Effect of annealing temperature on electrical and nano-structural properties of sol-gel derived ZnO thin films

Zinc oxide (ZnO) thin films have been prepared on silicon substrates by sol-gel spin coating technique with spinning speed of 3,000 rpm. The films were annealed at different temperatures from 200 to 500 A degrees C and found that ZnO films exhibit different nanostructures at different annealing temperatures. The X-ray diffraction (XRD) results showed that the ZnO films convert from amorphous to polycrystalline phase after annealing at 400 A degrees C. The metal oxide semiconductor (MOS) capacitors were fabricated using ZnO films deposited on pre-cleaned silicon (100) substrates and electrical properties such as current versus voltage (I-V) and capacitance versus voltage (C-V) characteristics were studied. The electrical resistivity decreased with increasing annealing temperature. The oxide capacitance was measured at different annealing temperatures and different signal frequencies. The dielectric constant and the loss factor (tan delta) were increased with increase of annealing temperature.

Low-temperature polaronic relaxations with variable range hopping conductivity in FeTiMO(6) (M = Ta,Nb,Sb)

Low-temperature dielectric measurements on FeTiMO(6) (M = Ta,Nb,Sb) rutile-type oxides at frequencies from 0.1 Hz to 10 MHz revealed anomalous dielectric relaxations with frequency dispersion. Unlike the high-temperature relaxor response of these materials, the low-temperature relaxations are polaronic in nature. The relationship between frequency and temperature of dielectric loss peak follows T(-1/4) behavior. The frequency dependence of ac conductivity shows the well-known universal dielectric response, while the dc conductivity follows Mott variable range hopping (VRH) behavior, confirming the polaronic origin of the observed dielectric relaxations. The frequency domain analysis of the dielectric spectra shows evidence for two relaxations, with the high-frequency relaxations following Mott VRH behavior more closely. Significantly, the Cr- and Ga-based analogs, CrTiNbO(6) and GaTiMO(6) (M = Ta,Nb), that were also studied, did not show these anomalies.

Pyrochlore ``dynamic spin-ice'' Pr(2)Sn(2)O(7) and monoclinic Pr(2)Ti(2)O(7): A comparative temperature-dependent Raman study

Here we report a temperature-dependent Raman study of the pyrochlore ``dynamic spin-ice'' compound Pr(2)Sn(2)O(7) and compare the results with its non-pyrochlore (monoclinic) counterpart Pr(2)Ti(2)O(7). In addition to phonon modes, we observe two bands associated with electronic Raman scattering involving crystal field transitions in Pr(2)Sn(2)O(7) at similar to 135 and 460 cm(-1) which couple strongly to phonons. Anomalous temperature dependence of phonon frequencies that are observed in Pyrochlore Pr(2)Sn(2)O(7) are absent in monoclinic Pr(2)Ti(2)O(7). This, therefore, confirms that the strong phonon-phonon anharmonic interactions, responsible for the temperature-dependent anomalous behavior of phonons, arise due to the inherent vacant sites in the pyrochlore structure. (C) 2011 Elsevier Inc. All rights reserved.

Role of rigidity and temperature in the kinetics of photodarkening in Ge(x)As((45-x))Se(55) thin films

We present insightful results on the kinetics of photodarkening (PD) in Ge(x)As(45-x)Se(55) glasses at the ambient and liquid helium temperatures when the network rigidity is increased by varying x from 0 to 16. We observe a many fold change in PD and its kinetics with decreasing network flexibility and temperature. Moreover, temporal evolution of PD shows a dramatic change with increasing x. (C)2011 Optical Society of America

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

Albedo enhancement of marine clouds to counteract global warming: impacts on the hydrological cycle

Recent studies have shown that changes in solar radiation affect the hydrological cycle more strongly than equivalent CO(2) changes for the same change in global mean surface temperature. Thus, solar radiation management ``geoengineering'' proposals to completely offset global mean temperature increases by reducing the amount of absorbed sunlight might be expected to slow the global water cycle and reduce runoff over land. However, proposed countering of global warming by increasing the albedo of marine clouds would reduce surface solar radiation only over the oceans. Here, for an idealized scenario, we analyze the response of temperature and the hydrological cycle to increased reflection by clouds over the ocean using an atmospheric general circulation model coupled to a mixed layer ocean model. When cloud droplets are reduced in size over all oceans uniformly to offset the temperature increase from a doubling of atmospheric CO(2), the global-mean precipitation and evaporation decreases by about 1.3% but runoff over land increases by 7.5% primarily due to increases over tropical land. In the model, more reflective marine clouds cool the atmospheric column over ocean. The result is a sinking motion over oceans and upward motion over land. We attribute the increased runoff over land to this increased upward motion over land when marine clouds are made more reflective. Our results suggest that, in contrast to other proposals to increase planetary albedo, offsetting mean global warming by reducing marine cloud droplet size does not necessarily lead to a drying, on average, of the continents. However, we note that the changes in precipitation, evaporation and P-E are dominated by small but significant areas, and given the highly idealized nature of this study, a more thorough and broader assessment would be required for proposals of altering marine cloud properties on a large scale.

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.