Anomalous structural relaxations in PVDF rich blends with PMMA in the presence of surface functionalized CNTs

The structural relaxations in PVDF rich blends with PMMA can be quite interesting in understanding the origin of the different molecular relaxations associated with the crystalline and amorphous phases, crystal-amorphous interphase and the segmental motions. In light of our recent findings, we understood that the origin of these molecular relaxations were strongly contingent on the concentration of PMMA in the blend, crystalline morphology and the surface functional moieties on multiwall carbon nanotubes (CNTs). In addition, for the blends with concentration of PMMA >= 25 wt%, the structural relaxations often merge and are dielectrically indistinguishable. In this study, we attempted to determine the critical width in composition where the structural relaxations can be distinctly realized both in the control as well as blends with amine functionalized CNTs (NH2-CNTs). Intriguingly, we observed that in a narrow zone in composition (with PMMA concentration >= 10 wt% and <= 25 wt%), the molecular relaxations can be dielectrically distinguished and they often merge for all other compositions. Furthermore, we attempted to understand how this critical width in composition is related to the crystalline morphology using small angle X-ray scattering and polarizing optical microscopy and the crystal structure using FTIR and Raman spectroscopy. We now understand that although the formation of beta crystals in the blends has no direct correlation with the observed molecular relaxations, the amorphous miscibility and the interphase regions seem to be dictating the origin of different molecular relaxations in the blends. The latter was observed to be strongly contingent on the concentration of PMMA in the blends.

Effect of absolute pressure on flow through a textured hydrophobic microchannel

The potential of textured hydrophobic surfaces to provide substantial drag reduction has been attributed to the presence of air bubbles trapped on the surface cavities. In this paper, we present results on water flow past a textured hydrophobic surface, while systematically varying the absolute pressure close to the surface. Trapped air bubbles on the surface are directly visualized, along with simultaneous pressure drop measurements across the surface in a microchannel configuration. We find that varying the absolute pressure within the channel greatly influences the trapped air bubble behavior, causing a consequent effect on the pressure drop (drag). When the absolute pressure within the channel is maintained below atmospheric pressure, we find that the air bubbles grow in size, merge and eventually detach from the surface. This growth and subsequent merging of the air bubbles leads to a substantial increase in the pressure drop. On the other hand, a pressure above the atmospheric pressure within the channel leads to gradual shrinkage and eventual disappearance of trapped air bubbles. We find that in this case, air bubbles do cause reduction in the pressure drop with the minimum pressure drop (or maximum drag reduction) occurring when the bubbles are flush with the surface. These results show that the trapped air bubble dynamics and the pressure drop across a textured hydrophobic microchannel are very significantly dependent on the absolute pressure within the channel. The results obtained hold important implications toward achieving sustained drag reduction in microfluidic applications.

A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation: Application to Image Denoising

In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

Effect Of Administration Of Luteinizing-Hormone (Lh) And Deprivation Of Lh On The Proteins Of Smooth Endoplasmic-Reticulum Of Immature And Adult-Rat Leydig-Cells

Analysis of proteins of smooth endoplasmic reticulum (SER) of Leydig cells from immature and admit rats by two-dimensional polyacrylamide gel electrophoresis (SDS-PAGE) revealed the presence of several new proteins in the adult rats. Administration of human chorionic gonadotropin to immature rats for ten days also resulted in a significant increase as well as the appearance of several new proteins. The general pattern of SDS-PAGE analysis of the SER proteins of Leydig cells resembled that of the adult rat. SDS-PAGE analysis of the SER proteins of Leydig cells from adult rats following deprivation of endogenous luteinizing hormone by administration of antiserum to ovine luteinizing hormone resulted in a pattern which to certain extent resembled that of an immature I at. Western Blot analysis of luteinizing hormone antiserum treated rat Leydig cell proteins revealed a decrease in the 17-alpha-hydroxylase compared to the control. These results provide biochemical evidence for the suggestion that one of the main functions of luteinizing hormone is the control of biogenesis and/or turnover SER of Leydig cells in the rat.

Composite MR image reconstruction and unaliasing for general trajectories using neural networks

In rapid parallel magnetic resonance imaging, the problem of image reconstruction is challenging. Here, a novel image reconstruction technique for data acquired along any general trajectory in neural network framework, called ``Composite Reconstruction And Unaliasing using Neural Networks'' (CRAUNN), is proposed. CRAUNN is based on the observation that the nature of aliasing remains unchanged whether the undersampled acquisition contains only low frequencies or includes high frequencies too. Here, the transformation needed to reconstruct the alias-free image from the aliased coil images is learnt, using acquisitions consisting of densely sampled low frequencies. Neural networks are made use of as machine learning tools to learn the transformation, in order to obtain the desired alias-free image for actual acquisitions containing sparsely sampled low as well as high frequencies. CRAUNN operates in the image domain and does not require explicit coil sensitivity estimation. It is also independent of the sampling trajectory used, and could be applied to arbitrary trajectories as well. As a pilot trial, the technique is first applied to Cartesian trajectory-sampled data. Experiments performed using radial and spiral trajectories on real and synthetic data, illustrate the performance of the method. The reconstruction errors depend on the acceleration factor as well as the sampling trajectory. It is found that higher acceleration factors can be obtained when radial trajectories are used. Comparisons against existing techniques are presented. CRAUNN has been found to perform on par with the state-of-the-art techniques. Acceleration factors of up to 4, 6 and 4 are achieved in Cartesian, radial and spiral cases, respectively. (C) 2010 Elsevier Inc. All rights reserved.

A note on the damping and oscillations of a fluid drop moving in another fluid

The oscillations of a drop moving in another fluid medium have been studied at low values of Reynolds number and Weber number by taking into consideration the shape of the drop and the viscosities of the two phases in addition to the interfacial tension. The deformation of the drop modifies the Lamb's expression for frequency by including a correction term while the viscous effects split the frequency into a pair of frequencies—one lower and the other higher than Lamb's. The lower frequency mode has ample experimental support while the higher frequency mode has also been observed. The two modes almost merge with Lamb's frequency for the asymptotic cases of a drop in free space or a bubble in a dense viscous fluid but the splitting becomes large when the two fluids have similar properties. Instead of oscillations, aperiodic damping modes are found to occur in drops with sizes smaller than a critical size ($\sim\hat{\rho}\hat{\nu}^2/T $). With the help of these calculations, many of the available experimental results are analyzed and discussed.

Structural, magnetic and electrochemical investigation of novel binary Na2-x(Fe1-yMny)P2O7 (0 <= y <= 1) pyrophosphate compounds for rechargeable sodium-ion batteries

Pyrophosphate cathodes have been recently reported as a competent family of insertion compounds for sodium-ion batteries. In the current study, we have investigated the binary Na2 - x(Fe1 - yMny)P2O7 (0 <= y <= 1) pyrophosphate family, synthesized by the classical solid-state method. They form a continuous solid solution maintaining triclinic P-1 (#2) symmetry. The local structural coordination differs mainly by different degrees of Na site occupancy and preferential occupation of the Fe2 site by Mn. The structural and magnetic properties of these mixed-metal pyrophosphate phases have been studied. In each case, complete Fe3+/Fe2+ redox activity has been obtained centered at 3 V vs. Na. The Fe3+/Fe2+ redox process involves multiple steps between 2.5 and 3 V owing to Na-cation ordering during electrochemical cycling, which merge to form a broad single Fe3+/Fe2+ redox peak upon progressive Mn-doping. (C) 2014 Elsevier B.V. All rights reserved.