Halogen bonding in fluorine: experimental charge density study on intermolecular F center dot center dot center dot F and F center dot center dot center dot S donor-acceptor contacts

The enigmatic type II C-F center dot center dot center dot F-C and C-F center dot center dot center dot S-C interactions in pentafluorophenyl 2,2'-bithiazole are shown to be realistic ``r-hole'' interactions based on high resolution X-ray charge density analysis.

A Hybrid Parallel Algorithm for Computing and Tracking Level Set Topology

The contour tree is a topological abstraction of a scalar field that captures evolution in level set connectivity. It is an effective representation for visual exploration and analysis of scientific data. We describe a work-efficient, output sensitive, and scalable parallel algorithm for computing the contour tree of a scalar field defined on a domain that is represented using either an unstructured mesh or a structured grid. A hybrid implementation of the algorithm using the GPU and multi-core CPU can compute the contour tree of an input containing 16 million vertices in less than ten seconds with a speedup factor of upto 13. Experiments based on an implementation in a multi-core CPU environment show near-linear speedup for large data sets.

CMOS-Compatible and Scalable Deposition of Nanocrystalline Zinc Ferrite Thin Film to Improve Inductance Density of Integrated RF Inductor

Development towards the combination of miniaturization and improved functionality of RFIC has been stalled due to the lack of high-performance integrated inductors. To meet this challenge, integration of magnetic material with high permeability as well as low conductivity is a must. Ferrite films are excellent candidates for RF devices due to their low cost, high resistivity, and low eddy current losses. Unlike its bulk counterpart, nanocrystalline zinc ferrite, because of partial inversion in the spinel structure, exhibits novel magnetic properties suitable for RF applications. However, most scalable ferrite film deposition processes require either high temperature or expensive equipment or both. We report a novel low temperature (< 200 degrees C) solution-based deposition process for obtaining high quality, polycrystalline zinc ferrite thin films (ZFTF) on Si (100) and on CMOS-foundry-fabricated spiral inductor structures, rapidly, using safe solvents and precursors. An enhancement of up to 20% at 5 GHz in the inductance of a fabricated device was achieved due to the deposited ZFTF. Substantial inductance enhancement requires sufficiently thick films and our reported process is capable of depositing smooth, uniform films as thick as similar to 20 mu m just by altering the solution composition. The method is capable of depositing film conformally on a surface with complex geometry. As it requires neither a vacuum system nor any post-deposition processing, the method reported here has a low thermal budget, making it compatible with modern CMOS process flow.

Gap renormalization of molecular crystals from density-functional theory

Fundamental gap renormalization due to electronic polarization is a basic phenomenon in molecular crystals. Despite its ubiquity and importance, all conventional approaches within density-functional theory completely fail to capture it, even qualitatively. Here, we present a new screened range-separated hybrid functional, which, through judicious introduction of the scalar dielectric constant, quantitatively captures polarization-induced gap renormalization, as demonstrated on the prototypical organic molecular crystals of benzene, pentacene, and C-60. This functional is predictive, as it contains system-specific adjustable parameters that are determined from first principles, rather than from empirical considerations.

The effect of cell size and channel density on neuronal information encoding and energy efficiency

Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na+ and K+ channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.

Scalar transport in diffusion flame wrapped up by an air and fuel side vortex

The present work involves a computational study of soot (chosen as a scalar which is a primary pollutant source) formation and transport in a laminar acetylene diffusion flame perturbed by a convecting line vortex. The topology of soot contours resulting from flame vortex interactions has been investigated. More soot was produced when vortex was introduced from the air side in comparison to the fuel side. Also, the soot topography was spatially more diffuse in the case of air side vortex. The computational model was found to be in good agreement with the experimental work previously reported in the literature. The computational simulation enabled a study of various parameters like temperature, equivalence ratio and temperature gradient affecting the soot production and transport. Temperatures were found to be higher in the case of air side vortex in contrast to the fuel side one. In case of fuel side vortex, abundance of fuel in the vortex core resulted in fuel-rich combustion zone in the core and a more discrete soot topography. Besides, the overall soot production was observed to be low in the fuel side vortex. However, for the air side vortex, air abundance in the core resulted in higher temperatures and greater soot production. Probability density functions (PDFs) have been introduced to investigate the spatiotemporal variation of soot yield and transport and their dependence on temperature and acetylene concentration from statistical view point. In addition, the effect of flame curvature on soot production is also studied. The regions convex to fuel stream side witnessed thicker soot layer. All numerical simulations have been carried out on Fluent 6.3.26. (C) 2013 Elsevier Ltd. All rights reserved.

