Diffuse reflectance behavior of the printed cotton/nylon blend fabrics treated with zirconium and cerium dioxide and citric acid in near- and short-wave IR radiation spectral ranges

Near- and short-wave IR emission spectra of printed cotton/nylon blend fabrics coated with inorganic compounds in order to tune their diffuse reflectance behavior to the ones with woodland and desert backgrounds are investigated. In this regard, cotton/nylon blend fabrics printed with a four-color digital pattern were used as the substrate, and different concentrations of zirconium and cerium dioxide (ZrO₂ and CeO₂) with and without citric acid as a cross-linker were loaded on these fabrics using the pad-dry-cure method. The diffuse reflectance of the coated fabrics with various concentrations of nanoparticles and a cross-linker was first measured by near-infrared (NIR) diffuse reflectance spectroscopy (DRS). Then, fabrics with an optimum concentration of nanoparticles and appropriate reflectivity profiles similar to woodland and desert were investigated by field emission scanning electron microscopy (FE-SEM), energy-dispersive spectroscopy (EDS), washing, and rubbing fastness properties. In general, NIR and short-wave infrared (SWIR) reflectance of fabrics coated with ZrO₂ and CeO₂ nanoparticles in range of 1% to 1.5% (w/v [%]) was suitable for matching with different environments. According to the findings obtained from the durability test, it was concluded that the washing fastness of the treated fabrics with CeO₂ nanoparticles was excellent in both environments. FE-SEM images of the treated fabrics containing ZrO₂ and CeO₂ indicated that the presence of nanoparticles on the surface of fabrics in woodland patterns was greater than the desert ones. However, the coated fabrics with CeO₂ and citric acid in the woodland pattern have shown better dispersion with a mean particle size of 30 to 60 nm.     

Transmission pricing and recovery of investment costs in the deregulated power system based on optimal circuit prices

Transmission pricing has become a major issue in the discussions about the deregulated electricity markets.Conse-quently,open access to the transmission system is one of the basic topics to allow compe...     

Polyester composite water uptake and organic contaminant release affected by carbon nanofiber reinforcements

The incorporation of carbon nanofiber (CNF) into glass fiber (GF) composites is a potential route to extend polymer composite service‐life and enhance mechanical properties. Under nonstatic conditions, only limited information concerning water uptake and contaminant release properties of nanocomposite materials is currently available. Polyester composites containing GF and oxidized CNF were immersed in water for 30 days under nominal pressure at 23 °C, below the polymer's glass‐transition temperature. Water was analyzed and changed every three days to simulate water chemistry regeneration similar to exposures in flowing systems. Composites with oxidized CNF had greater water sorption capacity and leaching rates than CNF‐free composites. The total mass of organic contaminant released correlated with the amount of water sorbed by each composite (r² = 0.91), although CNF dispersion was found to vary greatly within composites. The greatest and least contaminant release rates were found for the polyester‐CNF and the polyester‐GF composites, respectively. While volatile aromatic resin solvents and stabilizer compounds were detected, their concentrations declined over the 30 day exposure period. We hypothesize that the hydrophilic nature of the oxidized CNF increased the water sorption capacity of the polyester composites. Additional studies are warranted that examine the impact of this phenomenon on composite mechanical and long‐term durability properties. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43724.     

Characterization of the Ion Beam Current Density of the RF Ion Source with Flat and Convex Extraction Systems

Silicon - The characterization of ion beam current density distribution and beam uniformity is crucial for improving broad-beam ion source technologies. The design of the broad ion beam extraction...     

Synthesis of polyelectrolyte-modified ordered nanoporous carbon for removal of aromatic organic acids from purified terephthalic acid wastewater

In this work polyelectrolyte (polydiallyldimethylammonium chloride) modified ordered mesoporous carbon (CMK-1/PDDA) has been synthesized and has been employed in removal of major aromatic compounds present in purified terephthalic acid wastewater, such as p-toluic acid, benzoic acid, 4-carboxybenzaldehyde, phthalic acid and terephthalic. The adsorption behavior of these acidic impurities has been studied through batch experiments and using UV-spectrophotometric technique. The results show that CMK-1/PDDA is very effective in selective removal of acidic compounds from PTA-waste aqueous solutions. The electrostatic interaction was considered to be the main mechanism for the adsorption of acidic compounds. The effects of chemical modification, contact time, initial concentrations, adsorbent dose, agitation speed, solution pH and reaction temperature have been optimized. The sorption equilibrium was reached within 5 min. The sorption of acidic compounds on the CMK-1/PDDA slightly decreases with increasing pH, and temperature, indicating an exothermic process. The experimental isotherm data were analyzed using the Langmuir and Freundlich equations. The equilibrium data were best represented by the Langmuir isotherm.     

