An aqueous-solution based low-temperature pathway to synthesize giant dielectric CaCu3Ti4O12-Highly porous ceramic matrix and submicron sized powder

A simple, cost-effective and environment-friendly pathway for preparing highly porous matrix of giant dielectric material CaCu3Ti4O12 (CCTO) through combustion of a completely aqueous precursor solution is presented. The pathway yields phase-pure and impurity-less CCTO ceramic at an ultra-low temperature (700 degrees C) and is better than traditional solid-state reaction schemes which fail to produce pure phase at as high temperature as 1000 degrees C (Li, Schwartz, Phys. Rev. B 75, 012104). The porous ceramic matrix on grinding produced CCTO powder having particle size in submicron order with an average size 300 nm. On sintering at 1050 degrees C for 5 h the powder shows high dielectric constants (>10(4) at all frequencies from 100 Hz to 100 kHz) and low loss (with 0.05 as the lowest value) which is suitable for device applications. The reaction pathway is expected to be extended to prepare other multifunctional complex perovskite materials. (C) 2010 Elsevier B.V. All rights reserved.

Low-temperature structure of two copper-based precursors for MOCVD: Aquabis(tert-butyl acetoacetato)copper(II) and Bis(dipivaloylmethanido)copper(II)

The Cu atoms in aquabis(tert-butyl acetoacetato)copper(II),[Cu(C8H13O3)(2)(H2O)], and bis(dipivaloylmethanido)copper(II), [Cu(C11H19O2)(2)], adopt square-pyramidal and planar conformations, respectively, with average Cu--O distances of 1.933 Angstrom in the former (not including the water ligand) and 1.892 Angstrom in the latter. It is interesting to note that the lability of the tert-butyl and methyl groups in both structures, which renders even the location of the terminal C atoms difficult, is reduced at T = 130 K, enabling location of all the protons in the difference Fourier map.

Critical buckling temperature of single-walled carbon nanotubes embedded in a one-parameter elastic medium based on nonlocal continuum mechanics

In this paper, the critical budding temperature of single-walled carbon nanotubes (SWCNTs), which are embedded in one-parameter elastic medium (Winkler foundation) is estimated under the umbrella of continuum mechanics theory. Nonlocal continuum theory is incorporated into Timoshenko beam model and the governing differential equations of motion are derived. An explicit expression for the non-dimensional critical buckling temperature is also derived in this work. The effect of the nonlocal small scale coefficient, the Winkler foundation parameter and the ratio of the length to the diameter on the critical buckling temperature is investigated in detail. It can be observed that the effects of nonlocal small scale parameter and the Winkler foundation parameter are significant and should be considered for thermal analysis of SWCNTs. The results presented in this paper can provide useful guidance for the study and design of the next generation of nanodevices that make use of the thermal buckling properties of embedded single-walled carbon nanotubes. (C) 2011 Elsevier B.V. All rights reserved.

The effect of temperature on the surface tension and adsorption functions of the Fe-S-O melts - an analysis based on interaction parameters

The present investigation analyses the thermodynamic behaviour of the surfaces and adsorption as a function of temperature and composition in the Fe-S-O melts based on the Butler's equations. The calculated-values of the surface tensions exhibit an elevation or depression depending on the type of the added solute at a concentration which coincides with that already present in the system. Generally, the desorption of the solutes as a function of temperature results in an initial increase followed by a decrease in the values of the surface tension. The observations are analyzed based on the surface interaction parameters which are derived in the present research.

Assessment of conditional moment closure models of turbulent autoignition using DNS data

A systematic assessment of the submodels of conditional moment closure (CMC) formalism for the autoignition problem is carried out using direct numerical simulation (DNS) data. An initially non-premixed, n-heptane/air system, subjected to a three-dimensional, homogeneous, isotropic, and decaying turbulence, is considered. Two kinetic schemes, (1) a one-step and (2) a reduced four-step reaction mechanism, are considered for chemistry An alternative formulation is developed for closure of the mean chemical source term , based on the condition that the instantaneous fluctuation of excess temperature is small. With this model, it is shown that the CMC equations describe the autoignition process all the way up to near the equilibrium limit. The effect of second-order terms (namely, conditional variance of temperature excess sigma(2) and conditional correlations of species q(ij)) in modeling is examined. Comparison with DNS data shows that sigma(2) has little effect on the predicted conditional mean temperature evolution, if the average conditional scalar dissipation rate is properly modeled. Using DNS data, a correction factor is introduced in the modeling of nonlinear terms to include the effect of species fluctuations. Computations including such a correction factor show that the species conditional correlations q(ij) have little effect on model predictions with a one-step reaction, but those q(ij) involving intermediate species are found to be crucial when four-step reduced kinetics is considered. The "most reactive mixture fraction" is found to vary with time when a four-step kinetics is considered. First-order CMC results are found to be qualitatively wrong if the conditional mean scalar dissipation rate is not modeled properly. The autoignition delay time predicted by the CMC model compares excellently with DNS results and shows a trend similar to experimental data over a range of initial temperatures.

