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.

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.

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.

Enhanced Gas Adsorption on Graphitic Substrates via Defects and Local Curvature: A Density Functional Theory Study

Using van-der-Waals-corrected density functional theory calculations, we explore the possibility of engineering the local structure and morphology of high-surface-area graphene-derived materials to improve the uptake of methane and carbon dioxide for gas storage and sensing. We test the sensitivity of the gas adsorption energy to the introduction of native point defects, curvature, and the application of strain. The binding energy at topological point defect sites is inversely correlated with the number of missing carbon atoms, causing Stone-Wales defects to show the largest enhancement with respect to pristine graphene (similar to 20%). Improvements of similar magnitude are observed at concavely curved surfaces in buckled graphene sheets under compressive strain, whereas tensile strain tends to weaken gas binding. Trends for CO2 and CH4 are, similar, although CO2 binding is generally stronger by similar to 4 to 5 kJ mol(-1). However, the differential between the adsorption of CO2 and CH4 is much higher on folded graphene sheets and at concave curvatures; this could possibly be leveraged for CH4/CO2 flow separation and gasselective sensors.

Density Functional Theoretical Modeling, Electrostatic Surface Potential and Surface Enhanced Raman Spectroscopic Studies on Biosynthesized Silver Nanoparticles: Observation of 400 pM Sensitivity to Explosives

Interaction of adsorbate on charged surfaces, orientation of the analyte on the surface, and surface enhancement aspects have been studied. These aspects have been explored in details to explain the surface-enhanced Raman spectroscopic (SERS) spectra of 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (HNIW or CL-20), a well-known explosive, and 2,4,6-trinitrotoluene (TNT) using one-pot synthesis of silver nanoparticles via biosynthetic route using natural precursor extracts of clove and pepper. The biosynthesized silver nanoparticles (bio Ag Nps) have been characterized using UV-vis spectroscopy, scanning electron microscopy and atomic force microscopy. SERS studies conducted using bio Ag Nps on different water insoluble analytes, such as CL-20 and TNT, lead to SERS signals at concentration levels of 400 pM. The experimental findings have been corroborated with density functional computational results, electrostatic surface potential calculations, Fukui functions and potential measurements.

Effect of morphology on electrical treeing in low density polyethylene nanocomposites

Influence of polymer morphology on the inception and the growth of electrical trees in unfilled low density polyethylene (LDPE) as well as LDPE filled with 1, 3 and 5% by weight nanoalumina samples stressed with 50 Hz ac voltage has been studied. It is seen that there is a significant improvement in tree inception voltage with filler loading in LDPE filled with nanoparticles. Tree inception voltage increased with the filler loading up to 3% by weight nanoalumina loading and showed a reduction at 5% by weight loading. Change in tree growth patterns from branch to bush as well as a slower tree growth with increase in filler loading in LDPE alumina nanocomposites were observed. The degree of crystallinity and change in crystalline morphology induced by the presence of alumina nanoparticles in LDPE was studied using differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). DSC results show a similar melting behaviour for both unfilled LDPE and LDPE nanocomposites. However, there is a reduction in the degree of crystallinity for LDPE filled with 5% by weight nanoalumina. An increase in lamellae packing with increase in filler loadings and a highly disordered spherulitic structure for LDPE filled with 5% by weight nanoalumina was observed from the SEM images. The slow propagation of tree growth as well as reduction in tree inception voltage with increase in filler loadings were attributed to the morphological changes observed in the LDPE nanocomposites.

Exploring Cyclopentadienone Antiaromaticity: Charge Density Studies of Various Tetracyclones

A systematic study of six tetracyclones has been carried out using experimental and theoretical charge density analysis. A three pronged approach based on quantum theory of atoms in molecules (QTAIM), nucleus independent chemical shifts (NICS) criterion, and source function (SF) contributions has been performed to establish the degree of antiaromaticity of the central five-membered ring in all the derivatives. Electrostatic potentials mapped on the isodensity surface show that electron withdrawing substituents turn both C and O atoms of the carbonyl group more electropositive while retaining the direction of polarity.

Nonequilibrium ``Melting'' of a Charge Density Wave Insulator via an Ultrafast Laser Pulse

We employ an exact solution of the simplest model for pump-probe time-resolved photoemission spectroscopy in charge-density-wave systems to show how, in nonequilibrium, the gap in the density of states disappears while the charge density remains modulated, and then the gap reforms after the pulse has passed. This nonequilibrium scenario qualitatively describes the common short-time experimental features in TaS2 and TbTe3, indicating a quasiuniversality for nonequilibrium ``melting'' with qualitative features that can be easily understood within a simple picture.

Modelling the effects of chorus species composition and caller density on acoustic masking interference in multispecies choruses of crickets and katydids

Natural multispecies acoustic choruses such as the dusk chorus of a tropical rain forest consist of simultaneously signalling individuals of different species whose calls travel through a common shared medium before reaching their `intended' receivers. This causes masking interference between signals and impedes signal detection, recognition and localization. The levels of acoustic overlap depend on a number of factors, including call structure, intensity, habitat-dependent signal attenuation and receiver tuning. In addition, acoustic overlaps should also depend on caller density and the species composition of choruses, including relative and absolute abundance of the different calling species. In this study, we used simulations to examine the effects of chorus species relative abundance and caller density on the levels of effective heterospecific acoustic overlap in multispecies choruses composed of the calls of five species of crickets and katydids that share the understorey of a rain forest in southern India. We found that on average species-even choruses resulted in higher levels of effective heterospecific acoustic overlap than choruses with strong dominance structures. This effect was found consistently across dominance levels ranging from 0.4 to 0.8 for larger choruses of forty individuals. For smaller choruses of twenty individuals, the effect was seen consistently for dominance levels of 0.6 and 0.8 but not 0.4. Effective acoustic overlap (EAO) increased with caller density but the manner and extent of increase depended both on the species' call structure and the acoustic context provided by the composition scenario. The Phaloria sp. experienced very low levels of EAO and was highly buffered to changes in acoustic context whereas other species experienced high FAO across contexts or were poorly buffered. These differences were not simply predictable from call structures. These simulation-based findings may have important implications for acoustic biodiversity monitoring and for the study of acoustic masking interference in natural environments. (C) 2013 Elsevier B.V. All rights reserved.