Non-equilibrium segmental dynamics driven by multiwall carbon nanotubes in PS/PVME blends

The present paper discusses the effect of multiwall carbon nanotubes (MWNTs) on the structural relaxation and the intermolecular cooperativity in dynamically asymmetric blends of PS/PVME (polystyrene/poly(vinyl methyl ether)). The temperature regime where chain connectivity effects dominate the thermodynamic concentration fluctuation (T/T-g > 0.75, T-g is the glass transition temperature of the blends) was studied using dielectric spectroscopy (DS). Interestingly, in the blends with MWNTs a bimodal distribution of relaxation was obtained in the loss modulus spectra. This plausibly is due to different environments experienced by the faster component (PVME) in the presence of MWNTs. The segmental dynamics of PVME was observed to be significantly slowed down in the presence of MWNTs and an Arrhenius-type behavior, weakly dependent on temperature, is observed at higher frequencies. This non-equilibrium dynamics of PVME is presumed to be originating from interphase regions near the surface of MWNTs. The length scale of the cooperative rearranging region (xi CRR) at T-g, assessed by calorimetric measurements, was observed to be higher in the case of blends with MWNTs. An enhanced molecular level miscibility driven by MWNTs in the blends corroborates with the larger xi CRR and comparatively more number of segments in CRR (in contrast to neat blends) around T-g. The configurational entropy and length scale of the cooperative volume was mapped as a function of temperature in the temperature regime, Tg < T < T-g + 60 K. The blends phase separated by spinodal decomposition which further led to an interconnected PVME network in PS. This further led to materials with very high electrical conductivity upon demixing.

Regional flood frequency analysis using kernel- based fuzzy clustering approach

Regionalization approaches are widely used in water resources engineering to identify hydrologically homogeneous groups of watersheds that are referred to as regions. Pooled information from sites (depicting watersheds) in a region forms the basis to estimate quantiles associated with hydrological extreme events at ungauged/sparsely gauged sites in the region. Conventional regionalization approaches can be effective when watersheds (data points) corresponding to different regions can be separated using straight lines or linear planes in the space of watershed related attributes. In this paper, a kernel-based Fuzzy c-means (KFCM) clustering approach is presented for use in situations where such linear separation of regions cannot be accomplished. The approach uses kernel-based functions to map the data points from the attribute space to a higher-dimensional space where they can be separated into regions by linear planes. A procedure to determine optimal number of regions with the KFCM approach is suggested. Further, formulations to estimate flood quantiles at ungauged sites with the approach are developed. Effectiveness of the approach is demonstrated through Monte-Carlo simulation experiments and a case study on watersheds in United States. Comparison of results with those based on conventional Fuzzy c-means clustering, Region-of-influence approach and a prior study indicate that KFCM approach outperforms the other approaches in forming regions that are closer to being statistically homogeneous and in estimating flood quantiles at ungauged sites. Key Points Kernel-based regionalization approach is presented for flood frequency analysis Kernel procedure to estimate flood quantiles at ungauged sites is developed A set of fuzzy regions is delineated in Ohio, USA

Fluctuating micro-heterogeneity in water-tert-butyl alcohol mixtures and lambda-type divergence of the mean cluster size with phase transition-like multiple anomalies

Water-tert-butyl alcohol (TBA) binary mixture exhibits a large number of thermodynamic and dynamic anomalies. These anomalies are observed at surprisingly low TBA mole fraction, with x(TBA) approximate to 0.03-0.07. We demonstrate here that the origin of the anomalies lies in the local structural changes that occur due to self-aggregation of TBA molecules. We observe a percolation transition of the TBA molecules at x(TBA) approximate to 0.05. We note that ``islands'' of TBA clusters form even below this mole fraction, while a large spanning cluster emerges above that mole fraction. At this percolation threshold, we observe a lambda-type divergence in the fluctuation of the size of the largest TBA cluster, reminiscent of a critical point. Alongside, the structure of water is also perturbed, albeit weakly, by the aggregation of TBA molecules. There is a monotonic decrease in the tetrahedral order parameter of water, while the dipole moment correlation shows a weak nonlinearity. Interestingly, water molecules themselves exhibit a reverse percolation transition at higher TBA concentration, x(TBA) approximate to 0.45, where large spanning water clusters now break-up into small clusters. This is accompanied by significant divergence of the fluctuations in the size of largest water cluster. This second transition gives rise to another set of anomalies around. Both the percolation transitions can be regarded as manifestations of Janus effect at small molecular level. (C) 2014 AIP Publishing LLC.

