Low temperature molten-salt synthesis of nanocrystalline cubic Sr2SbMnO6

Sr2SbMnO6 (SSM) powders were successfully synthesized at reasonably low temperatures via molten-salt synthesis (MSS) method using eutectic composition of 0.635 Li2SO4-0.365 Na2SO4 (flux). High-temperature cubic phase SSM was stabilized at room temperature by calcining the as-synthesized powders at 900 degrees C/10 h. The phase formation and morphology of these powders were characterized via X-ray powder diffraction and scanning electron microscopy, respectively. The SSM phase formation associated with similar to 60 nm sized crystallites was also confirmed by transmission electron microscopy. The activation energy associated with the particle growth was found to be 95 +/- 5 kJ mol(-1). The dielectric constant of the tetragonal phase of the ceramic (fabricated using this cubic phase powder) with and without the flux (sulphates) has been monitored as a function of frequency (100 Hz-1 MHz) at room temperature. Internal barrier layer capacitance (IBLC) model was invoked to rationalize the dielectric properties.

Image fusion in GRDSS for Land use Mapping

Image fusion techniques are useful to integrate the geometric detail of a high-resolution panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MSS) image, particularly important for understanding land use dynamics at larger scale (1:25000 or lower), which is required by the decision makers to adopt holistic approaches for regional planning. Fused images can extract features from source images and provide more information than one scene of MSS image. High spectral resolution aids in identification of objects more distinctly while high spatial resolution allows locating the objects more clearly. The geoinformatics technologies with an ability to provide high-spatial-spectral-resolution data helps in inventorying, mapping, monitoring and sustainable management of natural resources. Fusion module in GRDSS, taking into consideration the limitations in spatial resolution of MSS data and spectral resolution of PAN data, provide high-spatial-spectral-resolution remote sensing images required for land use mapping on regional scale. GRDSS is a freeware GIS Graphic User Interface (GUI) developed in Tcl/Tk is based on command line arguments of GRASS (Geographic Resources Analysis Support System) with the functionalities for raster analysis, vector analysis, site analysis, image processing, modeling and graphics visualization. It has the capabilities to capture, store, process, analyse, prioritize and display spatial and temporal data.

Wetlands of Greater Bangalore, India: Automatic Delineation through Pattern Classifiers

Wetlands are the most productive and biologically diverse but very fragile ecosystems. They are vulnerable to even small changes in their biotic and abiotic factors. In recent years, there has been concern over the continuous degradation of wetlands due to unplanned developmental activities. This necessitates inventorying, mapping, and monitoring of wetlands to implement sustainable management approaches. The principal objective of this work is to evolve a strategy to identify and monitor wetlands using temporal remote sensing (RS) data. Pattern classifiers were used to extract wetlands automatically from NIR bands of MODIS, Landsat MSS and Landsat TM remote sensing data. MODIS provided data for 2002 to 2007, while for 1973 and 1992 IR Bands of Landsat MSS and TM (79m and 30m spatial resolution) data were used. Principal components of IR bands of MODIS (250 m) were fused with IRS LISS-3 NIR (23.5 m). To extract wetlands, statistical unsupervised learning of IR bands for the respective temporal data was performed using Bayesian approach based on prior probability, mean and covariance. Temporal analysis of wetlands indicates a sharp decline of 58% in Greater Bangalore attributing to intense urbanization processes, evident from a 466% increase in built-up area from 1973 to 2007.

Fusion of multi resolution remote sensing data for urban sprawl analysis

Urban population is growing at around 2.3 percent per annum in India. This is leading to urbanisation and often fuelling the dispersed development in the outskirts of urban and village centres with impacts such as loss of agricultural land, open space, and ecologically sensitive habitats. This type of upsurge is very much prevalent and persistent in most places, often inferred as sprawl. The direct implication of such urban sprawl is the change in land use and land cover of the region and lack of basic amenities, since planners are unable to visualise this type of growth patterns. This growth is normally left out in all government surveys (even in national population census), as this cannot be grouped under either urban or rural centre. The investigation of patterns of growth is very crucial from regional planning point of view to provide basic amenities in the region. The growth patterns of urban sprawl can be analysed and understood with the availability of temporal multi-sensor, multi-resolution spatial data. In order to optimise these spectral and spatial resolutions, image fusion techniques are required. This aids in integrating a lower spatial resolution multispectral (MSS) image (for example, IKONOS MSS bands of 4m spatial resolution) with a higher spatial resolution panchromatic (PAN) image (IKONOS PAN band of 1m spatial resolution) based on a simple spectral preservation fusion technique - the Smoothing Filter-based Intensity Modulation (SFIM). Spatial details are modulated to a co-registered lower resolution MSS image without altering its spectral properties and contrast by using a ratio between a higher resolution image and its low pass filtered (smoothing filter) image. The visual evaluation and statistical analysis confirms that SFIM is a superior fusion technique for improving spatial detail of MSS images with the preservation of spectral properties.

