Performance,emission and combustion studies of a DI diesel engine using Distilled Tyre pyrolysis oil-diesel blends

Increase in energy demand, stringent emission norms and depletion of oil resources led the researchers to find alternative fuels for internal combustion engines. Many alternate fuels like Alcohols, Biodiesel, LPG, CNG etc have been already commercialized in the transport sector. In this context, pyrolysis of solid waste is currently receiving renewed interest. The disposal of waste tyres can be simplified to some extent by pyrolysis. The properties of the Tyre pyrolysis oil (TPO) derived from waste automobile tyres were analyzed and compared with the petroleum products and found that it can also be used as a fuel for compression ignition engine. However, the crude TPO has a higher viscosity and sulphur content. The crude TPO was desulphurised and then distilled through vacuum distillation. In the present work, DTPO-diesel blends were used as an alternate fuel in a diesel engine without any engine modification. This paper presents the studies on the performance, emission and combustion characteristics of a single cylinder four stroke air cooled DI diesel engine running with the Distilled Tyre pyrolysis oil (DTPO).     

Structural and optical characterization of Ni-doped CdS quantum dots

Ni-doped CdS quantum dots have been prepared by chemical precipitation technique. The X-diffraction results indicated that the particle size of Ni-doped CdS nanoparticles is smaller than that of undoped CdS and no secondary phase was observed. The average grain size of the nanoparticles is found to lie in the range of 2.7–4 nm. The compositional analysis results show that Cd, Ni, and S are present in the samples. HRTEM studies reveal that the average particle size of undoped and Ni-doped CdS quantum dots is 2 and 3 nm, respectively. Raman spectra shows that 1LO, 2LO, and 3LO peaks of the Ni-doped CdS samples are slightly red shifted when compared to that of undoped CdS. The absorption edge of Ni-doped CdS nanoparticles is found to shift towards the higher-wavelength (red shift) side when compared to that of undoped CdS and the band gap is observed to lie in the range of 3.79–3.95 eV. This band gap is higher than that of the bulk CdS and is due to quantum confinement effect present in CdS nanoparticles.     

Development of Mathematical Model for Prediction and Optimization of Particle Size in Nanocrystalline CdS Thin Films Prepared by Sol-Gel Spin-Coating Method

Nanocrystalline CdS thin films have been prepared by the sol-gel spin-coating method. The influence of spin-coating process parameters such as, thiourea concentration (U), annealing temperature (A), rotational speed (S), and annealing time (T), and so on, on the properties of the prepared films have been studied. The experiments have been carried out based on four factor-five-level central composite designs with the full replication technique, and mathematical models have been developed using regression technique. The central composite rotatable design has been used to minimize the number of experimental parameters. The analysis of variance technique is applied to check the validity of the developed models. The developed mathematical model can be used effectively to predict the particle size in CdS nanocrystalline thin films at 95 pct confidence level. The results have been verified by depositing the films using the same condition. An ultraviolet-visible optical spectroscopy study was carried out to determine the band gap of the CdS nanocrystalline thin films. The band gap has been observed to depend strongly on particle size, and it indicated a blue shift caused by quantum confinement effects. The high-resolution transmission electron microscopy analysis showed the grain size of the prepared CdS film to be 6 nm. The main and interaction effects of deposition parameters on the properties of CdS nanocrystalline thin films also have been studied.     

The Final Case of the Decoding Delay Problem for Maximum Rate Complex Orthogonal Designs

Complex orthogonal space-time block codes (COSTBCs) based on generalized complex orthogonal designs (CODs) have been successfully implemented in wireless systems with multiple transmit antennas and single or multiple receive antennas. It has been shown that for a maximum rate COD with 2m-1 or 2m columns, a lower bound on decoding delay is (_m-1 ^2m) and this delay is achievable when the number of columns is congruent to 0, 1 , or 3 modulo 4. In this paper, the final case is addressed, and it is shown that when the number of columns is congruent to 2 modulo 4, the lower bound on decoding delay cannot be achieved. In this case, the shortest decoding delay a maximum rate COD can achieve is twice the lower bound. New techniques for analyzing CODs are introduced with connections to binary vector spaces.     

Printed Planar Monopole Antenna Design for Ultra-Wideband Communications

This paper presents an ultra wideband (UWB) planar printed monopole antenna fed by microstrip line. The antenna configuration contains a beveled ground plane. The beveled partial ground plane improves the impedance bandwidth. The measured frequency response demonstrates that the fabricated antenna exhibits an impedance bandwidth of 7.9 GHz over 3.1 to 11 GHz for VSWR < 2. The proposed antenna has ultra-wideband characteristics with omnidirectional radiation pattern and stable gain. Ultra-wideband performance of the proposed antenna is examined through the simulated surface current distributions. Measured results confirm that the antenna is suitable for UWB applications due to its compact size and high performance characteristics.     

