Thermal correlation functions of twisted quantum fields

We derive the thermal correlators for twisted quantum fields on noncommutative spacetime. We show that the thermal expectation value of the number operator is same as in commutative spacetime, but that higher correlators are sensitive to the noncommutativity parameters phi(mu nu).

On the paradoxical relation between the melting temperature and forbidden energy gap of nanoparticles

We comment on the paradox that seems to exist about a correlation between the size-dependent melting temperature and the forbidden energy gap of nanoparticles. By analyzing the reported expressions for the melting temperature and the band gap of nanoparticles, we conclude that there exists a relation between these two physical quantities. However, the variations of these two quantities with size for semiconductors are different from that of metals. (C) 2010 American Institute of Physics.[doi:10.1063/1.3466920].

First-principles analysis of electron correlation, spin ordering and phonons in the normal state of FeSe1-x

We present first-principles density-functional-theory-based calculations to determine the effects of the strength of on-site electron correlation, magnetic ordering, pressure and Se vacancies on phonon frequencies and electronic structure of FeSe1-x. The theoretical equilibrium structure (lattice parameters) of FeSe depends sensitively on the value of the Hubbard parameter U of on-site correlation and magnetic ordering. Our results suggest that there is a competition between different antiferromagnetic states due to comparable magnetic exchange couplings between first- and second-neighbor Fe sites. As a result, a short range order of stripe antiferromagnetic type is shown to be relevant to the normal state of FeSe at low temperature. We show that there is a strong spin-phonon coupling in FeSe (comparable to its superconducting transition temperature) as reflected in large changes in the frequencies of certain phonons with different magnetic ordering, which is used to explain the observed hardening of a Raman-active phonon at temperatures (similar to 100 K) where magnetic ordering sets in. The symmetry of the stripe antiferromagnetic phase permits an induced stress with orthorhombic symmetry, leading to orthorhombic strain as a secondary order parameter at the temperature of magnetic ordering. The presence of Se vacancies in FeSe gives rise to a large peak in the density of states near the Fermi energy, which could enhance the superconducting transition temperature within the BCS-like picture.

Fracture Properties of Concrete-Concrete Interfaces Using Digital Image Correlation

The mode I and mode II fracture toughness and the critical strain energy release rate for different concrete-concrete jointed interfaces are experimentally determined using the Digital Image Correlation technique. Concrete beams having different compressive strength materials on either side of a centrally placed vertical interface are prepared and tested under three-point bending in a closed loop servo-controlled testing machine under crack mouth opening displacement control. Digital images are captured before loading (undeformed state) and at different instances of loading. These images are analyzed using correlation techniques to compute the surface displacements, strain components, crack opening and sliding displacements, load-point displacement, crack length and crack tip location. It is seen that the CMOD and vertical load-point displacement computed using DIC analysis matches well with those measured experimentally.

Solvation dynamics, energy distribution and trapping of a light solute ion

In the theoretical treatments of the dynamics of solvation of a newly created ion in a dipolar solvent, the self-motion of the solute is usually ignored. Recently, it has been shown that for a light ion the translational motion of the ion can significantly enhance its own rate of solvation. Therefore, solvation itself may not be the rate determining step in the equilibration. Instead, the rate determining step is the search of the low energy configuration which serves to localize the light ion. In this article a microscopic calculation of the probability distribution of the interaction energy of the nascent charge with the dipolar solvent molecules is presented in order to address this problem of solute trapping. It is found that to a good approximation, this distribution is Gaussian and the second moment of this distribution is exactly equal to the half of its own solvation energy. It is shown that this is in excellent agreement with the simulation results that are available for the model Brownian dipolar lattice and for liquid acetonitrile. If the distortion of the solvent by the ion is negligible then the same relation gives the energy distribution for the solvated ion, with the average centered at the final equilibrium solvation energy. These results are expected to be useful in understanding various chemical processes in dipolar liquids. Another interesting outcome of the present study is a simple dynamic argument that supports Onsager's ''inverse snow-ball'' conjecture of solvation of a light ion. A simple derivation of the semi-phenomenological relation between the solvation time correlation function and the single particle orientation, reported recently by Maroncelli et al. (J. Phys. Chem. 97 (1993) 13), is also presented.

Smart applications for energy harvested WSNs

A Wireless Sensor Network (WSN) powered using harvested energies is limited in its operation by instantaneous power. Since energy availability can be different across nodes in the network, network setup and collaboration is a non trivial task. At the same time, in the event of excess energy, exciting node collaboration possibilities exist; often not feasible with battery driven sensor networks. Operations such as sensing, computation, storage and communication are required to achieve the common goal for any sensor network. In this paper, we design and implement a smart application that uses a Decision Engine, and morphs itself into an energy matched application. The results are based on measurements using IRIS motes running on solar energy. We have done away with batteries; instead used low leakage super capacitors to store harvested energy. The Decision Engine utilizes two pieces of data to provide its recommendations. Firstly, a history based energy prediction model assists the engine with information about in-coming energy. The second input is the energy cost database for operations. The energy driven Decision Engine calculates the energy budgets and recommends the best possible set of operations. Under excess energy condition, the Decision Engine, promiscuously sniffs the neighborhood looking for all possible data from neighbors. This data includes neighbor's energy level and sensor data. Equipped with this data, nodes establish detailed data correlation and thus enhance collaboration such as filling up data gaps on behalf of nodes hibernating under low energy conditions. The results are encouraging. Node and network life time of the sensor nodes running the smart application is found to be significantly higher compared to the base application.

