Direct correlation between non-random distribution of cations and ion transport mechanism in soda-lime silicate glasses

We report a direct correlation between dissimilar ion pair formation and alkali ion transport in soda-lime silicate glasses established via broad band conductivity spectroscopy and local structural probe techniques. The combined Raman and Nuclear Magnetic Resonance (NMR) spectroscopy techniques on these glasses reveal the coexistence of different anionic species and the prevalence of Na+-Ca2+ dissimilar pairs as well as their distributions. The spectroscopic results further confirm the formation of dissimilar pairs atomistically, where it increases with increasing alkaline-earth oxide content These results, are the manifestation of local structural changes in the silicate network with composition which give rise to different environments into which the alkali ions hop. The Na+ ion mobility varies inversely with dissimilar pair formation, i.e. it decreases with increase of non-random formation of dissimilar pairs. Remarkably, we found that increased degree of non-randomness leads to temperature dependent variation in number density of sodium ions. Furthermore, the present study provides the strong link between the dynamics of the alkali ions and different sites associated with it in soda-lime silicate glasses. (C) 2014 Elsevier B.V. All rights reserved.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Two techniques to improve the precision of a demand-driven null-dereference verification approach

The problem addressed in this paper is sound, scalable, demand-driven null-dereference verification for Java programs. Our approach consists conceptually of a base analysis, plus two major extensions for enhanced precision. The base analysis is a dataflow analysis wherein we propagate formulas in the backward direction from a given dereference, and compute a necessary condition at the entry of the program for the dereference to be potentially unsafe. The extensions are motivated by the presence of certain ``difficult'' constructs in real programs, e.g., virtual calls with too many candidate targets, and library method calls, which happen to need excessive analysis time to be analyzed fully. The base analysis is hence configured to skip such a difficult construct when it is encountered by dropping all information that has been tracked so far that could potentially be affected by the construct. Our extensions are essentially more precise ways to account for the effect of these constructs on information that is being tracked, without requiring full analysis of these constructs. The first extension is a novel scheme to transmit formulas along certain kinds of def-use edges, while the second extension is based on using manually constructed backward-direction summary functions of library methods. We have implemented our approach, and applied it on a set of real-life benchmarks. The base analysis is on average able to declare about 84% of dereferences in each benchmark as safe, while the two extensions push this number up to 91%. (C) 2014 Elsevier B.V. All rights reserved.

Solvatochromism of 9,10-phenanthrenequinone: An electronic and resonance Raman spectroscopic study

Solvent effects play a vital role in various chemical, physical, and biological processes. To gain a fundamental understanding of the solute-solvent interactions and their implications on the energy level re-ordering and structure, UV-VIS absorption, resonance Raman spectroscopic, and density functional theory calculation studies on 9,10-phenanthrenequinone (PQ) in different solvents of diverse solvent polarity has been carried out. The solvatochromic analysis of the absorption spectra of PQ in protic dipolar solvents suggests that the longest (1n-pi(1)*; S-1 state) and the shorter (1 pi-pi(1)*; S-2 state) wavelength band undergoes a hypsochromic and bathochromic shift due to intermolecular hydrogen bond weakening and strengthening, respectively. It also indicates that hydrogen bonding plays a major role in the differential solvation of the S-2 state relative to the ground state. Raman excitation profiles of PQ (400-1800 cm(-1)) in various solvents followed their corresponding absorption spectra therefore the enhancements on resonant excitation are from single-state rather than mixed states. The hyperchromism of the longer wavelength band is attributed to intensity borrowing from the nearby allowed electronic transition through vibronic coupling. Computational calculation with C-2 nu symmetry constraint on the S-2 state resulted in an imaginary frequency along the low-frequency out-of-plane torsional modes involving the C=O site and therefore, we hypothesize that this mode could be involved in the vibronic coupling. (C) 2015 AIP Publishing LLC.

