Near cathode optical emission spectroscopy in N2-H2 glow discharge plasma

Optical emission spectroscopy (OES) is a non-intrusive diagnostic technique, widely used to study different kinds of plasmas. In the present work, a locally resolved OES technique was used to obtain near cathode (substrate) emission spectra for N₂-H₂ glow discharges. It was observed that, along with N₂⁺ and N₂ lines, the characteristic atomic nitrogen lines at 742.3 nm (3p ⁴S⁰_3/2 → 3s ⁴P_1/2), 744.2 nm (3p ⁴S⁰_3/2 → 3s ⁴P_3/2), 746.8 nm (3p ⁴S⁰_3/2 → 3s ⁴P_5/2) and H_α (656.3 nm) were the main emissions coming from the sheath region that shrouded the cathode. A qualitative analysis of the spectral lines near the cathode has been done in order to understand the mechanism of plasma nitriding and the role played by the hydrogen in the nitriding process. The decrease in local intensity of these atomic lines with hydrogen composition suggests that the effect of hydrogen is to enhance the sticking/adsorption of N on the cathode surface.     

Effect of nickel substitution on thermal properties of Na<Subscript>0·9</Subscript>CoO<Subscript>2</Subscript>

We report on the effect of nickel substitution in Na_0.9CoO₂ by examining their thermal properties at room temperature. Experimental results indicate that thermoelectric efficiency is enhanced upon nickel substitution in sodium cobaltate.     

Comparative measurements of HV impulses to evaluate different setsof response parameters

Results are reported of comparative measurements made in 14 HV (high-voltage) laboratories in ten different countries. The theory of the proposed methods of characterizing the dynamic behavior is given, and the parameters to be used are discussed. Comparative measurements made using 95 systems based on 53 dividers are analyzed. This analysis shows that many of the system now in use, even though they fulfil the basic response requirements of the standards, do not meet the accuracy requirements. Because no transfer measurements were made between laboratories, there is no way to detect similar errors in both the system under test and the reference system. Hence, the situation may be worse than reported. This has led to the recommendation that comparative measurements should be the main route for quantifying industrial impulse measuring systems     

Network model for strip-fed cavity-backed printed slot antenna

An equivalent network for the strip-fed cavity-backed slot antenna is derived. The model is based on some physical insight into the problem. The various parameters of the network are derived from the experimental data on the input reflection parameter of the antenna. This model gives an insight into the strip-slot-cavity coupling and hence the working of the structure. It is also useful for predicting the performance of such practical antennas.     

Parameter estimation in stochastic mammogram model by heuristic optimization techniques.

The appearance of disproportionately large amounts of high-density breast parenchyma in mammograms has been found to be a strong indicator of the risk of developing breast cancer. Hence, the breast density model is popular for risk estimation or for monitoring breast density change in prevention or intervention programs. However, the efficiency of such a stochastic model depends on the accuracy of estimation of the model's parameter set. We propose a new approach-heuristic optimization-to estimate more accurately the model parameter set as compared to the conventional and popular expectation-maximization (EM) algorithm. After initial segmentation of a given mammogram, the finite generalized Gaussian mixture (FGGM) model is constructed by computing the statistics associated with different image regions. The model parameter set thus obtained is estimated by particle swarm optimization (PSO) and evolutionary programming (EP) techniques, where the objective function to be minimized is the relative entropy between the image histogram and the estimated density distributions. When our heuristic approach was applied to different categories of mammograms from the Mini-MIAS database, it yielded lower floor of estimation error in 109 out of 112 cases (97.3 %), and 101 out of 102 cases (99.0%), for the number of image regions being five and eight, respectively, with the added advantage of faster convergence rate, when compared to the EM approach. Besides, the estimated density model preserves the number of regions specified by the information-theoretic criteria in all the test cases, and the assessment of the segmentation results by radiologists is promising.     