DNA Free Energy-Based Promoter Prediction and Comparative Analysis of Arabidopsis and Rice Genomes

The cis-regulatory regions on DNA serve as binding sites for proteins such as transcription factors and RNA polymerase. The combinatorial interaction of these proteins plays a crucial role in transcription initiation, which is an important point of control in the regulation of gene expression. We present here an analysis of the performance of an in silico method for predicting cis-regulatory regions in the plant genomes of Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) on the basis of free energy of DNA melting. For protein-coding genes, we achieve recall and precision of 96% and 42% for Arabidopsis and 97% and 31% for rice, respectively. For noncoding RNA genes, the program gives recall and precision of 94% and 75% for Arabidopsis and 95% and 90% for rice, respectively. Moreover, 96% of the false-positive predictions were located in noncoding regions of primary transcripts, out of which 20% were found in the first intron alone, indicating possible regulatory roles. The predictions for orthologous genes from the two genomes showed a good correlation with respect to prediction scores and promoter organization. Comparison of our results with an existing program for promoter prediction in plant genomes indicates that our method shows improved prediction capability.

Estimation of surface free energy of pyrites by contact angle measurements

The surface properties of coal-pyrite play a major role in determining its separation from coal in processes such as flotation. The solution pH is an important parameter in determining the surface properties of both coal and coal-pyrite such as surface free energy and zeta-potential. In the present investigation, the effect of pH on the surface free energy of pyrites from different sources was studied. The surface free energy of solids is made up of two components, i.e. the dispersive surface free energy and the acid-base interaction energy. Various methods have been used by previous researchers to evaluate these two components for different solids. In the present study, a new approach was developed and used to study the surface free energy of pyrite surfaces. Results indicate that the dispersion surface free energy of various pyrites is independent of pH while the acid-base interaction energy is strongly dependent on the pH. The acid-base interaction energy is different for each pyrite sample and also the change with pH varies with the type of pyrite. Coal-pyrite was found to be more hydrophobic than ore-pyrite which may be attributed to the presence of carbon in coal-pyrites. The acid-base interaction energy varied little with pH for coal pyrites than ore-pyrite. Comparison of acid-base interaction energy with zeta-potential measurements shows a good correlation between the minimum in acid-base interaction energy and the pHpzc.

Universality of scaling laws in correlation between velocity and shear stress in turbulent boundary layers

In this study, we analyse simultaneous measurements (at 50 Hz) of velocity at several heights and shear stress at the surface made during the Utah field campaign for the presence of ranges of scales, where distinct scale-to-scale interactions between velocity and shear stress can be identified. We find that our results are similar to those obtained in a previous study [Venugopal et al., 2003] (contrary to the claim in V2003, that the scaling relations might be dependent on Reynolds number) where wind tunnel measurements of velocity and shear stress were analysed. We use a wavelet-based scale-to-scale cross-correlation to detect three ranges of scales of interaction between velocity and shear stress, namely, (a) inertial subrange, where the correlation is negligible; (b) energy production range, where the correlation follows a logarithmic law; and (c) for scales larger than the boundary layer height, the correlation reaches a plateau.

Strong electron correlation of Re 5d electrons in Ca2FeReO6

We have investigated the electronic structure of a double perovskite Ca2FeReO6 using photoemission spectroscopy and LDA+U bandstructure calculations. Small spectral weight at the Fermi level observed above the metal–insulator transition temperature, gradually disappears with decreasing T, forming a small (≤50 meV) energy gap. To reproduce this small energy gap, we require a very large effective U (Ueff) for Re (4 eV) in addition to Ueff of 4 eV for Fe. From simple calculations in terms of the ionic radii, we demonstrate that the Fe–Re bandwidth is smaller than that of Fe–Mo in Ca2FeMoO6, which should yield a strong electron correlation in the Re 5d bands.

Review of correlations between SPT N and shear modulus: A new correlation applicable to any region

A low strain shear modulus plays a fundamental role in earthquake geotechnical engineering to estimate the ground response parameters for seismic microzonation. A large number of site response studies are being carried out using the standard penetration test (SPT) data, considering the existing correlation between SPT N values and shear modulus. The purpose of this paper is to review the available empirical correlations between shear modulus and SPT N values and to generate a new correlation by combining the new data obtained by the author and the old available data. The review shows that only few authors have used measured density and shear wave velocity to estimate shear modulus, which were related to the SPT N values. Others have assumed a constant density for all the shear wave velocities to estimate the shear modulus. Many authors used the SPT N values of less than 1 and more than 100 to generate the correlation by extrapolation or assumption, but practically these N values have limited applications, as measuring of the SPT N values of less than 1 is not possible and more than 100 is not carried out. Most of the existing correlations were developed based on the studies carried out in Japan, where N values are measured with a hammer energy of 78%, which may not be directly applicable for other regions because of the variation in SPT hammer energy. A new correlation has been generated using the measured values in Japan and in India by eliminating the assumed and extrapolated data. This correlation has higher regression coefficient and lower standard error. Finally modification factors are suggested for other regions, where the hammer energy is different from 78%. Crown Copyright (C) 2012 Published by Elsevier Ltd. All rights reserved.