Synthesis, crystal structure and spectroscopic and electrochemical properties of bridged trisbenzoato copper-zinc heterobinuclear complex of 2,2 `-bipyridine

The synthesis of the heterobinuclear copper-zinc complex CuZn(bz)(3)(bpy)(2)]ClO4 (bz = benzoate) from benzoic acid and bipyridine is described. Single crystal X-ray diffraction studies of the heterobinuclear complex reveals the geometry of the benzoato bridged Cu(II)-Zn(II) centre. The copper or zinc atom is pentacoordinate, with two oxygen atoms from bridging benzoato groups and two nitrogen atoms from one bipyridine forming an approximate plane and a bridging oxygen atom from a monodentate benzoate group. The Cu-Zn distance is 3.345 angstrom. The complex is normal paramagnetic having mu(eff) value equal to 1.75 BM, ruling out the possibility of Cu-Cu interaction in the structural unit. The ESR spectrum of the complex in CH3CN at RT exhibit an isotropic four line spectrum centred at g = 2.142 and hyperfine coupling constants A(av) = 63 x 10(-4) cm(-1), characteristic of a mononuclear square-pyramidal copper(II) complexes. At LNT, the complex shows an isotropic spectrum with g(parallel to) = 2.254 and g(perpendicular to) =2.071 and A(parallel to) = 160 x 10(-4) cm(-1). The Hamiltonian parameters are characteristic of distorted square pyramidal geometry. Cyclic voltammetric studies of the complex have indicated quasi-reversible behaviour in acetonitrile solution. (C) 2014 Elsevier B.V. All rights reserved.

Raman Spectroscopic Studies on Screening of Myopathies

Myopathies are among the major causes of mortality in the world. There is no complete cure for this heterogeneous group of diseases, but a sensitive, specific, and fast diagnostic tool may improve therapy effectiveness. In this study, Raman spectroscopy is applied to discriminate between muscle mutants in Drosophila on the basis of associated changes at the molecular level. Raman spectra were collected from indirect flight muscles of mutants, upheld1 (up1), heldup(2) (hdp(2)), myosin heavy chain7 (Mhc7), actin88F(KM88) (Act88F(KM88)), upheld101 (up101), and Canton-S (CS) control group, for both 2 and 12 days old flies. Difference spectra (mutant minus control) of all the mutants showed an increase in nucleic acid and beta-sheet and/or random coil protein content along with a decrease in a-helix protein. Interestingly, the 12th day samples of up1 and Act88F(KM88) showed significantly higher levels of glycogen and carotenoids than CS. A principal components based linear discriminant analysis classification model was developed based on multidimensional Raman spectra, which classified the mutants according to their pathophysiology and yielded an overall accuracy of 97% and 93% for 2 and 12 days old flies, respectively. The up1 and Act88F(KM88) (nemaline-myopathy) mutants form a group that is clearly separated in a linear discriminant plane from up101 and hdp2 (cardiomyopathy) mutants. Notably, Raman spectra from a human sample with nemaline-myopathy formed a cluster with the corresponding Drosophila mutant (up1). In conclusion, this is the first demonstration in which myopathies, despite their heterogeneity, were screened on the basis of biochemical differences using Raman spectroscopy.

Water Dispersible, Positively and Negatively Charged MoS2 Nanosheets: Surface Chemistry and the Role of Surfactant Binding

Stable aqueous dispersions of atomically thin layered MoS2 nanosheets have been obtained by sonication in the presence of ionic surfactants. The dispersions are stabilized by electrostatic repulsion between the sheets, and we show that the sign of the charge on the MoS2 nanosheets, either positive or negative, can be can be controlled by the choice of the surfactant. Using techniques from solution NMR, we show that the surfactant chains are weakly bound to the MoS2 sheets and undergo rapid exchange with free surfactant chains present in the dispersion. In situ nuclear Overhauser effect spectroscopic measurements provide direct evidence that the surfactant chains lie flat, arranged randomly on the basal plane of the MoS2 nanosheets with their charged headgroup exposed. These results provide a chemical perspective for understanding the stability of these inorganic nanosheets in aqueous dispersions and the origin of the charge on the sheets.

A unique strategy towards high dielectric constant and low loss with multiwall carbon nanotubes anchored onto graphene oxide sheets

Multiwall carbon nanotubes (MWNTs) were anchored onto graphene oxide sheets (GOs) via diazonium and C-C coupling reactions and characterized by spectroscopic and electron microscopic techniques. The thus synthesized MWNT-GO hybrid was then melt mixed with 50/50 polyamide6-maleic anhydride-modified acrylonitrile-butadiene-styrene (PA6-mABS) blend to design materials with high dielectric constant (30) and low dielectric loss. The phase morphology was studied by SEM and it was observed that the MWNT-GO hybrid was selectively localized in the PA6 phase of the blend. The 30 scales with the concentration of MWNT-GO in the blends, which interestingly showed a very low dielectric loss (< 0.2) making them potential candidate for capacitors. In addition, the dynamic storage modulus scales with the fraction of MWNT-GO in the blends, demonstrating their reinforcing capability as well.

