning and microscopic investigation techniques. The particle fraction is found to decrease along the axis of the mold. The regions close to the boundary wall are determined as the possible clustering areas. A mathematical model is developed to characterize flow of mixture of molten metal alloy and ceramic particles. The distribution of particles is estimated from the trajectories of representative particles with the Lagrangian point of view. The numerical results are reasonably suited with experimental data.     

Synthesis, photophysical and photochemical properties of crown ether substituted zinc phthalocyanines

The photophysical and photochemical properties of the tetra- and octa-12-crown-4-substituted zinc (II) phthalocyanines are reported for the first time in the scope of this work. The new compounds have been characterized by elemental analysis, IR, ¹H and ¹³C NMR spectroscopy, electronic spectroscopy and mass spectra. General trends are described for photodegradation, singlet oxygen and fluorescence quantum yields, and fluorescence lifetimes of these compounds in dimethylsulphoxide (DMSO). Photophysical and photochemical properties of phthalocyanine complexes are very useful for photodynamic therapy (PDT) applications. The effects of the substituents on the photophysical and photochemical parameters of the zinc (II) phthalocyanines (5, 6 and 7) are also reported. The singlet oxygen quantum yields (Φ_Δ) ranged from 0.48 to 0.78 are indicating the potential of the complexes as photosensitizers in applications of PDT. The fluorescences of the substituted ZnPc complexes are effectively quenched by benzoquinone (BQ).     

Optimizing Leakage Energy Consumption in Cache Bitlines

As technology scales down into deep-submicron, leakage energy is becoming a dominant source of energy consumption. Leakage energy is generally proportional to the area of a circuit and caches constitute a large portion of the die area. Therefore, there has been much effort to reduce leakage energy in caches. Most techniques have been targeted at cell leakage energy optimization. Bitline leakage energy is critical as well. To this end, we propose a predictive precharging scheme to reduce bitline leakage energy consumption. Results show that energy savings are significant with little performance degradation. Also, our predictive precharging is more beneficial in more aggressively scaled technologies.     

Extraction of 2-hydroxyphenol by surfactant coated nanosized magnetic particles

A colloidal suspension of magnetic particles coated with double layer surfactant molecules was prepared, characterized and used for separation of some chemicals. The aqueous magnetic fluid was prepared by chemical precipitation method and characterized by total organic carbon analyzer (TOC), thermogravimetric analysis (TGA) and transmission electron microscopy (TEM). The TOC and TGA measurements indicate that the prepared magnetic particles are coated with surfactant molecules in double layers. The outer surfactant layer has free polar heads. TEM measurement results show that magnetic particles are nanosized. A mixture of 2-hydroxyphenol (strong polar) and 2-nitrophenol (weak polar) was chosen as the target system. Results show that the magnetic fluid can selectively adsorb 2-hydroxyphenol from the mixture, whereas the adsorption of 2-nitrophenol is insignificant. For 2-hydroxyphenol, the adsorption equilibrium can be described well by Langmuir isotherm, and the adsorption kinetic can be fitted well by a linear driving force mass transfer model.     

Generalized Regression Neural Networks and Feed Forward Neural Networks for prediction of scour depth around bridge piers

In this study, Generalized Regression Neural Networks (GRNN) and Feed Forward Neural Networks (FFNN) approaches are used to predict the scour depth around circular bridge piers. Hundred and sixty five data collected from various experimental studies, are used to predict equilibrium scour depth. The model consisting of the combination of dimensional data involving the input variables is constructed. The performance of the models in training and testing sets are compared with observations. Then, the model is also tested by Multiple Linear Regression (MLR) and empirical formula. The results of all approaches are compared in order to get more reliable comparison. The results indicated that GRNN can be applied successfully for prediction of scour depth around circular bridge piers.     

Data transformation in the evidential reasoning-based decision making process

This paper describes the application of an evidential reasoning (ER)‐based decision making process to multiple‐criteria decision making (MCDM) problems having both quantitative and qualitative criteria. The ER approach is based on the decision theory and the theory of evidence and it uses the concept of ‘degree of belief’ to assess decision alternatives on each attribute. When faced with MCDM problems, evaluation and selection or ranking of alternatives appear to be both challenging and vital to arrive at a rational and robust decision. In the presence of both qualitative and quantitative evaluations in an MCDM problem, it is necessary, when using the ER‐based decision making process, to transform or convert quantitative data into a belief structure using a number of grades so that the converted belief structure and the original quantitative data are equivalent in values or utilities. This paper suggests three scenarios for data transformation and examines how the ranking of decision alternatives is changed when different scenarios of data transformation are used. Ranking of UK universities using the ER approach is illustrated as an example.