Maximum mass of stable magnetized highly super-Chandrasekhar white dwarfs: stable solutions with varying magnetic fields

We address the issue of stability of recently proposed significantly super-Chandrasekhar white dwarfs. We present stable solutions of magnetostatic equilibrium models for super-Chandrasekhar white dwarfs pertaining to various magnetic field profiles. This has been obtained by self-consistently including the effects of the magnetic pressure gradient and total magnetic density in a general relativistic framework. We estimate that the maximum stable mass of magnetized white dwarfs could be more than 3 solar mass. This is very useful to explain peculiar, overluminous type Ia supernovae which do not conform to the traditional Chandrasekhar mass-limit.

Super-Resolution Reconstruction in Frequency-Domain Optical-Coherence Tomography Using the Finite-Rate-of-Innovation Principle

The standard approach to signal reconstruction in frequency-domain optical-coherence tomography (FDOCT) is to apply the inverse Fourier transform to the measurements. This technique offers limited resolution (due to Heisenberg's uncertainty principle). We propose a new super-resolution reconstruction method based on a parametric representation. We consider multilayer specimens, wherein each layer has a constant refractive index and show that the backscattered signal from such a specimen fits accurately in to the framework of finite-rate-of-innovation (FRI) signal model and is represented by a finite number of free parameters. We deploy the high-resolution Prony method and show that high-quality, super-resolved reconstruction is possible with fewer measurements (about one-fourth of the number required for the standard Fourier technique). To further improve robustness to noise in practical scenarios, we take advantage of an iterated singular-value decomposition algorithm (Cadzow denoiser). We present results of Monte Carlo analyses, and assess statistical efficiency of the reconstruction techniques by comparing their performance against the Cramer-Rao bound. Reconstruction results on experimental data obtained from technical as well as biological specimens show a distinct improvement in resolution and signal-to-reconstruction noise offered by the proposed method in comparison with the standard approach.

Modelling of optical transport behavior of organic photovoltaic devices with nano-pillar transparent conducting electrodes

Optical transport behavior of organic photo-voltaic devices with nano-pillar transparent electrodes is investigated in this paper in order to understand possible enhancement of their charge-collection efficiency. Modeling and simulations of optical transport due to this architecture show an interesting regime of length-scale dependent optical characteristics. An electromagnetic wave propagation model is employed with simulation objectives toward understanding the mechanism of optical scattering and waveguide effects due to the nano-pillars and effective transmission through the active layer. Partial filling of gaps between the nano-pillars due to the nano-fabrication process is taken into consideration. Observations made in this paper will facilitate appropriate design rules for nano-pillar electrodes. (C) 2014 AIP Publishing LLC.

Fabrication of a novel biomaterial with enhanced mechanical and conducting properties

Conducting polymers have the combined advantages of metal conductivity with ease in processing and biocompatibility; making them extremely versatile for biosensor and tissue engineering applications. However, the inherent brittle property of conducting polymers limits their direct use in such applications which generally warrant soft and flexible material responses. Addition of fillers increases the material compliance, but is achieved at the cost of reduced electrical conductivity. To retain suitable conductivity without compromising the mechanical properties, we fabricate an electroactive blend (dPEDOT) using low grade PEDOT: PSS as the base conducting polymer with polyvinyl alcohol as filler and glycerol as a dopant. Bulk dPEDOT films show a thermally stable response till 110 degrees C with over seven fold increase in room temperature conductivity as compared to 0.002 S cm(-1) for pristine PEDOT: PSS. We characterize the nonlinear stress-strain response of dPEDOT, well described using a Mooney-Rivlin hyperelastic model, and report elastomer-like moduli with ductility similar to fives times its original length. Dynamic mechanical analysis shows constant storage moduli over a large range of frequencies with corresponding linear increase in tan(delta). We relate the enhanced performance of dPEDOT with the underlying structural constituents using FTIR and AFM microscopy. These data demonstrate specific interactions between individual components of dPEDOT, and their effect on surface topography and material properties. Finally, we show biocompatibility of dPEDOT using fibroblasts that have comparable cell morphologies and viability as the control, which make dPEDOT attractive as a biomaterial.