Intense Acoustic Burst Ultrasound Modulated Optical Tomography for Elasticity Mapping of Soft Biological Tissue Mimicking Phantom: A Laser Speckle Contrast Analysis Study

This report addresses the assessment of variation in elastic property of soft biological tissues non-invasively using laser speckle contrast measurement. The experimental as well as the numerical (Monte-Carlo simulation) studies are carried out. In this an intense acoustic burst of ultrasound (an acoustic pulse with high power within standard safety limits), instead of continuous wave, is employed to induce large modulation of the tissue materials in the ultrasound insonified region of interest (ROI) and it results to enhance the strength of the ultrasound modulated optical signal in ultrasound modulated optical tomography (UMOT) system. The intensity fluctuation of speckle patterns formed by interference of light scattered (while traversing through tissue medium) is characterized by the motion of scattering sites. The displacement of scattering particles is inversely related to the elastic property of the tissue. We study the feasibility of laser speckle contrast analysis (LSCA) technique to reconstruct a map of the elastic property of a soft tissue-mimicking phantom. We employ source synchronized parallel speckle detection scheme to (experimentally) measure the speckle contrast from the light traversing through ultrasound (US) insonified tissue-mimicking phantom. The measured relative image contrast (the ratio of the difference of the maximum and the minimum values to the maximum value) for intense acoustic burst is 86.44 % in comparison to 67.28 % for continuous wave excitation of ultrasound. We also present 1-D and 2-D image of speckle contrast which is the representative of elastic property distribution.

Polymer-grafted multiwall carbon nanotubes functionalized by nitrene chemistry: effect on cooperativity and phase miscibility

The demixing of polystyrene (PS) and poly(vinyl methylether) (PVME) was systematically investigated in the presence of surface functionalized multiwall carbon nanotubes (MWNTs) by melt rheology. As PS-PVME blends are weakly interacting blends, the contribution of conformational entropy increases, resulting in thermo-rheological complexity wherein the concentration fluctuation persists even beyond the critical demixing temperature. These phenomenal changes were followed here in the presence of MWNTs with different surface functional groups. Polystyrene was synthesised by atom transfer radical polymerization and was immobilized onto carboxyl acid functionalized multiwall carbon nanotubes (COOH-MWNTs) via nitrene chemistry in order to improve the phase miscibility in PS-PVME blends. Interestingly, blends with 0.25 wt% polystyrene grafted multiwall carbon nanotubes (PS-g-MWNTs) delayed the spinodal decomposition temperature in the blends by similar to 33 degrees C with respect to both control blends and those with COOH-MWNTs. While the localization of COOH-MWNTs in PVME was explained from a thermodynamic point of view, the localization of PS-g-MWNTs was understood to result from favorable PS-PVME contact and the degree of surface coverage of PS on the surface of MWNTs. The length of the cooperative rearranging region (xi) decreased in presence of PS-g-MWNTs, suggesting confinement effects on large scale motions and enhanced interchain concentration fluctuation.

Sensitivity of simulated climate to latitudinal distribution of solar insolation reduction in solar radiation management

