Ultrasound‐induced nucleation in microcellular polymers

In this study, microcellular Acrylonitrile–Butadiene–Styrene foams with high cell density and expansion ratio has been manufactured using ultrasound‐induced nucleation technique in solid‐state batch foaming process. Influence of sonication time, sonication frequency, and ultrasound power were found very crucial in designing of cellular morphology. The initial 10 s of ultrasound exposure was found to influence the foam morphology critically. Longer periods of ultrasound exposure developed foams with lower average cell size as compared to foams developed with lesser ultrasound exposure time. Higher sonication power resulted in foams with uniform morphology and higher cell densities as compared to foams developed with lower sonication intensities. Finally, the ultrasonic frequency was also found to influence the morphology intensely. Low frequency sonication resulted in foams with uniform cell distribution, whereas high frequency sonication developed bimodal microcellular type of microstructure. The results coherently demonstrate that with the advent of ultrasonic waves, the energy barrier for cell nucleation swiftly decreases which enhances the cell density in the final foamed product. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40742.     

Artificial neural network-based prediction of performance and emission characteristics of CI engine using polanga as a biodiesel

The present work predicts the performance parameters, namely brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), peak pressure, exhaust gas temperature and exhaust emissions of a single cylinder four-stroke diesel engine at different injection timings and engine load using blended mixture of polanga biodiesel by artificial neural network (ANN). The properties of biodiesel produced from polanga were measured based on ASTM standards. Using some of the experimental data for training, an ANN model was developed based on standard back-propagation algorithm for the engine. Multi-layer perception network was used for non-linear mapping between input and output parameters. Different activation functions and several rules were used to assess the percentage error between the desired and the predicted values. It was observed that the developed ANN model can predict the engine performance and exhaust emissions quite well with correlation coefficient (R) 0.99946, 0.99968, 0.99988, 0.99967, 0.99899, 0.99941 and 0.99991 for the BSFC, BTE, peak pressure, exhaust gas temperature, NO_x, smoke and unburned hydrocarbon emissions, respectively. The experimental results revealed that the blended fuel provides better engine performance and improved emission characteristics.     

Comparative aroma profiles using supercritical carbon dioxide and Likens–Nickerson extraction from a commercial brand of Basmati rice

A comparative evaluation of the extraction of the aroma constituents of a popular commercial brand of Basmati rice using Likens–Nickerson extraction and supercritical fluid extraction (SFE) with carbon dioxide was carried out. SFE at 50 °C and 120 bar for 2 h provided appreciable extraction of the volatile constituents of the rice as compared with Likens–Nickerson extraction. The advantages of smaller sample size, shorter time of extraction and negligible possibility of artefacts with the SFE technique merit its use for recovery of aroma volatiles from Basmati rice. Copyright © 2003 Society of Chemical Industry     

Quality of traffic flow on urban arterial streets and its relationship with safety

The two-fluid model for vehicular traffic flow explains the traffic on arterials as a mix of stopped and running vehicles. It describes the relationship between the vehicles’ running speed and the fraction of running vehicles. The two parameters of the model essentially represent ‘free flow’ travel time and level of interaction among vehicles, and may be used to evaluate urban roadway networks and urban corridors with partially limited access. These parameters are influenced by not only the roadway characteristics but also by behavioral aspects of driver population, e.g., aggressiveness. Two-fluid models are estimated for eight arterial corridors in Orlando, FL for this study. The parameters of the two-fluid model were used to evaluate corridor level operations and the correlations of these parameters’ with rates of crashes having different types/severity. Significant correlations were found between two-fluid parameters and rear-end and angle crash rates. Rate of severe crashes was also found to be significantly correlated with the model parameter signifying inter-vehicle interactions. While there is need for further analysis, the findings suggest that the two-fluid model parameters may have potential as surrogate measures for traffic safety on urban arterial streets.     

Quantum dot/plasmonic nanoparticle metachromophores with quantum yields that vary with excitation wavelength

Coupled plasmonic/chromophore systems are of interest in applications ranging from fluorescent biosensors to solar photovoltaics and photoelectrochemical cells because near-field coupling to metal nanostructures can dramatically alter the optical performance of nearby materials. We show that CdSe quantum dots (QDs) near single silver nanoprisms can exhibit photoluminescence lifetimes and quantum yields that depend on the excitation wavelength, in apparent violation of the Kasha-Vavilov rule. We attribute the variation in QD lifetime with excitation wavelength to the wavelength-dependent coupling of higher-order plasmon modes to different spatial subpopulations of nearby QDs. At the QD emission wavelength, these subpopulations are coupled to far-field radiation with varying efficiency by the nanoprism dipolar resonance. These results offer an easily accessible new route to design metachromophores with tailored optical properties.     