Synthesis and characterization of Znq2 and Znq2:CTAB particles for optical applications

High luminescent zinc (ii)-bis (8-hydroxyquinoline) Znq2 nanoparticles were synthesized by the simple precipitation method in pure form and with cetyltrimethyl ammonium bromide (CTAB) as cationic surfactant. The crystalline nature of title samples was confirmed by powder X-ray diffraction. Thermo gravimetric analysis and differential thermal analysis were carried out to find the thermal stability of the synthesized samples. The morphology and elemental analyses of the samples were studied by scanning electron microscope and energy dispersive X-ray analyser, respectively. The functional groups of these nanoparticles were analysed and assigned using the Fourier transform infrared spectroscopy spectral study. The optical property of Znq2 and Znq2:CTAB was confirmed by UV–vis–NIR spectral study. The band gap of Znq2 was calculated. The synthesized Znq2 and Znq2:CTAB nanoparticles were confirmed by photoluminescence studies for organic-light-emitting diode applications as emission and electron transport layers.     

Application of Artificial Neural Network Modelling for Optimization of Yb: YAG Laser Welding of Nitinol

This article presents the investigation of Ytterbium: Yttrium aluminium garnet (Yb: YAG) laser welding of NiTinol sheet of thickness 1 mm. Welding speed, shielding gas blown distance, focal position, laser power were selected as input parameters and depth of penetration, bead width, hardness, corrosion current density were measured as performance characteristics. Experiment was designed based on L9 Taguchi design with 4 factors and 3 levels in each factor. Modelling was done using artificial neural network in four learning algorithms namely batch back propagation, quick propagation, incremental back propagation and Legvenberg-Marquardt back propagation. A comparison was made between these learning algorithms and it was found that based on least error, Legvenberg-Marquardt model was the best learning algorithm. Genetic algorithm was implemented for predicting the optimised laser welding parameters in joining NiTinol and the confirmation test results were in good agreement with the predicted results.     

A simple and rapid method to graft hydroxyapatite on carbon nanotubes

Herein a simple and effective approach is introduced to functionalize single walled carbon nanotubes (SWCNTs) by in-situ grafting of hydroxyapatite (HA). The pristine SWCNTs were chemically activated through introduction of carboxylic groups on their surfaces by refluxing in the mixture of H(2)SO(4) and HNO(3). The resulting carboxylated SWCNTs were further utilized for grafting of HA. The Fourier transform infrared and Raman spectroscopic studies demonstrated the formation of HA and its grafting over SWCNTs. The phase composition of HA and existence Ca(2+) and PO(4) (3-) ions were studied using X-ray diffraction and energy dispersive X-ray analyses, respectively. The surface morphology of functionalized SWCNTs was analyzed using scanning electron microscopy and transmission electron microscopy. Thermogravimetric analysis confirmed the existence of HA on SWCNTs by exhibiting different thermogram for pure HA and functionalized SWCNTs. Overall this method produced uniform grafting of low crystalline HA on carboxylated SWCNTs with strong interfacial bonding.     

Molecular recognition of β-O-GlcNAc glycopeptides by a lectin-like receptor: binding modulation by the underlying Ser or Thr amino acids

The binding properties of different carbohydrates and glycopeptides containing the β-O-2-deoxy-2-(N-acetyl)-D-glucosaminyl (β-O-GlcNAc) to a synthetically prepared lectin-like receptor have been analyzed. The study combines the use of NMR spectroscopy experiments with extensive MD simulations in explicit water. Notably, the presence of a key hydrogen bond between the receptor and the OMe group of the β-O-GlcNAc-OMe derivative appears to be responsible for the high selectivity observed for this compound. In addition, to study the effect on the binding of the underlying amino acid, we have prepared different model glycopeptides, which include the non-natural α-methylserine and α-methylthreonine as underlying amino acids. Interestingly, the presence of a methyl group decreases the affinity constant, especially in those cases in which a β-methyl group is present. As a result, the serine-containing glycopeptide exhibited the highest affinity constant of the glycopeptides, and the threonine derivative showed the lowest one. This low selectivity could have its origin in the difficulty to form both specific hydrogen bonds and hydrophobic (CH-π) contacts.