Sufficient conditions for formation of a network topology by self-interested agents

Networks such as organizational network of a global company play an important role in a variety of knowledge management and information diffusion tasks. The nodes in these networks correspond to individuals who are self-interested. The topology of these networks often plays a crucial role in deciding the ease and speed with which certain tasks can be accomplished using these networks. Consequently, growing a stable network having a certain topology is of interest. Motivated by this, we study the following important problem: given a certain desired network topology, under what conditions would best response (link addition/deletion) strategies played by self-interested agents lead to formation of a pairwise stable network with only that topology. We study this interesting reverse engineering problem by proposing a natural model of recursive network formation. In this model, nodes enter the network sequentially and the utility of a node captures principal determinants of network formation, namely (1) benefits from immediate neighbors, (2) costs of maintaining links with immediate neighbors, (3) benefits from indirect neighbors, (4) bridging benefits, and (5) network entry fee. Based on this model, we analyze relevant network topologies such as star graph, complete graph, bipartite Turan graph, and multiple stars with interconnected centers, and derive a set of sufficient conditions under which these topologies emerge as pairwise stable networks. We also study the social welfare properties of the above topologies.

Energy Hyperspace for Stacking Interaction in AU/AU Dinucleotide Step: Dispersion-Corrected Density Functional Theory Study

Double helical structures of DNA and RNA are mostly determined by base pair stacking interactions, which give them the base sequence-directed features, such as small roll values for the purine-pyrimidine steps. Earlier attempts to characterize stacking interactions were mostly restricted to calculations on fiber diffraction geometries or optimized structure using ab initio calculations lacking variation in geometry to comment on rather unusual large roll values observed in AU/AU base pair step in crystal structures of RNA double helices. We have generated stacking energy hyperspace by modeling geometries with variations along the important degrees of freedom, roll, and slide, which were chosen via statistical analysis as maximally sequence dependent. Corresponding energy contours were constructed by several quantum chemical methods including dispersion corrections. This analysis established the most suitable methods for stacked base pair systems despite the limitation imparted by number of atom in a base pair step to employ very high level of theory. All the methods predict negative roll value and near-zero slide to be most favorable for the purine-pyrimidine steps, in agreement with Calladine's steric clash based rule. Successive base pairs in RNA are always linked by sugar-phosphate backbone with C3-endo sugars and this demands C1-C1 distance of about 5.4 angstrom along the chains. Consideration of an energy penalty term for deviation of C1-C1 distance from the mean value, to the recent DFT-D functionals, specifically B97X-D appears to predict reliable energy contour for AU/AU step. Such distance-based penalty improves energy contours for the other purine-pyrimidine sequences also. (c) 2013 Wiley Periodicals, Inc. Biopolymers 101: 107-120, 2014.

Experimental evidence for `carbon bonding' in the solid state from charge density analysis

The validity of the newly proposed `carbon bonding', an interaction where a carbon atom acts as an electrophilic site towards a variety of nucleophiles, has been investigated in the solid state. X-ray charge density analysis provides experimental evidence for this hitherto unexplored interaction and unravels its nature and strength.