Solar radiation management (SRM) geoengineering has been proposed as a potential option to counteract climate change. We perform a set of idealized geoengineering simulations using Community Atmosphere Model version 3.1 developed at the National Center for Atmospheric Research to investigate the global hydrological implications of varying the latitudinal distribution of solar insolation reduction in SRM methods. To reduce the solar insolation we have prescribed sulfate aerosols in the stratosphere. The radiative forcing in the geoengineering simulations is the net forcing from a doubling of CO2 and the prescribed stratospheric aerosols. We find that for a fixed total mass of sulfate aerosols (12.6 Mt of SO4), relative to a uniform distribution which nearly offsets changes in global mean temperature from a doubling of CO2, global mean radiative forcing is larger when aerosol concentration is maximum at the poles leading to a warmer global mean climate and consequently an intensified hydrological cycle. Opposite changes are simulated when aerosol concentration is maximized in the tropics. We obtain a range of 1 K in global mean temperature and 3% in precipitation changes by varying the distribution pattern in our simulations: this range is about 50% of the climate change from a doubling of CO2. Hence, our study demonstrates that a range of global mean climate states, determined by the global mean radiative forcing, are possible for a fixed total amount of aerosols but with differing latitudinal distribution. However, it is important to note that this is an idealized study and thus not all important realistic climate processes are modeled.

Effect of High-Pressure Torsion on Texture, Microstructure, and Raman Spectroscopy: Case Study of Fe- and Te-Substituted CoSb3

Fe0.05Co0.95Sb2.875Te0.125, a double-element-substituted skutterudite, was prepared by induction melting, annealing, and hot pressing (HP). The hot-pressed sample was subjected to high-pressure torsion (HPT) with 4 GPa pressure at 673 K. X-ray diffraction was performed before and after HPT processing of the sample; the skutterudite phase was observed as a main phase, but an additional impurity phase (CoSb2) was observed in the HPT-processed sample. Surface morphology was determined by high-resolution scanning electron microscopy. In the HP sample, coarse grains with sizes in the range of approximately 100 nm to 300 nm were obtained. They changed to fine grains with a reduction in grain size to 75 nm to 125 nm after HPT due to severe plastic deformation. Crystallographic texture, as measured by x-ray diffraction, indicated strengthening of (112), (102) poles and weakening of the (123) pole of the HPT-processed sample. Raman-active vibrational modes showed a peak position shift towards the lower energy side, indicating softening of the modes after HPT. The distortion of the rectangular Sb-Sb rings leads to broadening of Sb-Sb vibrational modes due to local strain fluctuation. In the HPT process, a significant effect on the shorter Sb-Sb bond was observed as compared with the longer Sb-Sb bond.

De novo inference of protein function from coarse-grained dynamics

Inference of molecular function of proteins is the fundamental task in the quest for understanding cellular processes. The task is getting increasingly difficult with thousands of new proteins discovered each day. The difficulty arises primarily due to lack of high-throughput experimental technique for assessing protein molecular function, a lacunae that computational approaches are trying hard to fill. The latter too faces a major bottleneck in absence of clear evidence based on evolutionary information. Here we propose a de novo approach to annotate protein molecular function through structural dynamics match for a pair of segments from two dissimilar proteins, which may share even <10% sequence identity. To screen these matches, corresponding 1 mu s coarse-grained (CG) molecular dynamics trajectories were used to compute normalized root-mean-square-fluctuation graphs and select mobile segments, which were, thereafter, matched for all pairs using unweighted three-dimensional autocorrelation vectors. Our in-house custom-built forcefield (FF), extensively validated against dynamics information obtained from experimental nuclear magnetic resonance data, was specifically used to generate the CG dynamics trajectories. The test for correspondence of dynamics-signature of protein segments and function revealed 87% true positive rate and 93.5% true negative rate, on a dataset of 60 experimentally validated proteins, including moonlighting proteins and those with novel functional motifs. A random test against 315 unique fold/function proteins for a negative test gave >99% true recall. A blind prediction on a novel protein appears consistent with additional evidences retrieved therein. This is the first proof-of-principle of generalized use of structural dynamics for inferring protein molecular function leveraging our custom-made CG FF, useful to all. (C) 2014 Wiley Periodicals, Inc.