Experimental analysis of composite single-lap joints using digital image correlation and comparison with theoretical models

The demand for energy efficient, low weight structures has boosted the use of composite structures assembled using increased quantities of structural adhesives. Bonded structures may be subjected to severe working environments such as high temperature and moisture due to which the adhesive gets degraded over a period of time. This reduces the strength of a joint and leads to premature failure. Measurement of strains in the adhesive bondline at any point of time during service may be beneficial as an assessment can be made on the integrity of a joint and necessary preventive actions may be taken before failure. This paper presents an experimental approach of measuring peel and shear strains in the adhesive bondline of composite single-lap joints using digital image correlation. Different sets of composite adhesive joints with varied bond quality were prepared and subjected to tensile load during which digital images were taken and processed using digital image correlation software. The measured peel strain at the joint edge showed a rapid increase with the initiation of a crack till failure of the joint. The measured strains were used to compute the corresponding stresses assuming a plane strain condition and the results were compared with stresses predicted using theoretical models, namely linear and nonlinear adhesive beam models. A similar trend in stress distribution was observed. Further comparison of peel and shear strains also exhibited similar trend for both healthy and degraded joints. Maximum peel stress failure criterion was used to predict the failure load of a composite adhesive joint and a comparison was made between predicted and actual failure loads. The predicted failure loads from theoretical models were found to be higher than the actual failure load for all the joints.

Correlation between thermodynamic anomalies and pathways of ice nucleation in supercooled water

The well-known classical nucleation theory (CNT) for the free energy barrier towards formation of a nucleus of critical size of the new stable phase within the parent metastable phase fails to take into account the influence of other metastable phases having density/order intermediate between the parent metastable phase and the final stable phase. This lacuna can be more serious than capillary approximation or spherical shape assumption made in CNT. This issue is particularly significant in ice nucleation because liquid water shows rich phase diagram consisting of two (high and low density) liquid phases in supercooled state. The explanations of thermodynamic and dynamic anomalies of supercooled water often invoke the possible influence of a liquid-liquid transition between two metastable liquid phases. To investigate both the role of thermodynamic anomalies and presence of distinct metastable liquid phases in supercooled water on ice nucleation, we employ density functional theoretical approach to find nucleation free energy barrier in different regions of phase diagram. The theory makes a number of striking predictions, such as a dramatic lowering of nucleation barrier due to presence of a metastable intermediate phase and crossover in the dependence of free energy barrier on temperature near liquid-liquid critical point. These predictions can be tested by computer simulations as well as by controlled experiments. (C) 2014 AIP Publishing LLC.

Solubility-Hardness Correlation in Molecular Crystals: Curcumin and Sulfathiazole Polymorphs

Curcumin and sulfathiazole exist as three and five polymorphs, respectively. We correlate solubility and mechanical properties in these polymorphic systems. It is seen that hardness (H) is inversely proportional to the solubility of a polymorph. H of the polymorphs is explained on the basis of slip planes in the crystal structure, the Schmid factor (m), and the relative orientation of molecules with respect to the nanoindenter direction. Effectively, H is a useful parameter (compared to melting point, T-m, and density, rho) that correlates well with the solubility of a polymorph. Such a correlation is helpful in systems like curcumin and sulfathiazole in which the Gibbs free energy of the polymorphs are close to one another. To summarize, a softer polymorph is more soluble.

Diffusion on a rugged energy landscape with spatial correlations

Rugged energy landscapes find wide applications in diverse fields ranging from astrophysics to protein folding. We study the dependence of diffusion coefficient (D) of a Brownian particle on the distribution width (epsilon) of randomness in a Gaussian random landscape by simulations and theoretical analysis. We first show that the elegant expression of Zwanzig Proc. Natl. Acad. Sci. U.S.A. 85, 2029 (1988)] for D(epsilon) can be reproduced exactly by using the Rosenfeld diffusion-entropy scaling relation. Our simulations show that Zwanzig's expression overestimates D in an uncorrelated Gaussian random lattice - differing by almost an order of magnitude at moderately high ruggedness. The disparity originates from the presence of ``three-site traps'' (TST) on the landscape - which are formed by the presence of deep minima flanked by high barriers on either side. Using mean first passage time formalism, we derive a general expression for the effective diffusion coefficient in the presence of TST, that quantitatively reproduces the simulation results and which reduces to Zwanzig's form only in the limit of infinite spatial correlation. We construct a continuous Gaussian field with inherent correlation to establish the effect of spatial correlation on random walk. The presence of TSTs at large ruggedness (epsilon >> k(B)T) gives rise to an apparent breakdown of ergodicity of the type often encountered in glassy liquids. (C) 2014 AIP Publishing LLC.