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.

Temperature scaling in a dense vibrofluidized granular material

The leading order "temperature" of a dense two-dimensional granular material fluidized by external vibrations is determined. The grain interactions are characterized by inelastic collisions, but the coefficient of restitution is considered to be close to 1, so that the dissipation of energy during a collision is small compared to the average energy of a particle. An asymptotic solution is obtained where the particles are considered to be elastic in the leading approximation. The velocity distribution is a Maxwell-Boltzmann distribution in the leading approximation,. The density profile is determined by solving the momentum balance equation in the vertical direction, where the relation between the pressure and density is provided by the virial equation of state. The temperature is determined by relating the source of energy due to the vibrating surface and the energy dissipation due to inelastic collisions. The predictions of the present analysis show good agreement with simulation results at higher densities where theories for a dilute vibrated granular material, with the pressure-density relation provided by the ideal gas law, sire in error. [:S1063-651X(99)04408-6].

Catalytic oxidative polymerization of 1,1-diphenylethylene at ambient temperature and potential application of peroxide macroinitiator

The Co(II)TPP(Py) complex was used as an efficient dioxygen carrier for the radical polymerization of 1,1-diphenylethylene (DPE), which has a low ceiling temperature, at ambient temperature and low oxygen pressure. The mechanism of polymerization is discussed' on the basis of kinetic data, W-vis, ESR, and H-1 NMR studies. The rate of polymerization (RP) and number-average molecular weights (M) of poly(1,1-diphenylethylene peroxide) (PDPEP) are higher and the polydispersity is lower than in 2,2'-azobis(isobutyronitrile) (AIBN) initiated polymerization. PDPEP was further. used as a macroinitiator for the polymerization of MMA. The polymerization obeys classical kinetics. The K-2 value of the PDPEP has been determined from the slope of R-P(2) VS [M](2)[I], which reveals that it can also be used at higher temperature for the polymerization. An "active" PMMA was also synthesized, containing initiating segments in the polymer backbone.

Voltage and Temperature Scalable Standard Cell Leakage Models Based on Stacks for Statistical Leakage Characterization

With extensive use of dynamic voltage scaling (DVS) there is increasing need for voltage scalable models. Similarly, leakage being very sensitive to temperature motivates the need for a temperature scalable model as well. We characterize standard cell libraries for statistical leakage analysis based on models for transistor stacks. Modeling stacks has the advantage of using a single model across many gates there by reducing the number of models that need to be characterized. Our experiments on 15 different gates show that we needed only 23 models to predict the leakage across 126 input vector combinations. We investigate the use of neural networks for the combined PVT model, for the stacks, which can capture the effect of inter die, intra gate variations, supply voltage(0.6-1.2 V) and temperature (0 - 100degC) on leakage. Results show that neural network based stack models can predict the PDF of leakage current across supply voltage and temperature accurately with the average error in mean being less than 2% and that in standard deviation being less than 5% across a range of voltage, temperature.

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.

Voltage and Temperature-Aware SSTA Using Neural Network Delay Model

With the emergence of voltage scaling as one of the most powerful power reduction techniques, it has been important to support voltage scalable statistical static timing analysis (SSTA) in deep submicrometer process nodes. In this paper, we propose a single delay model of logic gate using neural network which comprehensively captures process, voltage, and temperature variation along with input slew and output load. The number of simulation programs with integrated circuit emphasis (SPICE) required to create this model over a large voltage and temperature range is found to be modest and 4x less than that required for a conventional table-based approach with comparable accuracy. We show how the model can be used to derive sensitivities required for linear SSTA for an arbitrary voltage and temperature. Our experimentation on ISCAS 85 benchmarks across a voltage range of 0.9-1.1V shows that the average error in mean delay is less than 1.08% and average error in standard deviation is less than 2.85%. The errors in predicting the 99% and 1% probability point are 1.31% and 1%, respectively, with respect to SPICE. The two potential applications of voltage-aware SSTA have been presented, i.e., one for improving the accuracy of timing analysis by considering instance-specific voltage drops in power grids and the other for determining optimum supply voltage for target yield for dynamic voltage scaling applications.

Effect of temperature on the plastic zone size and the shear band density in a bulk metallic glass

High temperature bonded interface indentation experiments are carried out on a Zr based bulk metallic glass (BMG) to examine the plastic deformation characteristics in subsurface deformation zone under a Vickers indenter. The results show that the shear bands are semi-circular in shape and propagate in radial direction. At all temperatures the inter-band spacing along the indentation axis is found to increase with increasing distance from the indenter tip. The average shear band spacing monotonically increases with temperature whereas the shear band induced plastic deformation zone is invariant with temperature. These observations are able to explain the increase in pressure sensitive plastic flow of BMGs with temperature. (C) 2011 Elsevier B.V. All rights reserved.

Experiments on thermal response of low aspect ratio packed beds at high Reynolds numbers with varying inflow temperature

An experimental study for transient temperature response of low aspect ratio packed beds at high Reynolds numbers for a free stream with varying inlet temperature is presented. The packed bed is used as a compact heat exchanger along with a solid propellant gas-generator, to generate room temperature gases for use in applications such as control actuation and air bottle pressurization. Packed beds of lengths similar to 200 mm and 300 mm were characterized for packing diameter based Reynolds numbers, Re-d ranging from 0.6 x 10(4) to 8.5 x 10(4). The solid packing used in the bed consisted of circle divide 9.5 mm and circle divide 5 mm steel spheres with suitable arrangements to eliminate flow entrance and exit effects. The ratios of packed bed diameter to packing diameter for 9.5 mm and 5 mm sphere packing were similar to 9.5 and 18 respectively, with the average packed bed porosities around 0.4. Gas temperatures were measured at the entry, exit and at three axial locations along centre-line in the packed beds. The solid packing temperature was measured at three axial locations in the packed bed. An average Nusselt number correlation of the form Nu(d) = 3.91Re(d)(05) for Re-d range of 10(4) is proposed. For engineering applications of packed beds such as pebble bed heaters, thermal storage systems, and compact heat exchangers a simple procedure is suggested for calculating unsteady gas temperature at packed bed exit for packing Biot number Bi-d < 0.1. (C) 2012 Elsevier Inc. All rights reserved.