Electrochemical exfoliation of graphite to produce graphene using tetrasodium pyrophosphate

An electrochemical exfoliation based synthetic methodology to produce graphene is provided. An eco-friendly and non-toxic tetrasodium pyrophosphate solution in which the pyrophosphate anion acts as an intercalating ion was used as the electroactive media. Five different ion intercalation potentials were used. Characterization by microscopy, X-ray diffraction, Raman spectroscopy and UV-Visible spectroscopic techniques confirmed that all the potentials produced nano to micrometer sized graphene sheets. No trace of graphene oxide was detected. It was observed that (i) an increase in the intercalation potential increased the graphene yield and (ii) the defect density of graphene did not change significantly with a change in the intercalation potential.

Electrochemical behavior of Zn-graphene composite coatings

A Zn-graphene composite coating was electrodeposited on mild steel. The graphene was synthesized by electrochemical exfoliation of graphite. Electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction techniques were used to characterize the coatings. Compared to a pure Zn coating, the Zn-graphene coating exhibited reduced grain size, reduced surface defects, hillock structures over the coating surface and an altered texture. The corrosion behavior of the coatings was examined by Tafel polarization and electrochemical impedance spectroscopic methods. A significant improvement in the corrosion resistance in terms of reduction in corrosion current and corrosion rate and increase in polarization resistance was noted in the case of the Zn coating containing graphene.

Postsynthetic Exterior Decoration of an Organic Cage by Copper(I)-Catalysed A(3)-Coupling and Detection of Nitroaromatics

A new synthetic protocol based on one-pot, copper(I)-catalysed multicomponent reaction of formaldehyde, secondary amine and terminal alkyne has been employed to postsynthetically modify a self-assembled nanoscopic organic cage. By employing this synthetic strategy, three new cages appended with phenyl-, xylyl-and naphthyl-acetylene moieties have been synthesised. The resulting modified cages were characterised by using a range of spectroscopic techniques. The synthesised cages were fluorescent and thus one of them was tested to explore the potential use of such compounds as chemosensors for the detection of nitroaromatics. Experimental findings suggest a high selective quenching of initial fluorescence intensity in the presence of nitroaromatic compounds. Furthermore, it has been observed that among the various nitroaromatics tested, nitrophenolic compounds have better quenching ability.

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Synthesis and characterization of monometallic rhenium(I) complexes and their application as selective sensors for copper(II) ions

Novel imine functionalized monometallic rhenium(I) polypyridine complexes (1-4) comprising two phenol moieties attached to 2,20-bipyridine ligands L1-L4 have been synthesized and characterized. These complexes exhibit selective and sensitive detection towards copper(II) ions and this is observed through changes in UV-visible absorption, luminescence and time-resolved spectroscopic techniques. An enormous enhancement is observed in emission intensity, quantum yield and luminescence lifetime with the addition of copper(II) ions, and this can be attributed to the restriction of C=N isomerization in the Re(I) complexes. The strong binding between copper(II) ions and these complexes reveals that the binding constant values are in the range of 1.1 x 10(3)-6.0 x 103 M-1. The absorption spectral behavior of the complexes is supported by DFT calculations.

Experimentally validated Raman Monte Carlo simulation for a cuboid object to obtain Raman spectroscopic signatures for hidden material

In conventional Raman spectroscopic measurements of liquids or surfaces the preferred geometry for detection of the Raman signal is the backscattering (or reflection) mode. For non-transparent layered materials, sub-surface Raman signals have been retrieved using spatially offset Raman spectroscopy (SORS), usually with light collection in the same plane as the point of excitation. However, as a result of multiple scattering in a turbid medium, Raman photons will be emitted in all directions. In this study, Monte Carlo simulations for a three-dimensional layered sample with finite geometry have been performed to confirm the detectability of Raman signals at all angles and at all sides of the object. We considered a non-transparent cuboid container (high density polyethylene) with explosive material (ammonium nitrate) inside. The simulation results were validated with experimental Raman intensities. Monte Carlo simulation results reveal that the ratio of sub-surface to surface signals improves at geometries other than backscattering. In addition, we demonstrate through simulations the effects of the absorption and scattering coefficients of the layers, and that of the diameter of the excitation beam. The advantage of collecting light from all possible 4 angles, over other collection modes, is that this technique is not geometry specific and molecular identification of layers underneath non-transparent surfaces can be obtained with minimal interference from the surface layer. To what extent all sides of the object will contribute to the total signal will depend on the absorption and scattering coefficients and the physical dimensions. Copyright (c) 2015 John Wiley & Sons, Ltd.