Influence of current density on crystalline structure and magnetic properties of electrodeposited Co-rich CoNiW alloys

The influence of current density, at the interval 5–100 mA cm⁻², on the structural and magnetic properties of electrodeposited (Co_100−xNi_x)_100−yW_y alloys (x = 23–33.5 at. % Ni, y = 1.7–7.3 at. % W) was studied from a glycine-containing bath. W-content decreases with the increase of the current density magnitude. X-ray data have shown stabilization of hexagonal close packed, face centered cubic or a mixture of these structures by modulating the applied cathodic current density, for values lower than 50 mA cm⁻². Two structural phase transitions were observed: one from hexagonal close packed to face centered cubic structural transition occurring for a current density of 20 mA cm⁻², and another one, from cubic crystalline phase to amorphous state, which happens for values higher than 50 mA cm⁻². These structural phase transitions seem to be associated with the W-content as well as average crystalline grain sizes that reduce with increasing the current density value. The grain size effect may explain the face centered cubic stabilization in Co-rich CoNiW alloys, which was initially assumed to be basically due to H-adsorption/incorporation. Magnetic properties of Co-rich CoNiW alloys are strongly modified by the current density value; as a result of the changes on the W-content and their structural properties.     

Fabrication and characterizations of PCDTBT: PC71BM bulk heterojunction solar cell using air brush coating method

Organic solar cells have been significantly attracted due to the need to develop an inexpensive clean and sustainable renewable energy source. We report on the fabrication of poly [N-9″-hepta-decanyl-2,7-carbazole-alt-5,5-(4′,7′-di-2-thienyl-2′,1′,3′-benzothiadiazole)]/[6, 6]-phenyl-C₇₁-butyric acid methyl ester blend active layer using airbrush spray-coating method in mixed solvents. Optical absorption of the active layers was analyzed using UV–visible spectral studies in the wavelength range from 300 to 800 nm. The surface morphology of the active layers deposited with different parameters (spraying time and substrate-nozzle distance) was examined using atomic force microscopy. The current density–voltage (J–V) characteristics of photovoltaic cells were measured under the illumination of simulated solar light with 100 mW cm^?2 (AM 1.5G) by an Oriel 1000 W solar simulator. The power conversion efficiency of the solar cell is more than 5 %.     

Comparison of performances of five prospective approaches for the multi-response optimization

The Taguchi method of experimental design is widely used for optimization of process performance. However, this method has been developed to optimize single-response processes. But, in many situations, the engineers are required to determine the process settings that can simultaneously optimize multiple responses. In the recent past, researchers have proposed several systematic procedures for multi-response optimization. Most of these methods use complicated statistical/mathematical models and are, therefore, not easily comprehendible to the engineers who do not have a strong background in mathematics. Only a few methods, e.g. weighted signal-to-noise (WSN) ratio, Grey relational analysis, multiple-response signal-to-noise ratio, VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian), and weighted principal component methods, use relatively simpler procedures. In this paper, the computational procedures for these five methods are standardized. Three sets of experimental data are analyzed using these standardized procedures and the predicted optimization performances of the five methods are compared. The results show that no method can give better optimization than the WSN method.     

Dropping False Packet to Increase the Network Lifetime of Wireless Sensor Network using EFDD Protocol

In Wireless Sensor Network (WSN) sensors are densely deployed where the intruders can compromise some sensor nodes and inject false data in order to raise false alarms, reduce network lifetime, utilize bandwidth resources and so on. False Data Injection can possibly occur in Data Aggregation (DA) and Data Forwarding (DF). This paper analyses EFDD Protocol-Early False Data Detection Protocol which addresses the two possibilities in a simple and secure way considering the constraints of sensor nodes. The main idea is the selection of the network structure; this protocol will work effectively in Spatial/Semantic Correlation Tree Structure (SCT). False Data Detection in DA is done using some monitoring nodes which will monitor the Data Aggregator. EFDD in SCT structure reduce the counterfeit data transmission when compared to other structure in a better way. The result shows that EFDD reduce data transmission by dropping false data earlier and it also reduces computation when compared to the existing schemes.     