An insight to the low temperature conduction mechanism of c-axis grown Al-doped ZnO, a widely used transparent conducting oxide

Al-doped ZnO thin films were synthesized from oxygen reactive co-sputtering of Al and Zn targets. Explicit doping of Al in the highly c-axis oriented crystalline films of ZnO was manifested in terms of structural optical and electrical properties. Electrical conduction with different extent of Al doping into the crystal lattice of ZnO (AZnO) were characterized by frequency dependent (40 Hz-50 MHz) resistance. From the frequency dependent resistance, the ac conduction of them, and correlations of localized charge particles in the crystalline films were studied. The dc conduction at the low frequency region was found to increase from 8.623 mu A to 1.14 mA for the samples AZnO1 (1 wt% Al) and AZnO2 (2 wt% Al), respectively. For the sample AZnO10 (10 wt% Al) low frequency dc conduction was not found due to the electrode polarization effect. The measure of the correlation length by inverse of threshold frequency (omega(0)) showed that on application of a dc electric field such length decreases and the decrease in correlation parameter(s) indicates that the correlation between potentials wells of charge particles decreases for the unidirectional nature of dc bias. The comparison between the correlation length and the extent of correlation in the doped ZnO could not be made due to the observation of several threshold frequencies at the extent of higher doping. Such threshold frequencies were explained by the population possibility of correlated charge carriers that responded at different frequencies. For AZnO2 (2% Al), the temperature dependent (from 4.5 to 288 K) resistance study showed that the variable range hopping mechanism was the most dominating conduction mechanism at higher temperature whereas at low temperature region it was influenced by the small polaronic hopping conduction mechanism. There was no significant influence found in these mechanisms on applications of 1, 2 and 3 V as biases.

Super Resolution Using a Single Image Dictionary

To perform super resolution of low resolution images, state-of-the-art methods are based on learning a pair of lowresolution and high-resolution dictionaries from multiple images. These trained dictionaries are used to replace patches in lowresolution image with appropriate matching patches from the high-resolution dictionary. In this paper we propose using a single common image as dictionary, in conjunction with approximate nearest neighbour fields (ANNF) to perform super resolution (SR). By using a common source image, we are able to bypass the learning phase and also able to reduce the dictionary from a collection of hundreds of images to a single image. By adapting recent developments in ANNF computation, to suit super-resolution, we are able to perform much faster and accurate SR than existing techniques. To establish this claim, we compare the proposed algorithm against various state-of-the-art algorithms, and show that we are able to achieve b etter and faster reconstruction without any training.

A trade-off between maxima in efficiency and specific work output of super- and trans-critical CO2 Brayton cycles

Several operational aspects for thermal power plants in general are non-intuitive and involve simultaneous optimization of a number of operational parameters. In the case of solar operated power plants, it is even more difficult due to varying heat source temperatures induced by variability in insolation levels. This paper introduces a quantitative methodology for load regulation of a CO2 based Brayton cycle power plant using the `thermal efficiency and specific work output' coordinate system. The analysis shows that a transcritical CO2 cycle offers more flexibility under part load performance than the supercritical cycle in case of non-solar power plants. However, for concentrated solar power, where efficiency is important, supercritical CO2 cycle fares better than transcritical CO2 cycle. A number of empirical equations relating heat source temperature, high side pressure with efficiency and specific work output are proposed which could assist in generating control algorithms. (C) 2015 Elsevier B.V. All rights reserved.

Engineering a Water-Dispersible, Conducting, Photoreduced Graphene Oxide

A critical limitation that has hampered widespread application of the electrically conducting reduced graphene oxide (r-GO) is its poor aqueous dispersibility. Here we outline a strategy to obtain water-dispersible conducting r-GO sheets, free of any stabilizing agents, by exploiting the fact that the kinetics of the photoreduction of the insulating GO is heterogeneous. We show that by controlling UV exposure times and pH, we can obtain r-GO sheets with the conducting sp(2)-graphitic domains restored but with the more acidic carboxylic groups, responsible for aqueous dispersibility, intact. The resultant photoreduced r-GO sheets are both conducting and water-dispersible.

MRT Letter: A Unified Accelerated Maximum Likelihood Technique for Widefield, Confocal, and Super-Resolution 4Pi Microscopy

We propose an algorithmic technique for accelerating maximum likelihood (ML) algorithm for image reconstruction in fluorescence microscopy. This is made possible by integrating Biggs-Andrews (BA) method with ML approach. The results on widefield, confocal, and super-resolution 4Pi microscopy reveal substantial improvement in the speed of 3D image reconstruction (the number of iterations has reduced by approximately one-half). Moreover, the quality of reconstruction obtained using accelerated ML closely resembles with nonaccelerated ML method. The proposed technique is a step closer to realize real-time reconstruction in 3D fluorescence microscopy. Microsc. Res. Tech. 78:331-335, 2015. (c) 2015 Wiley Periodicals, Inc.

A critical review on in situ reduction of graphene oxide during preparation of conducting polymeric nanocomposites

Graphene oxide (GO), prepared by chemical oxidation of graphite, serves as a building block for developing polymeric nanocomposites. However, their application in electrical conductivity is limited by the fact that the oxygen sites on GO trap electrons and impede charge transport. Conducting nanocomposites can be developed by reducing GO. Various strategies have been adopted to either reduce GO ex situ, before the composite preparation, or in situ during the development of the nanocomposites. The current state of research on in situ reduction of GO during the preparation of conducting polymeric nanocomposites is discussed in this review. The mechanism and the efficiency of reduction is discussed with respect to various strategies employed during the preparation of the nanocomposite, the type of polymer used, and the processing conditions employed, etc. Its overall effect on the electrical conductivity of the nanocomposites is also discussed and the future outlook in this area is presented.