Cl-35 NQR frequency and spin lattice relaxation time in 3,4-dichlorophenol as a function of pressure and temperature

The pressure dependences of Cl-35 nuclear quadrupole resonance (NQR) frequency, temperature and pressure variation of spin lattice relaxation time (T-1) were investigated in 3,4-dichlorophenol. T-1 was measured in the temperature range 77-300 K. Furthermore, the NQR frequency and T-1 for these compounds were measured as a function of pressure up to 5 kbar at 300 K. The temperature dependence of the average torsional lifetimes of the molecules and the transition probabilities W-1 and W-2 for the Delta m = +/- 1 and Delta m = +/- 2 transitions were also obtained. A nonlinear variation of NQR frequency with pressure has been observed and the pressure coefficients were observed to be positive. A thermodynamic analysis of the data was carried out to determine the constant volume temperature coefficients of the NQR frequency. An attempt is made to compare the torsional frequencies evaluated from NQR data with those obtained by IR spectra. On selecting the appropriate mode from IR spectra, a good agreement with torsional frequency obtained from NQR data is observed. The previously mentioned approach is a good illustration of the supplementary nature of the data from IR studies, in relation to NQR studies of compounds in solid state.

Low temperature combustion synthesis and magnetostructural properties of Co-Mn nanoferrites

In the present work, Co1-xMnxFe2O4 nanoparticles were synthesized by the low-temperature auto-combustion method. The thermal decomposition process was investigated by means of differential and thermal gravimetric analysis (TG-DTA) that showed the precursor yield the final product above 450 degrees C. The phase purity and crystal lattice symmetry were estimated from X-ray diffraction (XRD). Microstructural features observed by scanning electron microscopy (SEM) demonstrates that the fine clustered particles were formed with an increase in average grain size with Mn2+ content. Fourier transform infrared spectroscopy (FTIR) study confirms the formation of spinel ferrite. Room temperature magnetization measurements showed that the magnetization M-s increases from 29 to 60 emu/g and H-c increases from 13 to 28 Oe with increase in Mn2+ content, which implies that these materials may be applicable for magnetic data storage and recording media. (C) 2013 Elsevier B.V. All rights reserved.

Local structural disorder and its influence on the average global structure and polar properties in Na0.5Bi0.5TiO3

Na0.5Bi0.5TiO3 (NBT) and its derivatives have prompted a great surge in interest owing to their potential as lead-free piezoelectrics. In spite of five decades since its discovery, there is still a lack of clarity on crucial issues such as the origin of significant dielectric relaxation at room temperature, structural factors influencing its depoling, and the status of the recently proposed monoclinic (Cc) structure vis-a-vis the nanosized structural heterogeneities. In this work, these issues are resolved by comparative analysis of local and global structures on poled and unpoled NBT specimens using electron, x-ray, and neutron diffraction in conjunction with first-principles calculation, dielectric, ferroelectric, and piezoelectric measurements. The reported global monoclinic (Cc) distortion is shown not to correspond to the thermodynamic equilibrium state at room temperature. The global monocliniclike appearance rather owes its origin to the presence of local structural and strain heterogeneities. Poling removes the structural inhomogeneities and establishes a long-range rhombohedral distortion. In the process the system gets irreversibly transformed from a nonergodic relaxor to a normal ferroelectric state. The thermal depoling is shown to be associated with the onset of incompatible in-phase tilted octahedral regions in the field-stabilized long range rhombohedral distortion.

Low temperature synthesis of pure cubic ZrO2 nanopowder: Structural and luminescence studies

Pure cubic zirconia (ZrO2) nanopowder is prepared for the first time by simple low temperature solution combustion method without calcination. The product is characterized by Powder X-ray Diffraction (PXRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Fourier Transform Infra Red spectroscopy (FTIR) and Ultraviolet-Visible spectroscopy (UV-Vis). The PXRD showed the formation of pure stable cubic ZrO2 nanopowders with average crystallite size ranging from 6 to 12 nm. The lattice parameters were calculated from Rietveld refinement method. SEM micrograph shows fluffy, mesoporous, agglomerated particles with large number of voids. TEM micrograph shows honey comb like arrangement of particles with particle size similar to 10 nm. The PL emission spectrum excited at 210 nm and 240 nm consists of intense bands centered at similar to 365 and similar to 390 nm. Both the samples show shoulder peak at 420 nm, along with four weak emission bands at similar to 484, similar to 528, similar to 614 and similar to 726 nm. TL studies were carried out pre-irradiating samples with gamma-rays ranging from 1 to 5 KGy at room temperature. A well resolved glow peak at 377 degrees C is recorded which can be ascribed to deep traps. With increase in gamma radiation there is linear increase in TL intensity which shows the possible use of ZrO2 as dosimetric material. (C) 2013 Elsevier B.V. All rights reserved.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data

Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of 2 degrees C than MODIS with an error of 3 degrees C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 degrees C & for MODIS data is 3.7 degrees C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect. (C) 2013 Elsevier Ltd. All rights reserved.