274 resultados para Nano-meter scale
Resumo:
In this study, we present the spontaneous self-assembly of designed simplest aromatic cyclic dipeptides of (L-Phg-L-Phg) and (D-Phg-L-Phg) to form highly stable two-dimensional (2D) nano- and mesosheets with large lateral surface area. Various microscopy data revealed that the morphology of 2D mesosheets resembles the hierarchical natural materials with layered structure. Solution and solid-state NMR studies on cyclo(L-Phg-L-Phg) revealed the presence of strong (N-H-O) hydrogen-bonded molecular chains supported by aromatic pi-pi interactions to form 2D mesosheets. Interestingly, cyclo(D-Phg-L-Phg) self-assembles to form single-crystalline as well as non-crystalline 2D rhomboid sheets with large lateral dimension. X-ray diffraction analysis revealed the stacking of (N-H-O) hydrogen-bonded molecular layers along c-axis supported by aromatic pi-pi interactions. The thermogravimetric analysis shows two transitions with overall high thermal stability attributed to layered hierarchy found in 2D mesosheets.
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We study the dynamics of a spherical steel ball falling freely through a solution of entangled wormlike-micelles. If the sphere diameter is larger than a threshold value, the settling velocity shows repeated short oscillatory bursts separated by long periods of relative quiescence. We propose a model incorporating the interplay of settling-induced flow, viscoelastic stress and, as in M. E. Cates, D. A. Head and A. Ajdari, Phys. Rev. E, 2002, 66, 025202(R) and A. Aradian and M. E. Cates, Phys. Rev. E, 2006, 73, 041508, a slow structural variable for which our experiments offer independent evidence.
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We have fabricated nano-Schottky diodes of CdTe QDs with platinum metal electrodes in metal-semiconductor-metal planar configuration by drop-casting. The observed high value of ideality factor (13.3) of the diode was possibly due to the presence of defects in colloidal QDs. We observed asymmetry and non-linear nature of I-V characteristics between forward and reverse directions, which has been explained in terms of size distributions of quantum dots due to coffee ring effect. Copyright 2011 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. doi:10.1063/1.3669408]
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The ternary alloy Ni-W-P and its WS2 nanocomposite coatings were successfully obtained on low-carbon steel using the electroless plating technique. The sodium tungstate (Na2WO4) concentration in the bath was varied to obtain Ni-W-P deposits containing various Ni and P contents. WS2 composite was obtained with a suitable concentration of Na2WO4 in Ni-P coating. These deposits were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray analysis (EDX) studies. The corrosion behavior was investigated by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) studies in 3.5 wt % NaCl solutions, and the corrosion rates of the coatings for Ni-P, Ni-W-P, and Ni-W-P-WS2 were found to be 2.571 x 10(-5), 8.219 x 10(-7), and 7.986 x 10(-7) g/h, respectively. An increase in the codeposition of alloying metal tungsten (W) enhanced the corrosion resistance and microhardness and changed the structure and morphology of the deposits. Incorporation of WS2 nanoparticles to Ni-W-P alloy coating reduced the coefficient of friction from 0.16 to 0.11 and also helped in improving the corrosion resistance of the coating further.
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We have demonstrated a simple, scalable and inexpensive method based on microwave plasma for synthesizing 5 to 10 g/h of nanomaterials. Luminescent nano silicon particles were synthesized by homogenous nucleation of silicon vapour produced by the radial injection of silicon tetrachloride vapour and nano titanium nitride was synthesized by using liquid titanium tetrachloride as the precursor. The synthesized nano silicon and titanium nitride powders were characterized by XRD, XPS, TEM, SEM and BET. The characterization techniques indicated that the synthesized powders were indeed crystalline nanomaterials.
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Nano-ceramic phosphor CaSiO 3 doped with Pb and Mn was synthesized by the low temperature solution combustion method. The materials were characterized by Powder X-Ray Diffraction (XRD), Thermo-gravimetric and Differential Thermal Analysis (TG-DTA), Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). The Electron Paramagnetic Resonance (EPR) spectrum of the investigated sample exhibits a broad resonance signal centered at g=1.994. The number of spins participating in resonance (N) and its paramagnetic susceptibility (�) have been evaluated. Photoluminescence of doped CaSiO 3 was investigated when excited by UV radiation of 256 nm. The phosphor exhibits an emission peak at 353 nm in the UV range due to Pb 2+. Further, a broad emission peak in the visible range 550-625 nm can be attributed to 4T 1� 6A 1 transition of Mn 2+ ions. The investigation reveals that doping perovskite nano-ceramics with transition metal ions leads to excellent phosphor materials for potential applications. © 2012 Elsevier Ltd and Techna Group S.r.l.
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The Zn-CeO 2 composite coatings through electrodeposition technique were successfully fabricated on mild steel substrate. As a comparison pure zinc coating was also prepared. The concentration of CeO 2 nanoparticles was varied in the electrolytic bath and the composites were electrodeposited both in the presence and absence of cetyltriammonium bromide (CTAB). The performance of the CeO 2 nanoparticles towards the deposition, crystal structure, texture, surface morphology and electrochemical corrosion behavior was studied. For characterizations of the electrodeposits, the techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM) were used. Both the additives ceria and surfactant polarize the reduction processes and thus influence the deposition process, surface nature and the electrochemical properties. The electrochemical experiments like potentiodynamic polarization and electrochemical impedance spectroscopic (EIS) studies carried out in 3.5 wt. NaCl solution explicit higher corrosion resistance by CeO 2 incorporated coating in the presence of surfactant. © 2012 Elsevier B.V. All rights reserved.