Engineering a nanostructured ``super surface'' with superhydrophobic and superkilling properties

We present a nanostructured ``super surface'' fabricated using a simple recipe based on deep reactive ion etching of a silicon wafer. The topography of the surface is inspired by the surface topographical features of dragonfly wings. The super surface is comprised of nanopillars 4 mm in height and 220 nm in diameter with random inter-pillar spacing. The surface exhibited superhydrophobicity with a static water contact angle of 154.0 degrees and contact angle hysteresis of 8.3 degrees. Bacterial studies revealed the bactericidal property of the surface against both gram negative (Escherichia coli) and gram positive (Staphylococcus aureus) strains through mechanical rupture of the cells by the sharp nanopillars. The cell viability on these nanostructured surfaces was nearly six-fold lower than on the unmodified silicon wafer. The nanostructured surface also killed mammalian cells (mouse osteoblasts) through mechanical rupture of the cell membrane. Thus, such nanostructured super surfaces could find applications for designing selfcleaning and anti-bacterial surfaces in diverse applications such as microfluidics, surgical instruments, pipelines and food packaging.

GRMHD formulation of highly super-Chandrasekhar magnetized white dwarfs: stable configurations of non-spherical white dwarfs

The topic of magnetized super-Chandrasekhar white dwarfs is in the limelight, particularly in the last few years, since our proposal of their existence. By full-scale general relativistic magnetohydrodynamic (GRMHD) numerical analysis, we confirm in this work the existence of stable, highly magnetized, significantly super-Chandrasekhar white dwarfs with mass more than 3 solar mass. While a poloidal field geometry renders the white dwarfs oblate, a toroidal field makes them prolate retaining an overall quasi-spherical shape, as speculated in our earlier work. These white dwarfs are expected to serve as the progenitors of over-luminous type Ia supernovae.

Modified Einstein's gravity as a possible missing link between sub- and super-Chandrasekhar type Ia supernovae

We explore the effect of modification to Einstein's gravity in white dwarfs for the first time in the literature, to the best of our knowledge. This leads to significantly sub- and super-Chandrasekhar limiting masses of white dwarfs, determined by a single model parameter. On the other hand, type Ia supernovae (SNeIa), a key to unravel the evolutionary history of the universe, are believed to be triggered in white dwarfs having mass close to the Chandrasekhar limit. However, observations of several peculiar, under- and over-luminous SNeIa argue for exploding masses widely different from this limit. We argue that explosions of the modified gravity induced sub- and super-Chandrasekhar limiting mass white dwarfs result in under- and over-luminous SNeIa respectively, thus unifying these two apparently disjoint sub-classes and, hence, serving as a missing link. Our discovery raises two fundamental questions. Is the Chandrasekhar limit unique? Is Einstein's gravity the ultimate theory for understanding astronomical phenomena? Both the answers appear to be no!

Synthetic image super resolution using FeatureMatch

In this paper, we propose a super resolution (SR) method for synthetic images using FeatureMatch. Existing state-of-the-art super resolution methods are learning based methods, where a pair of low-resolution and high-resolution dictionary pair are trained, and this trained pair is used to replace patches in low-resolution image with appropriate matching patches from the high-resolution dictionary. In this paper, we show that by using Approximate Nearest Neighbour Fields (ANNF), and a common source image, we can by-pass the learning phase, and use a single image for dictionary. Thus, reducing the dictionary from a collection obtained from hundreds of training images, to a single image. We show that by modifying the latest developments in ANNF computation, to suit super resolution, we can perform much faster and more accurate SR than existing techniques. To establish this claim we will compare our algorithm against various state-of-the-art algorithms, and show that we are able to achieve better and faster reconstruction without any training phase.

An Evaluation of the Effectiveness of a Charged Bilayered Conducting Fine Mesh as a Dust Filter

Aim: To develop a mesh meant to be mounted on a windowpane that will act as a barrier for dust, while allowing wind to pass freely. Materials and Methods: Two small metal meshes separated at 1 cm, connected to an electrostatic generator and holding opposite charges are used. A videographic analysis has been performed. Results: The charged bilayered mesh was able to prevent a large portion of dust from passing through. Conclusion: The device is a simple, economical, and reliable way of reducing the entry of dust into a room, easing the need for periodic cleaning, and thus creating a healthier environment for the inhabitants of the building. It also has potential space applications.