Quantum chemical study on influence of intermolecular hydrogen bonding on the geometry, the atomic charges and the vibrational dynamics of 2,6-dichlorobenzonitrile

FT-IR (4000-400 cm(-1)) and FT-Raman (4000-200 cm(-1)) spectral measurements on solid 2,6-dichlorobenzonitrile (2,6-DCBN) have been done. The molecular geometry, harmonic vibrational frequencies and bonding features in the ground state have been calculated by density functional theory at the B3LYP/6-311++G (d,p) level. A comparison between the calculated and the experimental results covering the molecular structure has been made. The assignments of the fundamental vibrational modes have been done on the basis of the potential energy distribution (PED). To investigate the influence of intermolecular hydrogen bonding on the geometry, the charge distribution and the vibrational spectrum of 2,6-DCBN; calculations have been done for the monomer as well as the tetramer. The intermolecular interaction energies corrected for basis set superposition error (BSSE) have been calculated using counterpoise method. Based on these results, the correlations between the vibrational modes and the structure of the tetramer have been discussed. Molecular electrostatic potential (MEP) contour map has been plotted in order to predict how different geometries could interact. The Natural Bond Orbital (NBO) analysis has been done for the chemical interpretation of hyperconjugative interactions and electron density transfer between occupied (bonding or lone pair) orbitals to unoccupied (antibonding or Rydberg) orbitals. UV spectrum was measured in methanol solution. The energies and oscillator strengths were calculated by Time Dependent Density Functional Theory (TD-DFT) and matched to the experimental findings. TD-DFT method has also been used for theoretically studying the hydrogen bonding dynamics by monitoring the spectral shifts of some characteristic vibrational modes involved in the formation of hydrogen bonds in the ground and the first excited state. The C-13 nuclear magnetic resonance (NMR) chemical shifts of the molecule were calculated by the Gauge independent atomic orbital (GIAO) method and compared with experimental results. Standard thermodynamic functions have been obtained and changes in thermodynamic properties on going from monomer to tetramer have been presented. (C) 2013 Elsevier B.V. All rights reserved.

A parametric study on the buckling of functionally graded material plates with internal discontinuities using the partition of unity method

In this paper, the effect of local defects, viz., cracks and cutouts on the buckling behaviour of functionally graded material plates subjected to mechanical and thermal load is numerically studied. The internal discontinuities, viz., cracks and cutouts are represented independent of the mesh within the framework of the extended finite element method and an enriched shear flexible 4-noded quadrilateral element is used for the spatial discretization. The properties are assumed to vary only in the thickness direction and the effective properties are estimated using the Mori-Tanaka homogenization scheme. The plate kinematics is based on the first order shear deformation theory. The influence of various parameters, viz., the crack length and its location, the cutout radius and its position, the plate aspect ratio and the plate thickness on the critical buckling load is studied. The effect of various boundary conditions is also studied. The numerical results obtained reveal that the critical buckling load decreases with increase in the crack length, the cutout radius and the material gradient index. This is attributed to the degradation in the stiffness either due to the presence of local defects or due to the change in the material composition. (C) 2013 Elsevier Masson SAS. All rights reserved.

A molecular dynamics study of ambient and high pressure phases of silica: Structure and enthalpy variation with molar volume

Extensive molecular dynamics studies of 13 different silica polymorphs are reported in the isothermal-isobaric ensemble with the Parrinello-Rahman variable shape simulation cell. The van Beest-Kramer-van Santen (BKS) potential is shown to predict lattice parameters for most phases within 2%-3% accuracy, as well as the relative stabilities of different polymorphs in agreement with experiment. Enthalpies of high-density polymorphs - CaCl2-type, alpha-PbO2-type, and pyrite-type for which no experimental data are available as yet, are predicted here. Further, the calculated enthalpies exhibit two distinct regimes as a function of molar volume-for low and medium-density polymorphs, it is almost independent of volume, while for high-pressure phases a steep dependence is seen. A detailed analysis indicates that the increased short-range contributions to enthalpy in the high-density phases arise not only from an increased coordination number of silicon but also shorter Si-O bond lengths. Our results indicate that amorphous phases of silica exhibit better optimization of short-range interactions than crystalline phases at the same density while the magnitude of Coulombic contributions is lower in the amorphous phase. (C) 2014 AIP Publishing LLC.

A bottom-up approach for optimization of friction stir processing parameters; a study on aluminium 2024-T3 alloy

Friction stir processing (FSP) is emerging as one of the most competent severe plastic deformation (SPD) method for producing bulk ultra-fine grained materials with improved properties. Optimizing the process parameters for a defect free process is one of the challenging aspects of FSP to mark its commercial use. For the commercial aluminium alloy 2024-T3 plate of 6 mm thickness, a bottom-up approach has been attempted to optimize major independent parameters of the process such as plunge depth, tool rotation speed and traverse speed. Tensile properties of the optimum friction stir processed sample were correlated with the microstructural characterization done using Scanning Electron Microscope (SEM) and Electron Back-Scattered Diffraction (EBSD). Optimum parameters from the bottom-up approach have led to a defect free FSP having a maximum strength of 93% the base material strength. Micro tensile testing of the samples taken from the center of processed zone has shown an increased strength of 1.3 times the base material. Measured maximum longitudinal residual stress on the processed surface was only 30 MPa which was attributed to the solid state nature of FSP. Microstructural observation reveals significant grain refinement with less variation in the grain size across the thickness and a large amount of grain boundary precipitation compared to the base metal. The proposed experimental bottom-up approach can be applied as an effective method for optimizing parameters during FSP of aluminium alloys, which is otherwise difficult through analytical methods due to the complex interactions between work-piece, tool and process parameters. Precipitation mechanisms during FSP were responsible for the fine grained microstructure in the nugget zone that provided better mechanical properties than the base metal. (C) 2014 Elsevier Ltd. All rights reserved.

Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model

In this study, we applied the integration methodology developed in the companion paper by Aires (2014) by using real satellite observations over the Mississippi Basin. The methodology provides basin-scale estimates of the four water budget components (precipitation P, evapotranspiration E, water storage change Delta S, and runoff R) in a two-step process: the Simple Weighting (SW) integration and a Postprocessing Filtering (PF) that imposes the water budget closure. A comparison with in situ observations of P and E demonstrated that PF improved the estimation of both components. A Closure Correction Model (CCM) has been derived from the integrated product (SW+PF) that allows to correct each observation data set independently, unlike the SW+PF method which requires simultaneous estimates of the four components. The CCM allows to standardize the various data sets for each component and highly decrease the budget residual (P - E - Delta S - R). As a direct application, the CCM was combined with the water budget equation to reconstruct missing values in any component. Results of a Monte Carlo experiment with synthetic gaps demonstrated the good performances of the method, except for the runoff data that has a variability of the same order of magnitude as the budget residual. Similarly, we proposed a reconstruction of Delta S between 1990 and 2002 where no Gravity Recovery and Climate Experiment data are available. Unlike most of the studies dealing with the water budget closure at the basin scale, only satellite observations and in situ runoff measurements are used. Consequently, the integrated data sets are model independent and can be used for model calibration or validation.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.