Vegetation impact on stream chemical fluxes: Mule Hole watershed (South India)

The proportion of chemical elements passing through vegetation prior to being exported in a stream was quantified for a forested tropical watershed(Mule Hole, South India) using an extensive hydrological and geochemical monitoring at several scales. First, a solute annual mass balance was established at the scale of the soil-plant profile for assessing the contribution of canopy interaction and litter decay to the solute fluxes of soil inputs (overland flow) and soil outputs (pore water flow as seepages). Second, based on the respective contributions of overland flow and seepages to the stream flow as estimated by a hydrological lumped model, we assigned the proportion of chemical elements in the stream that transited through the vegetation at both flood event (End Member Mixing Analysis) and seasonal scales. At the scale of the 1D soil-plant profile, leaching from the canopy constituted the main source of K above the ground surface. Litter decay was the main source of Si, whereas alkalinity, Ca and Mg originated in the same proportions from both sources. The contribution of vegetation was negligible for Na. Within the soil, all elements but Na were removed from the pore water in proportions varying from 20% for Cl to 95% for K: The soil output fluxes corresponded to a residual fraction of the infiltration fluxes. The behavior of K, Cl, Ca and Mg in the soil-plant profile can be explained by internal cycling, as their soil output fluxes were similar to the atmospheric inputs. Na was released from soils as a result of Na-plagioclase weathering and accompanied by additional release of Si. Concentration of soil pore water by evapotranspiration might limit the chemical weathering in the soil. Overall, the solute K, Ca, Mg, alkalinity and Si fluxes associated with the vegetation turnover within the small experimental watershed represented 10-15 times the solute fluxes exported by the stream, of which 83-97% transited through the vegetation. One important finding is that alkalinity and Si fluxes at the outlet were not linked to the ``current weathering'' of silicates in this watershed. These results highlight the dual effect of the vegetation cover on the solute fluxes exported from the watershed: On one hand the runoff was limited by evapotranspiration and represented only 10% of the annual rainfall, while on the other hand, 80-90% of the overall solute flux exported by the stream transited through the vegetation. The approach combining geochemical monitoring and accurate knowledge of the watershed hydrological budget provided detailed understanding of several effects of vegetation on stream fluxes: (1) evapotranspiration (limiting), (2) vertical transfer through vegetation from vadose zone to ground surface (enhancing) and (3) redistribution by throughfalls and litter decay. It provides a good basis for calibrating geochemical models and more precisely assessing the role of vegetation on soil processes. (C) 2014 Elsevier Ltd. All rights reserved.

An assessment of terrestrial water storage, rainfall and river discharge over Northern India from satellite data

Terrestrial water storage (TWS) plays a key role in the global water cycle and is highly influenced by climate variability and human activities. In this study, monthly TWS, rainfall and Ganga-Brahmaputra river discharge (GBRD) are analysed over India for the period of 2003-12 using remote sensing satellite data. The spatial pattern of mean TWS shows a decrease over a large and populous region of Northern India comprising the foothills of the Himalayas, the Indo-Gangetic Plains and North East India. Over this region, the mean monthly TWS exhibits a pronounced seasonal cycle and a large interannual variability, highly correlated with rainfall and GBRD variations (r > 0.8) with a lag time of 2 months and 1 month respectively. The time series of monthly TWS shows a consistent and statistically significant decrease of about 1 cm year(-1) over Northern India, which is not associated with changes in rainfall and GBRD. This recent change in TWS suggests a possible impact of rapid industrialization, urbanization and increase in population on land water resources. Our analysis highlights the potential of the Earth-observation satellite data for hydrological applications.

Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

Effect of epitaxial strain on phase separation in thin films

In epitaxially grown alloy thin films, spinodal decomposition may be promoted or suppressed depending on the sign of the epitaxial strain. We study this asymmetry by extending Cahn's linear theory of spinodal decomposition to systems with a composition dependent lattice parameter and modulus (represented by Vegard's law coefficients, GRAPHICS] and y, respectively), and an imposed (epitaxial) strain (e). We show analytically (and confirm using simulations) that the asymmetric effect of epitaxial strains arises only in elastically inhomogeneous systems. Specifically, we find good agreement between analytical and simulation results for the wave number GRAPHICS] of the fastest growing composition fluctuation. The asymmetric effect due to epitaxial strain also extends to microstructure formation: our simulations show islands of elastically softer (harder) phase with (without) a favourable imposed strain. We discuss the implications of these results to GeSi thin films on Si and Ge substrates, as well as InGaAs films on GaAs substrates.