Effect of analyte concentration on the laser-induced plasma temperature and electron density in liquid matrix

In the present work, we report spectroscopic studies of laser-induced plasmas produced by focusing the second harmonic (532nm) of a Nd:YAG laser onto the laminar flow of a liquid containing chromium. The plasma temperature is determined from the coupled Saha-Boltzmann plot and the electron density is evaluated from the Stark broadening of an ionic line of chromium Cr(II)] at 267.7nm. Our results reveal a decrease in plasma temperature with an increase in Cr concentration up to a certain concentration level; after that, it becomes approximately constant, while the electron density increases with an increase in analyte (Cr) concentration in liquid matrix.

A Reduced Device-Count Hybrid Multilevel Inverter Topology with single DC Source and Improved Fault Tolerance

A new hybrid multilevel power converter topology is presented in this paper. The proposed power converter topology uses only one DC source and floating capacitors charged to asymmetrical voltage levels, are used for generating different voltage levels. The SVPWM based control strategy used in this converter maintains the capacitor voltages at the required levels in the entire modulation range including the over-modulation region. For the voltage levels: nine and above, the number of components required in the proposed topology is significantly lower, compared to the conventional multilevel inverter topologies. The number of capacitors required in this topology reduces drastically compared to the conventional flying capacitor topology, when the number of levels in the inverter output increases. This topology has better fault tolerance, as it is capable of operating with reduced number of levels, in the entire modulation range, in the event of any failure in the H-bridges. The transient as well as the steady state performance of the nine-level version of the proposed topology is experimentally verified in the entire modulation range including the over-modulation region.

Effect of the Addition of B2O3 on the Density, Microstructure, Dielectric, Piezoelectric and Ferroelectric Properties of K0.5Na0.5NbO3 Ceramics

Boron oxide (B2O3) addition to pre-reacted K0.5Na0.5NbO3 (KNN) powders facilitated swift densification at relatively low sintering temperatures which was believed to be a key to minimize potassium and sodium loss. The base KNN powder was synthesized via solid-state reaction route. The different amounts (0.1-1 wt%) of B2O3 were-added, and ceramics were sintered at different temperatures and durations to optimize the amount of B2O3 needed to obtain KNN pellets with highest possible density and grain size. The 0.1 wt% B2O3-added KNN ceramics sintered at 1,100 A degrees C for 1 h exhibited higher density (97 %). Scanning electron microscopy studies confirmed an increase in average grain size with increasing B2O3 content at appropriate temperature of sintering and duration. The B2O3-added KNN ceramics exhibited improved dielectric and piezoelectric properties at room temperature. For instance, 0.1 wt% B2O3-added KNN ceramic exhibited d (33) value of 116 pC/N which is much higher than that of pure KNN ceramics. Interestingly, all the B2O3-added (0.1-1 wt%) KNN ceramics exhibited polarization-electric field (P vs. E) hysteresis loops at room temperature. The remnant polarization (P (r)) and coercive field (E (c)) values are dependent on the B2O3 content and crystallite size.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix.

Topological analysis of electron density and the electrostatic properties of isoniazid: an experimental and theoretical study

Isoniazid (isonicotinohydrazide) is an important first-line antitubercular drug that targets the InhA enzyme which synthesizes the critical component of the mycobacterial cell wall. An experimental charge-density analysis of isoniazid has been performed to understand its structural and electronic properties in the solid state. A high-resolution single-crystal X-ray intensity data has been collected at 90 K. An aspherical multipole refinement was carried out to explore the topological and electrostatic properties of the isoniazid molecule. The experimental results were compared with the theoretical charge-density calculations performed using CRYSTAL09 with the B3LYP/6-31G** method. A topological analysis of the electron density reveals that the Laplacian of electron density of the N-N bond is significantly less negative, which indicates that the charges at the b.c.p. (bond-critical point) of the bond are least accumulated, and so the bond is considered to be weak. As expected, a strong negative electrostatic potential region is present in the vicinity of the O1, N1 and N3 atoms, which are the reactive locations of the molecule. The C-H center dot center dot center dot N, C-H center dot center dot center dot O and N-H center dot center dot center dot N types of intermolecular hydrogen-bonding interactions stabilize the crystal structure. The topological analysis of the electron density on hydrogen bonding shows the strength of intermolecular interactions.