Polyaniline–polypropylene melt‐spun fiber filaments: The collaborative effects of blending conditions and fiber draw ratios on the electrical properties of fiber filaments

A melt‐processable polyaniline complex was blended with polypropylene under different mixing conditions and melt‐spun into fiber filaments under different draw ratios. The conductivity, electrical resistance at different voltages, and morphological characteristics of the prepared fibers were investigated. The morphology of this two‐phase blend was demonstrated to have a large effect on the conductivity level and the linearity of the resistance–voltage relationship of the blend fibers. Two factors had substantial effects on the morphology and electrical properties of the fibers. They were the size of the initial dispersed conductive phase, which depended on the melt blending conditions, and the stress applied to orient this phase to a fibril‐like morphology, which was controlled by the draw ratio of the fiber. The two factors were shown to be associated with each other to maintain an appropriate balance of fibril formation and breakage and to create continuous conductive pathways. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Convenient synthesis of benzamides mediated by poly(4‐vinylpyridine)‐supported benzoyl chloride

The use of polymeric reagents simplifies the routine acylation of amines because it eliminates traditional purification. In this article, the use of readily available crosslinked poly(4‐vinylpyridine)‐supported benzoyl chloride as an acylating agent of amines in the presence of K₂CO₃ in n‐hexane is described. The product was readily obtained by the filtration and evaporation of the solvent. The spent polymeric reagent could be regenerated and reused. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Dynamic performance assessment of the efficiency of fuel cell-powered bicycle: An experimental approach

Zero-emission fuel cell driven systems are regarded as promising technological advances in the future of the transportation industry that have the potential to replace internal combustion engines. The design, performance, and efficiency properties of a vehicle are often stated to be some of the key challenges in its commercialization. This paper highlights a polymer electrolyte membrane fuel cell (PEMFC)-powered system of an electric bicycle. The system consists of a 250-W fuel cell, ECU, battery pack, DC/DC converter, electric motor, and other supporting equipment. After introducing the different parts of the bicycle, its overall efficiency will be discussed in great detail. The efficiency of fuel cells is not specific; it is a subordinate to the power density where the system operates. Experimental work has been conducted to measure the values of the efficiency and energy flow. The results indicated a maximum fuel cell efficiency of 63% and an overall system efficiency of 35.4%. The latter value is expressed with regards to the Lower Heating Value (LHV) of hydrogen. All measurements were taken for the cruising conditions of the vehicle and its corresponding to power consumption. The results are superior to those of a standard internal ignition engine. The fuel cell performance is least efficient when functioning under maximum output power conditions.     

A novel algorithm for layout optimization of injection process with random demands and sequence dependent setup times

Injection molding is an ideal manufacturing process for producing high volumes of products from both thermoplastic and thermo setting materials. Nevertheless, in some cases, this type of manufacturing process decelerates the production rate as a bottleneck. Thus, layout optimization plays a crucial role in this type of problem in terms of increasing the efficiency of the production line. In this regard, a novel computer simulation–stochastic data envelopment analysis (CS-SDEA) algorithm is proposed in this paper to deal with a single row job-shop layout problem in an injection molding process. First, the system is modeled with discrete-event-simulation as a powerful tool for analyzing complex stochastic systems. Then, due to lack of information about some operational parameters, theory of uncertainty is imported to the simulation model. Finally, an output-oriented stochastic DEA model is used for ranking the outputs of simulation model. The proposed CS-SDEA algorithm is capable of modeling and optimizing non-linear, stochastic, and uncertain injection process problems. The solution quality is illustrated by an actual case study in a refrigerator manufacturing company.     

Cometabolic degradation of para-nitrophenol and phenol by Ralstonia eutropha in a Kissiris-immobilized cell bioreactor

Ralstonia eutropha was able to degrade p-nitrophenol (PNP) at concentrations ranging from 5 to 15mg l ^?1 in the presence of phenol which was kept at the constant concentration of 200 mg l ^?1. More than 90% of phenol was degraded within 30 h and in the absence of PNP. While in this time period and in the presence of 15 mg l ^?1 less than 30% of phenol was degraded and PNP removal ability of the test bacterium was about 20%. Kissiris as a natural source of silicon dioxide having a very rigid structure with many micropores irregularly distributed throughout its surface was used to evaluate effectiveness of the cell immobilization using a Kissiris-immobilized cell bioreactor [ICB]. By applying phenol-feeding regime in the ICB operated in a batch recycling mode, simultaneous degradation of phenol in total amount of 1,000 mg l ^?1 with 15 mg l ^?1 PNP was achieved within 40 h.     