Sensitivity of polarization fluctuations to the nature of protein-water interactions: Study of biological water in four different protein-water systems

Since the time of Kirkwood, observed deviations in magnitude of the dielectric constant of aqueous protein solution from that of neat water (similar to 80) and slower decay of polarization have been subjects of enormous interest, controversy, and debate. Most of the common proteins have large permanent dipole moments (often more than 100 D) that can influence structure and dynamics of even distant water molecules, thereby affecting collective polarization fluctuation of the solution, which in turn can significantly alter solution's dielectric constant. Therefore, distance dependence of polarization fluctuation can provide important insight into the nature of biological water. We explore these aspects by studying aqueous solutions of four different proteins of different characteristics and varying sizes, chicken villin headpiece subdomain (HP-36), immunoglobulin binding domain protein G (GB1), hen-egg white lysozyme (LYS), and Myoglobin (MYO). We simulate fairly large systems consisting of single protein molecule and 20000-30000 water molecules (varied according to the protein size), providing a concentration in the range of similar to 2-3 mM. We find that the calculated dielectric constant of the system shows a noticeable increment in all the cases compared to that of neat water. Total dipole moment auto time correlation function of water < dM(W) (0)delta M-W (t) > is found to be sensitive to the nature of the protein. Surprisingly, dipole moment of the protein and total dipole moment of the water molecules are found to be only weakly coupled. Shellwise decomposition of water molecules around protein reveals higher density of first layer compared to the succeeding ones. We also calculate heuristic effective dielectric constant of successive layers and find that the layer adjacent to protein has much lower value (similar to 50). However, progressive layers exhibit successive increment of dielectric constant, finally reaching a value close to that of bulk 4-5 layers away. We also calculate shellwise orientational correlation function and tetrahedral order parameter to understand the local dynamics and structural re-arrangement of water. Theoretical analysis providing simple method for calculation of shellwise local dielectric constant and implication of these findings are elaborately discussed in the present work. (C) 2014 AIP Publishing LLC.

Temperature dependent current-voltage characteristics of zinc oxide nanowire/polypyrrole nanocomposite

Temperature dependent current-voltage (I-V) measurements of electrochemically prepared zinc oxide nanowire/polypyrrole (ZnONW/PPy) nanocomposite yielded non-linear I-V characteristics at temperatures between 300 and 4.5 K. The low-field conductance (G) of the ZnONW/PPy film exhibits pronounced temperature dependence with room temperature conductance (G(300K)) similar to 10(-3) S and a conductance ratio (G(300)K/G(4.5K)) of similar to 10(4), indicating dominance of significant temperature dependent charge transport processes. The conduction mechanism of the film is satisfactorily understood by extended fluctuation induced tunneling (FIT) model as the non-linear I-V characteristics fit fairly well to the extended FIT model. Further, the temperature dependence of G(o) obtained from fitting followed Sheng's model also. (C) 2014 AIP Publishing LLC.

Sources of major ions and processes affecting the geochemical and isotopic signatures of subsurface waters along a tropical river, Southwestern India

Systematic monitoring of subsurface hydrogeochemistry has been carried out for a period of one year in a humid tropical region along the Nethravati-Gurupur River. The major ion and stable isotope (delta O-18 and delta H-2) compositions are used to understand the hydrogeochemistry of groundwater and its interaction with surface water. In the study, it is observed that intense weathering of source rocks is the major source of chemical elements to the surface and subsurface waters. In addition, agricultural activities and atmospheric contributions also control the major ion chemistry of water in the study area. There is a clear seasonality in the groundwater chemistry, which is related to the recharge and discharge of the hydrological system. On a temporal scale, there is a decrease in major cation concentrations during the monsoon which is a result of dilution of sources from the weathering of rock minerals, and an increase in anion concentrations which is contributed by the atmosphere, accompanied by an increase in water level during the monsoon. The stable isotope composition indicates that groundwater in the basin is of meteoric origin and recharged directly from the local precipitation during the monsoonal season. Soon after the monsoon, groundwater and surface water mix in the subsurface region. The groundwater feeds the surface water during the lean river flow season.