Highly selective GaN-nanowire/TiO2-nanocluster hybrid sensors for detection of benzene and related environment pollutants

Nanowire-nanocluster hybrid chemical sensors were realized by functionalizing gallium nitride (GaN) nanowires (NWs) with titanium dioxide (TiO(2)) nanoclusters for selectively sensing benzene and other related aromatic compounds. Hybrid sensor devices were developed by fabricating two-terminal devices using individual GaN NWs followed by the deposition of TiO(2) nanoclusters using RF magnetron sputtering. The sensor fabrication process employed standard microfabrication techniques. X-ray diffraction and high-resolution analytical transmission electron microscopy using energy-dispersive x-ray and electron energy-loss spectroscopies confirmed the presence of the anatase phase in TiO(2) clusters after post-deposition anneal at 700?°C. A change of current was observed for these hybrid sensors when exposed to the vapors of aromatic compounds (benzene, toluene, ethylbenzene, xylene and chlorobenzene mixed with air) under UV excitation, while they had no response to non-aromatic organic compounds such as methanol, ethanol, isopropanol, chloroform, acetone and 1,3-hexadiene. The sensitivity range for the noted aromatic compounds except chlorobenzene were from 1% down to 50 parts per billion (ppb) at room temperature. By combining the enhanced catalytic properties of the TiO(2) nanoclusters with the sensitive transduction capability of the nanowires, an ultra-sensitive and selective chemical sensing architecture is demonstrated. We have proposed a mechanism that could qualitatively explain the observed sensing behavior.     

Homoepitaxial n-core: p-shell gallium nitride nanowires: HVPE overgrowth on MBE nanowires

We present the homoepitaxial growth of p-type, magnesium doped gallium nitride shells by use of halide vapor phase epitaxy (HVPE) on n-type gallium nitride nanowires grown by plasma-assisted molecular beam epitaxy (MBE). Scanning electron microscopy shows clear dopant contrast between the core and shell of the nanowire. The growth of magnesium doped nanowire shells shows little or no effect on the lattice parameters of the underlying nanowires, as measured by x-ray diffraction (XRD). Photoluminescence measurements of the nanowires show the appearance of sub-bandgap features in the blue and the ultraviolet, indicating the presence of acceptors. Finally, electrical measurements confirm the presence of electrically active holes in the nanowires.     

Correlation between the performance and microstructure of Ti/Al/Ti/Au Ohmic contacts to p-type silicon nanowires

Understanding the electrical and microstructural aspects of contact formation at nanoscale is essential for the realization of low-resistance metallization suitable for the next generation of nanowire based devices. In this study, we present detailed electrical and microstructural characteristics of Ti/Al/Ti/Au metal contacts to p-type Si nanowires (SiNWs) annealed at various temperatures. Focused ion beam cross-sectioning techniques and scanning transmission electron microscopy (STEM) were used to determine the microstructure of the source/drain metal contacts of working SiNW field-effect transistors (FETs) annealed for 30 s in the 450-850?°C temperature range in inert atmosphere. Formation of titanium silicides is observed at the metal/semiconductor interface after the 750?°C anneal. Extensive Si out-diffusion from the nanowire after the 750?°C anneal led to Kirkendall void formation. Annealing at 850?°C led to almost complete out-diffusion of Si from the nanowire core. Devices with 550?°C annealed contacts had linear electrical characteristics; whereas the devices annealed at 750?°C had the best characteristics in terms of linearity, symmetric behavior, and yield. Devices annealed at 850?°C had poor yield, which can be directly attributed to the microstructure of the contact region observed in STEM.     

Removal of rain from videos: a review

In this paper, the algorithms for the detection and removal of rain from videos have been reviewed. Rain reduces the visibility of scene and thus performance of computer vision algorithms which use feature information. Detection and removal of rain requires the discrimination of rain and nonrain pixels. Accuracy of the algorithm depends upon this discrimination. Here merits and demerits of the algorithms are discussed, which motivate the further research. A rain removal algorithm has a wide application in tracking and navigation, consumer electronics and entertainment industries.