Determination of various impurities in synthetic diamond powder

Impurities in industrial synthetic diamond powder samples were analyzed by X-ray diffraction (XRD) and Flame Atomic Absorption Spectrometry (FAAS). Specimen for FAAS is required in solution form. Diamonds are chemically inert to most acids and alkalies. Carbon was removed as CO₂ on heating and estimated gravimetrically. The remaining residue was fused with di-lithium tetraborate and dissolved in nitric acid. Impurities such as Si, Al, Fe, Ca, Mg, W, Na, Co and Ni were then determined by FAAS. Crystalline phases of major impurities were identified by XRD.     

Thermodynamic analysis and optimization of a novel two-stage transcritical N2O cycle

Thermodynamic (energy and exergy) analyses and optimization studies of two-stage transcritical N₂O and CO₂ cycles, incorporating compressor intercooling, are presented based on cycle simulation employing simultaneous optimization of intercooler pressure and gas cooler pressure. Further, performance comparisons with the basic single-stage cycles are also presented. The N₂O cycle exhibits higher cooling COP, lower optimum gas cooler pressure and discharge temperature and higher second law efficiency as compared to an equivalent CO₂ cycle. However, two-stage compression with intercooling yields lesser COP improvement for N₂O compared to CO₂. Based on the cycle simulations, correlations of optimum gas cooler pressure and inter-stage pressure in terms of gas cooler exit temperature and evaporator temperature are obtained. This is expected to be of help as a guideline in optimal design and operation of such systems.     

Size variation of polyaniline nanoparticles dispersed in polyvinyl alcohol matrix

We report the preparation of polyaniline (PANI) nanoparticles dispersed in polyvinyl alcohol (PVA) matrix. From SEM picture it is seen that the particle sizes vary from 100–20 nm. Also with increase in PVA content the stability of dispersion is found to increase. Apart from SEM, spin cast films of PANI in PVA are also characterized through XRD and FTIR. XRD shows increase in crystallinity with PVA content and FTIR gives evidence of crosslinking between PANI and PVA molecules. In plane electrical conductivity (in the range of 10² Scm⁻¹) and the exponent of nonlinear I–V are found to decrease with increase of PVA content. There is a good correlation between SEM, XRD, FTIR and electrical properties.     

Influence of temperature, voltage and hydrogen on the reversible transition of electrical conductivity in sol–gel grown nanocrystalline TiO2 thin film

Undoped nanocrystalline p-type TiO₂ thin film was deposited by sol–gel method on a thermally oxidized p-Si (2–5 Ω cm resistivity and $ \left\langle {100} \right\rangle $ orientation) substrate. The thin film was characterized by two-dimensional X-ray Diffraction (2D-XRD) and Field Emission Scanning Electron Microscopy (FESEM) to confirm the formation of stable nano crystalline anatase titania and to determine the grain size (~10 nm). Optical absorption spectroscopy was carried out to ascertain the band gap of the material. Two lateral Pd contacts were used as the metal electrodes to TiO₂ thin film to study the electrical conductivity. A clear p- to n-type transition was observed at 240 °C and a bias voltage of 0.83 V and the effect was enhanced on exposure to H₂ gas. The thin film showed fully n-type conductivity at 275 °C and 0.1 V. However, the reversal of the type of conductivity from n- to p-type was observed below 240 °C during lowering the temperature. The creation of oxygen vacancy and the diffusion of lattice oxygen to the surface of TiO₂ thin film might be the most possible mechanism of such transitions. Presence of hydrogen enhanced the process.     

A simple unsupervised MRF model based image segmentation approach

A simple technique has been suggested to obtain optimal segmentation based on tonal and textural characteristics of an image using the Markov random field (MRF) model. The technique takes an initially over segmented image as well as the original image as its inputs and defines an MRF over the region adjacency graph (RAG) of the initially segmented regions. A tonal-region based segmentation technique due to Kartikeyan and Sarkar (1989) has been used for initial segmentation. The energy function has been defined over the first order cliques of the MRF. The essence of this approach is primarily based on quantitative values of the second order statistics, on region characteristics and consequently deciding upon the action of merging neighboring regions using the F-statistic. The effectiveness of our approach is demonstrated with wide variety of real life examples viz., indoor, outdoor and satellite and a comparison of its output with that of a previous work in the literature has been provided.     

Review and comparative evaluation of symbolic dynamic filtering for detection of anomaly patterns

Symbolic dynamic filtering (SDF) has been recently reported in literature as a pattern recognition tool for early detection of anomalies (i.e., deviations from the nominal behavior) in complex dynamical systems. This paper presents a review of SDF and its performance evaluation relative to other classes of pattern recognition tools, such as Bayesian Filters and Artificial Neural Networks, from the perspectives of: (i) anomaly detection capability, (ii) decision making for failure mitigation and (iii) computational efficiency. The evaluation is based on analysis of time series data generated from a nonlinear active electronic system. This work has been supported in part by the U.S. Army Research Laboratory and the U.S. Army Research Office under Grant No. W911NF-07-1-0376, by the U.S. Office of Naval Research under Grant No. N00014-08-1-380, and by NASA under Cooperative Agreement No. NNX07AK49A.     

Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery.

This work deals with multisensor data fusion to obtain landcover classification. The role of feature-level fusion using the Dempster-Shafer rule and that of data-level fusion in the MRF context is studied in this paper to obtain an optimally segmented image. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two examples of data fusion of optical images and a synthetic aperture radar image are presented, each set having been acquired on different dates. Classification accuracies of the technique proposed are compared with those of some recent techniques in literature for the same image data.     

Partial replacement of metakaolin with red ceramic waste in geopolymer

Metakaolin was incrementally replaced (33.3%, 50% and 66.6%) by red ceramic waste in geopolymer formulation to study the effect on geopolymerisation and its resultant properties. The geopolymer binders composed of two calcined aluminosilicates (viz. Metakaolin and Red ceramic waste), NaOH and sodium silicate. In the experimental compositions, metakaolin was replaced gradually up to 66.6% in the clay fraction, the Si/Al increased from 3.36 to 5.16 and Na/Al increased from 0.93 to 1.38. The FTIR spectroscopic studies of geopolymer pastes along with XRD analysis indicated that the red ceramic waste partly reacts with alkali and takes part in geopolymer formation. Replacement of 33.3% metakaolin by the red ceramic waste in geopolymer binder did not reduce the compressive strength with respect to the pure metakaolin geopolymer here. Additional replacement resulted in a drastic decrease in the compressive strength of the geopolymer binder. However, the compressive strength of geopolymer mortars revealed interesting synergy between the amount of binder and particle packing in the mortar. Despite having a lower amount of binder phase, mortars with 33% and 50% red ceramic waste exhibited maximum compressive strength values. This has been attributed to improved particle packing through incorporation of red ceramic waste particles.