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Exascale systems of the future are predicted to have mean time between failures (MTBF) of less than one hour. Malleable applications, where the number of processors on which the applications execute can be changed during executions, can make use of their malleability to better tolerate high failure rates. We present AdFT, an adaptive fault tolerance framework for long running malleable applications to maximize application performance in the presence of failures. AdFT framework includes cost models for evaluating the benefits of various fault tolerance actions including checkpointing, live-migration and rescheduling, and runtime decisions for dynamically selecting the fault tolerance actions at different points of application execution to maximize performance. Simulations with real and synthetic failure traces show that our approach outperforms existing fault tolerance mechanisms for malleable applications yielding up to 23% improvement in application performance, and is effective even for petascale systems and beyond.
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Plasmonic interactions in a well-defined array of metallic nanoparticles can lead to interesting optical effects, such as local electric field enhancement and shifts in the extinction spectra, which are of interest in diverse technological applications, including those pertaining to biochemical sensing and photonic circuitry. Here, we report on a single-step wafer scale fabrication of a three-dimensional array of metallic nanoparticles whose sizes and separations can be easily controlled to be anywhere between fifty to a few hundred nanometers, allowing the optical response of the system to be tailored with great control in the visible region of the spectrum. The substrates, apart from having a large surface area, are inherently porous and therefore suitable for optical sensing applications, such as surface enhanced Raman scattering, containing a high density of spots with enhanced local electric fields arising from plasmonic couplings.
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Recent studies show that fast climate response on time scales of less than a month can have important implications for long-term climate change. In this study, we investigate climate response on the time scale of days to weeks to a step-function quadrupling of atmospheric CO2 and contrast this with the response to a 4% increase in solar irradiance. Our simulations show that significant climate effects occur within days of a stepwise increase in both atmospheric CO2 content and solar irradiance. Over ocean, increased atmospheric CO2 warms the lower troposphere more than the surface, increasing atmospheric stability, moistening the boundary layer, and suppressing evaporation and precipitation. In contrast, over ocean, increased solar irradiance warms the lower troposphere to a much lesser extent, causing a much smaller change in evaporation and precipitation. Over land, both increased CO2 and increased solar irradiance cause rapid surface warming that tends to increase both evaporation and precipitation. However, the physiological effect of increased atmospheric CO2 on plant stomata reduces plant transpiration, drying the boundary layer and decreasing precipitation. This effect does not occur with increased solar irradiance. Therefore, differences in climatic effects from CO2 versus solar forcing are manifested within days after the forcing is imposed.
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We report on the large scale synthesis of millimetre long buckled multiwalled carbon nanotubes by one-step pyrolysis. Current carrying capability of a highly buckled region is shown to be more as compared to a less buckled region.
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Detecting and quantifying the presence of human-induced climate change in regional hydrology is important for studying the impacts of such changes on the water resources systems as well as for reliable future projections and policy making for adaptation. In this article a formal fingerprint-based detection and attribution analysis has been attempted to study the changes in the observed monsoon precipitation and streamflow in the rain-fed Mahanadi River Basin in India, considering the variability across different climate models. This is achieved through the use of observations, several climate model runs, a principal component analysis and regression based statistical downscaling technique, and a Genetic Programming based rainfall-runoff model. It is found that the decreases in observed hydrological variables across the second half of the 20th century lie outside the range that is expected from natural internal variability of climate alone at 95% statistical confidence level, for most of the climate models considered. For several climate models, such changes are consistent with those expected from anthropogenic emissions of greenhouse gases. However, unequivocal attribution to human-induced climate change cannot be claimed across all the climate models and uncertainties in our detection procedure, arising out of various sources including the use of models, cannot be ruled out. Changes in solar irradiance and volcanic activities are considered as other plausible natural external causes of climate change. Time evolution of the anthropogenic climate change ``signal'' in the hydrological observations, above the natural internal climate variability ``noise'' shows that the detection of the signal is achieved earlier in streamflow as compared to precipitation for most of the climate models, suggesting larger impacts of human-induced climate change on streamflow than precipitation at the river basin scale.
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Critical applications like cyclone tracking and earthquake modeling require simultaneous high-performance simulations and online visualization for timely analysis. Faster simulations and simultaneous visualization enable scientists provide real-time guidance to decision makers. In this work, we have developed an integrated user-driven and automated steering framework that simultaneously performs numerical simulations and efficient online remote visualization of critical weather applications in resource-constrained environments. It considers application dynamics like the criticality of the application and resource dynamics like the storage space, network bandwidth and available number of processors to adapt various application and resource parameters like simulation resolution, simulation rate and the frequency of visualization. We formulate the problem of finding an optimal set of simulation parameters as a linear programming problem. This leads to 30% higher simulation rate and 25-50% lesser storage consumption than a naive greedy approach. The framework also provides the user control over various application parameters like region of interest and simulation resolution. We have also devised an adaptive algorithm to reduce the lag between the simulation and visualization times. Using experiments with different network bandwidths, we find that our adaptive algorithm is able to reduce lag as well as visualize the most representative frames.