Robust Approach for Identification of Bad Data in State Estimation Using SLP Technique

This paper proposes a new approach for solving the state estimation problem. The approach is aimed at producing a robust estimator that rejects bad data, even if they are associated with leverage-point measurements. This is achieved by solving a sequence of Linear Programming (LP) problems. Optimization is carried via a new algorithm which is a combination of “upper bound optimization technique" and “an improved algorithm for discrete linear approximation". In this formulation of the LP problem, in addition to the constraints corresponding to the measurement set, constraints corresponding to bounds of state variables are also involved, which enables the LP problem more efficient in rejecting bad data, even if they are associated with leverage-point measurements. Results of the proposed estimator on IEEE 39-bus system and a 24-bus EHV equivalent system of the southern Indian grid are presented for illustrative purpose.

Spark plasma sintering of novel ZrB2-SiC-TiSi2 composites with better mechanical properties

We report here the development of ultrafine grained ZrB2-SiC composites using TiSi2 as the sintering aid and spark plasma sintering (SPS) as the processing technique. It was observed that the presence of TiSi2 improved the sinterability of the composites, such that near theoretical densification (99.9%) could be achieved for ZrB2-18 wt.% SiC-5 wt.% TiSi2 composites after SPS at 1600 degrees C for 10 min at 50 MPa. Use of innovative multi stage sintering (MSS) route, which involved holding the samples at lower (intermediate) temperatures for some time before holding at the final temperature, while keeping the net holding time to 10 min, allowed attainment of full densification of ZrB2-18 wt.% SiC-2.5 wt.% TiSi2 at a still lower final temperature of 1500 degrees C at 30 MPa. TEM observations, which revealed the presence of anisotropic ZrB2 grains with faceted grain boundaries and TiSi2 at the intergranular regions, suggested the occurrence of liquid phase sintering in the presence of TiSi2. No additional phase was detected in XRD as well as TEM, which confirmed the absence of any sintering reaction. The as developed composites possessed an excellent combination of Vickers hardness and indentation toughness, both of which increased with increase in TiSi2 content, such that the ZrBi2-18 wt.% SiC-5 wt.% TiSi2 (SPS processed at 1600 degrees C) possessed hardness of similar to 20 GPa and indentation toughness of similar to 5 MPa m(1/2). The use of MSS SPS at 1500 degrees C for ZrBi2-18 wt.% SiC-2.5 wt.% TiSi2 composite resulted in improvement in hardness of up to similar to 27 GPa and attainment of high flexural strength of similar to 455 MPa. (C) 2011 Elsevier B.V. All rights reserved.

High Temperature Phase Transition Studies and Dielectric Properties of Sr2SbMnO6

Sr2SbMnO6 (SSMO) ceramics were, fabricated using the nanocrystalline powders obtained via molten salt synthesis (MSS) method. High temperature X-ray diffraction studies confirmed the structural phase transition (room temperature tetragonal (I4/mcm) to the cubic phase (Pm-3m)) temperature to be around 736K. The discontinuity in the phase transition indicated its first order nature reflecting the presence of ferroelectric-like distortions in SSMO prepared from MSS which seemed to be unique as it was not observed so far in the case of SSMO prepared using solid-state reaction method. The dielectric behavior of SSMO was studied in the 300-950 K temperature range at high frequencies (MHz range) in order to suppress the of space charge and related effects that dominate at such higher temperatures and mask the real phase transition.

Synthesis, characterization, EPR and thermoluminescence properties of CaTiO3 nanophosphor

Calcium titanate (CaTiO3) nanophosphors were synthesized by three different routes namely solution combustion (SC), modified solid-state reaction (MSS) and solid-state (SS) methods. Rietveld refinement studies revealed the presence of an orthorhombic structure with traces of CaCO3. The crystallite sizes were found to be in the 43-45 nm range. TEM studies also confirm the nano size with well crystalline nature. EPR spectrum for SS method exhibits a broad resonance signal at g = 2.027 is attributed to TiO6](9-) center, whereas in MSS sample the resonance signals are attributed to surface electron and hole trapping sites. The TL behavior has been investigated for the first time using gamma-irradiation. TL glow peak at 169 degrees C were recorded in CaTiO3 prepared by SC, MSS and SS methods. The trapping parameters such as activation energy (E) and order of kinetics (b) were estimated using peak shape method and results are discussed in detail. (C) 2013 Elsevier Ltd. All rights reserved.

Integration of speckle de-noising and image segmentation using synthetic aperture radar image for flood extent extraction

Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.