Effect of microwave‐assisted extraction on the release of polyphenols from ginger (Zingiber officinale)

The significance of different variables viz. temperature, time and solvent at constant power in microwave‐assisted extraction (MAE) process of ginger was studied and compared with conventional method. Aqueous ethanol (50%) provided higher yields of extract as well as the highest release of total polyphenols (TPP) than alcoholic solvents. The reason could be the high dielectric constant of aqueous ethanol as compared to alcohols. Microwave heating being a volumetric process, an exposure time of 1 min was found to be sufficient. The better penetration of microwaves and greater solubility at higher temperature resulted in higher yield of TPP and [6]‐gingerol. The resultant extract showed higher radical scavenging activity (RSA) values. Thus, MAE allowed higher recoveries compared to conventional extraction process, with improvement in the quantity and quality of extract in very short period of time.     

A theoretical study of the performance of sub-micron MOSFET devices in the presence of edge potential

In the present communication we have presented a detailed theoretical analysis of the performance of the sub-micron device in the presence of the discontinuity at the Si–SiO₂ interface. It is assumed that due to interface discontinuity a potential develops at the edges (Source/Drain) in addition to the built-in-potential. This potential, called Edge Potential, measures directly the extent of the interface roughness. The effect of this potential is more critical in the case of short channel device where drain and source are in close proximity. Our analysis shows that the discontinuity is dominant at the edges but not in the channel. Drive current as well as saturation transconductance decreases in the presence of edge potential. These results suggest that the performance of the device degrades due to the interface roughness. Effect of interface roughness near the edges can be reduced at high gate voltage but it will result more interface roughness scattering.     

Performance of the transmission line model for the microstrip elements

Although more rigorous treatments have been developed for the microstrip elements, the purpose of this transmission line model is to provide a numerically efficient substitute for them. The rectangular resonator is replaced by two equivalent radiating slots. In most practical cases the approximations are acceptable. It is obvious that the efficiency of the transmission model can be used to include mutual coupling in practical analysis. The calculated results are in good agreement with observed results.     

Development of image processing based system to study yarn structure during extension

The present study describes design and development and use of an image processing system to characterize and visualize the configuration of fibers in yarn in extended mode. An especially dedicated instrument and software for data acquisition and analysis are the unique features of the system. It is capable of grabbing the images of extended yarn in two orthogonal planes. The software can acquire data from these two orthogonal planes. The three‐dimensional trajectory of whole length of different colored tracer fibers can be plotted and can be viewed at different angles. The image processing system along with multi‐colored tracer fiber technique has been used for quantitative analysis of changes in the internal structure of ring yarn on extension.     

Factors influencing arsenic and nitrate removal from drinking water in a continuous flow electrocoagulation (EC) process

An experimental study was conducted under continuous flow conditions to evaluate some of the factors influencing contaminant removal by electrocoagulation (EC). A bench-scale simulation of drinking water treatment was done by adding a filtration column after a rectangular EC reactor. Contaminant removal efficiency was determined for voltages ranging from 10 to 25 V and a comparative study was done with distilled water and tap water for two contaminants: nitrate and arsenic(V). Maximum removal efficiency was 84% for nitrate at 25 V and 75% for arsenic(V) at 20 V. No significant difference in contaminant removal was observed in tap water versus distilled water. Increase in initial As(V) concentration from 1 ppm to 2 ppm resulted in a 10% increase in removal efficiency. Turbidity in the EC reactor effluent was 52 NTU and had to be filtered to achieve acceptable levels of final turbidity (5 NTU) at steady-state. The flow regime in the continuous flow reactor was also evaluated in a tracer study to determine whether it is a plug flow reactor (PFR) or constantly stirred tank reactor (CSTR) and the results show that this reactor was close to an ideal CSTR, i.e., it was fairly well-mixed.     

Monthly Rainfall Prediction Using Wavelet Neural Network Analysis

Rainfall is one of the most significant parameters in a hydrological model. Several models have been developed to analyze and predict the rainfall forecast. In recent years, wavelet techniques have been widely applied to various water resources research because of their time-frequency representation. In this paper an attempt has been made to find an alternative method for rainfall prediction by combining the wavelet technique with Artificial Neural Network (ANN). The wavelet and ANN models have been applied to monthly rainfall data of Darjeeling rain gauge station. The calibration and validation performance of the models is evaluated with appropriate statistical methods. The results of monthly rainfall series modeling indicate that the performances of wavelet neural network models are more effective than the ANN models.