A Flexure-based Deployable Stereo Vision Mechanism and Temperature and Force Sensors for Laparoscopic Tools

This paper presents concepts, designs, and working prototypes of enhanced laparoscopic surgical tools. The enhancements are in equipping the tool with force and temperature sensing as well as image acquisition for stereo vision. Just as the pupils of our eyes are adequately spaced out and the distance between them is adjustable, two minute cameras mounted on a mechanism in our design can be moved closer or farther apart inside the inflated abdomen during the surgery. The cameras are fitted to a deployable mechanism consisting of flexural joints so that they can be inserted through a small incision and then deployed and moved as needed.A temperature sensor and a force sensor are mounted on either of the gripping faces of the surgical grasping tool to measure the temperature and gripping force, which need to be controlled for safe laparoscopic surgery. The sensors are small enough and hence they do not cause interference during surgery and insertion.Prototyping and working of the enhanced laparoscopic tool are presented with details

Temperature deformation behaviour of a Mg-0.8Al alloy

There is considerable interest currently in developing magnesium based alloys as replacements for aluminum alloys in automobile applications, due to their high specific strength as compared to aluminum alloys. However, the poor formability of magnesium alloys has restricted their applications; superplasticity can be utilized to form components with complex shapes. In the present study, the compressive deformation characteristics of a Mg-0.8 wt% Al alloy with an initial grain size of 19 +/- 1.0 mum have been studied in the temperature range of 623-673 K and at strain rates ranging from 10(-7) to 10(-3) s(-1). The stress exponent was observed to decrease with a decrease in stress. The results are analyzed in terms of the existing theoretical models for high temperature deformation. Furthermore, the potential for superplasticity in this alloy is explored, based on the mechanical and microstructural characteristics of the alloy.

Carbon based materials for low temperature detection

Resistance temperature detectors (RTDs) are being widely used to detect low temperature, while thermocouples (TCs) are being used to detect high temperature. The materials suitable for RTDs are platinum, germanium, carbon, carbon-glass, cernox, etc. Here, we have reported the possible application of another form of carbon i.e. carbon nanotubes in low temperature thermometry. It has been shown the resistance R and the sensitivity of carbon nanotube bundles can be tuned and made suitable for ultralow temperature detection. We report on the R-T measurement of carbon nanotube bundles from room temperature down to 1 K to felicitate the possible application of bundles in low temperature RTDs. ©2008 American Institute of Physics

Voltage and Temperature Scalable Gate Delay and Slew Models Including Intra-Gate Variations

We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

Voltage and Temperature Scalable Gate Delay and Slew Models Including Intra-Gate Variations

We investigate the feasibility of developing a comprehensive gate delay and slew models which incorporates output load, input edge slew, supply voltage, temperature, global process variations and local process variations all in the same model. We find that the standard polynomial models cannot handle such a large heterogeneous set of input variables. We instead use neural networks, which are well known for their ability to approximate any arbitrary continuous function. Our initial experiments with a small subset of standard cell gates of an industrial 65 nm library show promising results with error in mean less than 1%, error in standard deviation less than 3% and maximum error less than 11% as compared to SPICE for models covering 0.9- 1.1 V of supply, -40degC to 125degC of temperature, load, slew and global and local process parameters. Enhancing the conventional libraries to be voltage and temperature scalable with similar accuracy requires on an average 4x more SPICE characterization runs.

How good are the simulations of tropical SST-rainfall relationship by IPCC AR4 atmospheric and coupled models?

The failure of atmospheric general circulation models (AGCMs) forced by prescribed SST to simulate and predict the interannual variability of Indian/Asian monsoon has been widely attributed to their inability to reproduce the actual sea surface temperature (SST)-rainfall relationship in the warm Indo-Pacific oceans. This assessment is based on a comparison of the observed and simulated correlation between the rainfall and local SST. However, the observed SSTconvection/rainfall relationship is nonlinear and for this a linear measure such as the correlation is not an appropriate measure. We show that the SST-rainfall relationship simulated by atmospheric and coupled general circulation models in IPCC AR4 is nonlinear, as observed, and realistic over the tropical West Pacific (WPO) and the Indian Ocean (IO). The SST-rainfall pattern simulated by the coupled versions of these models is rather similar to that from the corresponding atmospheric one, except for a shift of the entire pattern to colder/warmer SSTs when there is a cold/warm bias in the coupled version.

Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

New insights into designing metallacarborane based room temperature hydrogen storage media

Metallacarboranes are promising towards realizing room temperature hydrogen storage media because of the presence of both transition metal and carbon atoms. In metallacarborane clusters, the transition metal adsorbs hydrogen molecules and carbon can link these clusters to form metal organic framework, which can serve as a complete storage medium. Using first principles density functional calculations, we chalk out the underlying principles of designing an efficient metallacarborane based hydrogen storage media. The storage capacity of hydrogen depends upon the number of available transition metal d-orbitals, number of carbons, and dopant atoms in the cluster. These factors control the amount of charge transfer from metal to the cluster, thereby affecting the number of adsorbed hydrogen molecules. This correlation between the charge transfer and storage capacity is general in nature, and can be applied to designing efficient hydrogen storage systems. Following this strategy, a search for the best metallacarborane was carried out in which Sc based monocarborane was found to be the most promising H-2 sorbent material with a 9 wt.% of reversible storage at ambient pressure and temperature. (C) 2013 AIP Publishing LLC.