NMR studies of artificial double-crossover DNA tiles

This report documents the design and characterization of DNA molecular nanoarchitectures consisting of artificial double crossover DNA tiles with different geometry and chemistry. The Structural characterization of the unit tiles, including normal, biotinylated and hairpin loop structures, are morphologically studied by atomic force microscopy. The specific proton resonance of the individual tiles and their intra/inter nucleotide relationships are verified by proton nuclear magnetic resonance spectroscopy and 2-dimensional correlation spectral studies, respectively. Significant up-field and down-field shifts in the resonance signals of the individual residues at various temperatures are discussed. The results suggest that with artificially designed DNA tiles it is feasible to obtain structural information of the relative base sequences. These tiles were later fabricated into 2D DNA lattice structures for specific applications such as protein arrangement by biotinylated bulged loops or pattern generation using a hairpin structure.     

Controlled release of drugs from gradient hydrogels for high-throughput analysis of cell-drug interactions

In this paper, we report a method to fabricate microengineered hydrogels that contain a concentration gradient of a drug for high-throughput analysis of cell-drug interactions. A microfluidic gradient generator was used to create a concentration gradient of okadaic acid (OA) as a model drug within poly(ethylene glycol) diacrylate hydrogels. These hydrogels were then incubated with MC3T3-E1 cell seeded glass slides to investigate the cell viability through the spatially controlled release of OA. The drug was released from the hydrogel in a gradient manner and induced a gradient of the cell viability. The drug concentration gradient containing hydrogels developed in this study have the potential to be used for drug discovery and diagnostics applications due to their ability to simultaneously test the effects of different concentrations of various chemicals.     

An efficient and automatic glioblastoma brain tumor detection using shift‐invariant shearlet transform and neural networks

The detection and segmentation of tumor region in brain image is a critical task due to the similarity between abnormal and normal region. In this article, a computer‐aided automatic detection and segmentation of brain tumor is proposed. The proposed system consists of enhancement, transformation, feature extraction, and classification. The shift‐invariant shearlet transform (SIST) is used to enhance the brain image. Further, nonsubsampled contourlet transform (NSCT) is used as multiresolution transform which transforms the spatial domain enhanced image into multiresolution image. The texture features from grey level co‐occurrence matrix (GLCM), Gabor, and discrete wavelet transform (DWT) are extracted with the approximate subband of the NSCT transformed image. These extracted features are trained and classified into either normal or glioblastoma brain image using feed forward back propagation neural networks. Further, K‐means clustering algorithm is used to segment the tumor region in classified glioblastoma brain image. The proposed method achieves 89.7% of sensitivity, 99.9% of specificity, and 99.8% of accuracy.     

Optimization of hybrid laser–TIG welding of 316LN stainless steel using genetic algorithm

Determination of optimum hybrid laser–TIG welding process variables for achieving the maximum depth of penetration (DOP) in type 316LN stainless steel has been carried out using a genetic algorithm (GA). Nd:YAG pulsed laser and the TIG heat source were coupled at the weld pool to carry out hybrid welding. Design of experiments approach was used to generate the experimental design matrix. Bead-on-plate welds were carried out based on the design matrix. The input variables considered were laser power, pulse frequency, pulse duration, and TIG current. The response variable considered was the DOP. Multiple-regression model was developed correlating the process variables with the DOP using the generated data. The regression model was used for evaluating the objective function in GA. GA-based model was developed and it produced a set of solutions. Tournament and roulette wheel selection methods were used during the execution of GA. It was found that both the selection methods identified similar welding process parameters for achieving the maximum DOP. Excellent agreement was observed between the target DOP and the DOP values obtained in the validation experiments during hybrid laser–TIG welding.     

Effect of Traverse Speed on Microstructure and Microhardness of Cu/B4C Surface Composite Produced by Friction Stir Processing

Friction stir processing (FSP) has evolved as a potential candidate to fabricate surface composites. This paper investigates the influence of traverse speed on microstructure and microhardness of Cu/B₄C surface composite fabricated using FSP. The traverse speed was varied from 20 to 60 in steps of 20 mm/min. The tool rotational speed, axial force and groove width were kept constant. Optical microscopy and scanning electron microscopy were employed to study the microstructure of the fabricated surface composites. The results indicated that the traverse speed significantly influenced the area of the surface composite and distribution of B₄C particles. The area of the surface composite was found to bear an inversely proportional relationship to traverse speed. Lower traverse speed exhibited homogenous distribution of B₄C particles while higher traverse speed caused poor distribution of B₄C particles in the surface composite.