Insulating State and Breakdown of Fermi Liquid Description in Molecular-Scale Single-Crystalline Wires of Gold

Electrical transport measurements on ultrathin single-crystalline Au nanowires, synthesized via a wet chemical route, show an unexpected insulating behavior. The linear response electrical resistance exhibits a power-law dependence on temperature. In addition, the variation of current over a wide range of temperature and voltage obeys a universal scaling relation that provides compelling evidence for a non-Fermi liquid behavior. Our results demonstrate that the quantum ground state In ultrathin nanowires of simple metallic systems can be radically different from their bulk counterparts and can be described In terms of a Tomonaga-Luttinger liquid (TLL), in the presence of remarkably strong electron-electron interactions.

Atomic Scale Fluctuations Govern Brittle Fracture and Cavitation Behavior in Metallic Glasses

We perform atomistic simulations on the fracture behavior of two typical metallic glasses, one brittle (FeP) and the other ductile (CuZr), and show that brittle fracture in the FeP glass is governed by an intrinsic cavitation mechanism near crack tips in contrast to extensive shear banding in the ductile CuZr glass. We show that a high degree of atomic scale spatial fluctuations in the local properties is the main reason for the observed cavitation behavior in the brittle metallic glass. Our study corroborates with recent experimental observations of nanoscale cavity nucleation found on the brittle fracture surfaces of metallic glasses and provides important insights into the root cause of the ductile versus brittle behavior in such materials.

Scale effects on buckling analysis of orthotropic nanoplates based on nonlocal two-variable refined plate theory

This article presents the buckling analysis of orthotropic nanoplates such as graphene using the two-variable refined plate theory and nonlocal small-scale effects. The two-variable refined plate theory takes account of transverse shear effects and parabolic distribution of the transverse shear strains through the thickness of the plate, hence it is unnecessary to use shear correction factors. Nonlocal governing equations of motion for the monolayer graphene are derived from the principle of virtual displacements. The closed-form solution for buckling load of a simply supported rectangular orthotropic nanoplate subjected to in-plane loading has been obtained by using the Navier's method. Numerical results obtained by the present theory are compared with first-order shear deformation theory for various shear correction factors. It has been proven that the nondimensional buckling load of the orthotropic nanoplate is always smaller than that of the isotropic nanoplate. It is also shown that small-scale effects contribute significantly to the mechanical behavior of orthotropic graphene sheets and cannot be neglected. Further, buckling load decreases with the increase of the nonlocal scale parameter value. The effects of the mode number, compression ratio and aspect ratio on the buckling load of the orthotropic nanoplate are also captured and discussed in detail. The results presented in this work may provide useful guidance for design and development of orthotropic graphene based nanodevices that make use of the buckling properties of orthotropic nanoplates.

Multi-scale interactions and predictability of the Indian summer monsoon

Following the seminal work of Charney and Shukla (198 1), the tropical climate is recognised to be more predictable than extra tropical climate as it is largely forced by 'external' slowly varying forcing and less sensitive to initial conditions. However, the Indian summer monsoon is an exception within the tropics where 'internal' low frequency (LF) oscillations seem to make significant contribution to its interannual variability (IAV) and makes it sensitive to initial conditions. Quantitative estimate of contribution of 'internal' dynamics to IAV of Indian monsoon is made using long experiments with an atmospheric general circulation model (AGCM) and through analysis of long daily observations. Both AGCM experiments and observations indicate that more than 50% of IAV of the monsoon is contributed by 'internal' dynamics making the predictable signal (external component) burried in unpredictable noise (internal component) of comparable amplitude. Better understanding of the nature of the 'internal' LF variability is crucial for any improvement in predicition of seasonal mean monsoon. Nature of 'internal' LF variability of the monsoon and mechanism responsible for it are investigated and shown that vigorous monsoon intraseasonal oscillations (ISO's) with time scale between 10-70 days are primarily responsible for generating the 'internal' IAV. The monsoon ISO's do this through scale interactions with synoptic disturbances (1-7 day time scale) on one hand and the annual cycle on the other. The spatial structure of the monsoon ISO's is similar to that of the seasonal mean. It is shown that frequency of occurance of strong (weak) phases of the ISO is different in different seasons giving rise to stronger (weaker) than normal monsoon. Change in the large scale circulation during strong (weak) phases of the ISO make it favourable (inhibiting) for cyclogenesis and gives rise to space time clustering of synoptic activity. This process leads to enhanced (reduced) rainfall in seasons of higher frequency of occurence strong (weak) phases of monsoon ISO.

On the role of cloud adjustment time scale in simulating precipitation with Relaxed Arakawa-Schubert convection scheme

The precipitation by Relaxed Arakawa-Schubert cumulus parameterization in a General Circulation Model (GCM) is sensitive to the choice of relaxation parameter or specified cloud adjustment time scale. In the present study, we examine sensitivity of simulated precipitation to the choice of cloud adjustment time scale (tau(adj)) over different parts of the tropics using National Center for Environmental Prediction (NCEP) Seasonal Forecast Model (SFM) during June-September. The results show that a single specified value of tau(adj) performs best only over a particular region and different values are preferred over different parts of the world. To find a relation between tau(adj) and cloud depth (convective activity) we choose six regions over the tropics. Based on the observed relation between outgoing long-wave radiation and tau(adj), we propose a linear cloud-type dependent relaxation parameter to be used in the model. The simulations over most parts of the tropics show improved results due to this newly formulated cloud-type dependent relaxation parameter.

Oscillatory settling in wormlike-micelle solutions: bursts and a long time scale

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.

AdFT: An Adaptive Framework for Fault Tolerance on Large Scale Systems using Application Malleability

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.

Climate response to changes in atmospheric carbon dioxide and solar irradiance on the time scale of days to weeks

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.

Large scale synthesis of ultralong aligned buckled multiwalled carbon nanotubes by one-step pyrolysis

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.

On the basin-scale detection and attribution of human-induced climate change in monsoon precipitation and streamflow

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.

Integrated parallelization of computations and visualization for large-scale applications

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.