The effect of SiO2 porosity on activity profiles and comonomer incorporation in slurry ethylene/butene‐1 polymerization by (SiO2/MgCl2/TEOS/TiCl4) catalyst system

To investigate the influence of support porosity parameters e.g., average pore volume (APV), pore diameter (PD), and pore surface area distribution (PSAD) on activity‐profile of catalyst and comonomer incorporation, a series of silica‐supports with different porosity were prepared through sol–gel method and used to synthesize corresponding (SiO₂/MgCl₂/TEOS/TiCl₄) catalysts. Polymerization of ethylene/butene‐1 showed that increasing of APV from 0.75 to 2.2 cm³ g increase initial activity from 120 to 400 (g_poly/g_cat.bar.hr) followed by appearance of secondary peaks in activity‐profile which could be attributed to the variation of PSAD. It is found that the effect of support in polymerization is a complicated issue which depends not only on the porosity parameters also on the comonomer concentration. The catalyst with PD of 300 Å gives higher comonomer incorporation and polymers with 15–20% lower crystallinity in contrast to catalyst with PD of 100 Å. Porosity effect was quantitatively studied by modifying of conventional Z‐N catalyst polymerization mechanism through introducing fragmentation term to achieve a new tool in designing and developing of polyolefin catalysts. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

On-line analysis of out-of-control signals in multivariate manufacturing processes using a hybrid learning-based model

Advanced automatic data acquisition is now widely adopted in manufacturing industries and it is common to monitor several correlated quality variables simultaneously. Most of multivariate quality control charts are effective in detecting out-of-control signals based upon an overall statistics in multivariate manufacturing processes. The main problem of such charts is that they can detect an out-of-control event but do not directly determine which variable or group of variables has caused the out-of-control signal and what is the magnitude of out of control. This study presents a hybrid learning-based model for on-line analysis of out-of-control signals in multivariate manufacturing processes. This model consists of two modules. In the first module using a support vector machine-classifier, type of unnatural pattern can be recognized. Then by using three neural networks for shift mean, trend and cycle it can be recognized magnitude of mean shift, slope of trend and cycle amplitude for each variable simultaneously in the second module. The performance of the proposed approach has been evaluated using two examples. The output generated by trained hybrid model is strongly correlated with the corresponding actual target value for each quality characteristic. The main contributions of this work are recognizing the type of unnatural pattern and classification major parameters for shift, trend and cycle and for each variable simultaneously by proposed hybrid model.     

Robust non-aggressive three-axis attitude control of spacecraft: dynamic sliding mode approach

Conventional sliding mode control (SMC) has been extensively applied in controlling spacecrafts because of its appealing characteristics such as robustness and a simple design procedure. Several methods such as second-order sliding modes and discontinuous controllers are applied for the SMC implementation. However, the main problems of these methods are convergence and error tracking in a finite amount of time. This paper combines an improved dynamic sliding mode controller and model predictive controller for spacecrafts to solve the chattering phenomenon in traditional sliding mode control. To this aim, this paper develops dynamic sliding mode control for spacecraft’s applications to omit the chattering issue. The proposed approach shows robust attitude tracking by a set of reaction wheels and stabilizes the spacecraft subject to disturbances and uncertainties. The proposed method improves the performance of the SMC for spacecraft by avoiding chattering. A set of simulation results are provided that show the advantages and improvements of this approach (in some sense) compared to SMC approaches.     

Resource discovery in the Internet of Things integrated with fog computing using Markov learning model

The Journal of Supercomputing - Due to high and unpredictable connection delays, privacy gaps, and traffic load of networks connecting cloud computing to end users in many of the Internet of Things...     

Distributed Adaptive Dynamic Surface Control for Synchronization of Uncertain Nonlinear Multi-agent Systems

In this paper a distributed adaptive dynamic surface controller is proposed for multi-agent systems under fixed directed graph topologies. The agents have uncertain nonlinear dynamics and are influenced by bounded unknown disturbances. The controller should synchronize the states of all agents with the corresponding states of the nonautonomous leader. It is proved that, with the proposed controller, the synchronization error remains bounded; and the bounds can be arbitrarily decreased by increasing the controller gains. The control rules are designed such that each agent only requires the state information of its neighbors, rendering a distributed control. The effectiveness of the proposed method is demonstrated through two simulation examples.