A robust decision-making methodology for evaluation and selection of simulation software package

Today, simulation has a broad range of applications from solving service problems to analyzing manufacturing problems such as warehousing and logistic systems. Simulation has become a popular methodology and selecting an appropriate simulation software package is one of the decisions that any industrial engineer may face at work. As a result, numerous types of simulation software packages have been developed for modeling simulation problems. The increasing variety of simulation software packages in the software market makes the selection of an appropriate simulation software package a critical decision. Selecting an inappropriate software package will be followed by many negative consequences. This paper will present a robust decision-making methodology based on Fuzzy Analytical Hierarchy Process (FAHP) for evaluating and selecting the appropriate simulation software package. The robust decision method aggregates the experts’ judgments for the criteria weights and the suitability of simulation software alternatives. The FAHP is used to prioritize and evaluate existing alternatives based on the proposed criteria for choosing the proper simulation software. The proposed methodology is applied to selecting the appropriate simulation software as an experiment and results are provided.     

Physical and Morphological Properties of Combined Treated Wood Polymer Composites by Maleic Anhydride and Methyl Methacrylate

Wood polymer composites were prepared by consecutive impregnation with maleic anhydride (MAN) and methyl methacrylate (MMA). Samples impregnated with MAN alone, were heated at 120°C and 150°C for 4 and 8 h. Based on the Fourier transform infrared (FT-IR) analysis and soaking-drying test results, treatment with MAN at 150°C for 4 h resulted in formation of stable crosslinks. In the second stage, MMA was used for in situ polymerization within MAN-treated wood. Field emission scanning electron microscopy observation and FT-IR analysis indicated that MMA copolymerized with MAN, and the resultant polymer filled up the lumen and is also grafted on to the cell wall. Improvement of water repellency and dimensional stability were observed in the treated samples, particularly in combined treated samples. The MAN/MMA treatment improved interaction between polymer and wood.     

Heterogeneous photocatalytic degradation of 4-chlorophenol by immobilization of cobalt tetrasulphophthalocyanine onto MCM-41

The photocatalytic activity of cobalt tetrasulphophthalocyanine immobilized onto MCM-41 was investigated for photocatalytic degradation of 4-chlorophenol (4-CP) in aqueous solutions. Immobilization of cobalt tetrasulphophthalocyanine complex to the walls of MCM-41 was performed by pre-anchorage of 3-(aminopropyl)-triethoxysilane (APTES) onto MCM-41 via post-synthesis method. X-ray diffraction, nitrogen physisorption, diffuse reflectance spectroscopy, energy-dispersive X-ray and FT-IR methods were used to characterize the product. Photocatalytic efficiency of the prepared photocatalyst for degradation of 4-CP was tested under illumination of UV-A and visible light. The reaction intermediates were identified by gas chromatography-mass spectrometry (GC-MS) technique.     

A flexible neural network-fuzzy data envelopment analysis approach for location optimization of solar plants with uncertainty and complexity

This study presents a flexible neuro-fuzzy approach for location optimization of solar plants with possible complexity and uncertainty. The flexible approach is composed of artificial neural network (ANN) and fuzzy data envelopment analysis (FDEA). The intelligent approach of this study is applied for location optimization of solar plants in Iran. First, FDEA is validated by DEA, and then it is used for ranking of solar plant units (SPUs) and the best α-cut is selected based on the test of Normality. Also, several ANNs are developed through multi layer perceptron (MLP) for ranking of solar plants and the best one with minimum mean absolute percentage of error (MAPE) is selected for further considerations. Finally, the preferred model (FDEA or ANN) is selected based on test of Normality. The implementation of the flexible approach for solar plants in Iran identifies the preferred FDEA at α = 0.3, where is the level of data uncertainty. This indicates that the data are collected from the uncertain and fuzzy environment. This is the first study that presents a flexible approach for identification of optimum location of solar plants with possible noise, non-linearity, complexity and environmental uncertainty. This would help policy makers to identify the preferred Strategy for location optimization problems associated with solar plant units.