Proposal for Graphene-Boron Nitride Heterobilayer-Based Tunnel FET

We investigate the gate-controlled direct band-to-band tunneling (BTBT) current in a graphene-boron nitride (G-BN) heterobilayer channel-based tunnel field effect transistor. We first study the imaginary band structure of hexagonal and Bernal-stacked heterobilayers by density functional theory, which is then used to evaluate the gate-controlled current under the Wentzel-Kramers-Brillouin approximation. It is shown that the direct BTBT is probable for a certain interlayer spacing of the G-BN which depends on the stacking orders.

Taming of large diameter triaxial setup

Triaxial tests are essential to estimate the shear strength properties of the soil or rock. Normally triaxial tests are carried out on samples of 38 mm diameter and 76 mm height. Granular materials, predominantly used in base/sub-base construction of pavements or in railways have size range of 60-75 mm. Determination of shear strength parameters of those materials can be made possible only through triaxial tests on large diameter samples. This paper describes a large diameter cyclic triaxial testing facility set up in the Geotechnical Engineering lab of Indian Institute of Science. This setup consists of 100 kN capacity dynamic loading frame, which facilitates testing of samples of up to 300 mm diameter and 600 mm height. The loading ram can be actuated up to a maximum frequency of 10 Hz, with maximum amplitude of 100 mm. The setup is capable of carrying out static as well as dynamic triaxial tests under isotropic, anisotropic conditions with a maximum confining pressure of 1 MPa. Working with this setup is a difficult task because of the size of the sample. In this paper, a detailed discussion on the various problems encountered during the initial testing using the equipment, the ideas and solutions adopted to solve them are presented. Pilot experiments on granular sub-base material of 53 mm down size are also presented.

A scaled unscented transformation based directed Gaussian sum filter for nonlinear dynamic system identification

Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

Iterated gain-based stochastic filters for dynamic system identification

We propose a novel form of nonlinear stochastic filtering based on an iterative evaluation of a Kalman-like gain matrix computed within a Monte Carlo scheme as suggested by the form of the parent equation of nonlinear filtering (Kushner-Stratonovich equation) and retains the simplicity of implementation of an ensemble Kalman filter (EnKF). The numerical results, presently obtained via EnKF-like simulations with or without a reduced-rank unscented transformation, clearly indicate remarkably superior filter convergence and accuracy vis-a-vis most available filtering schemes and eminent applicability of the methods to higher dimensional dynamic system identification problems of engineering interest. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Spatially Adaptive Kernel Regression Using Risk Estimation

An important question in kernel regression is one of estimating the order and bandwidth parameters from available noisy data. We propose to solve the problem within a risk estimation framework. Considering an independent and identically distributed (i.i.d.) Gaussian observations model, we use Stein's unbiased risk estimator (SURE) to estimate a weighted mean-square error (MSE) risk, and optimize it with respect to the order and bandwidth parameters. The two parameters are thus spatially adapted in such a manner that noise smoothing and fine structure preservation are simultaneously achieved. On the application side, we consider the problem of image restoration from uniform/non-uniform data, and show that the SURE approach to spatially adaptive kernel regression results in better quality estimation compared with its spatially non-adaptive counterparts. The denoising results obtained are comparable to those obtained using other state-of-the-art techniques, and in some scenarios, superior.

Diffraction tomography from intensity measurements: an evolutionary stochastic search to invert experimental data

We develop iterative diffraction tomography algorithms, which are similar to the distorted Born algorithms, for inverting scattered intensity data. Within the Born approximation, the unknown scattered field is expressed as a multiplicative perturbation to the incident field. With this, the forward equation becomes stable, which helps us compute nearly oscillation-free solutions that have immediate bearing on the accuracy of the Jacobian computed for use in a deterministic Gauss-Newton (GN) reconstruction. However, since the data are inherently noisy and the sensitivity of measurement to refractive index away from the detectors is poor, we report a derivative-free evolutionary stochastic scheme, providing strictly additive updates in order to bridge the measurement-prediction misfit, to arrive at the refractive index distribution from intensity transport data. The superiority of the stochastic algorithm over the GN scheme for similar settings is demonstrated by the reconstruction of the refractive index profile from simulated and experimentally acquired intensity data. (C) 2014 Optical Society of America

Germanane: a Low Effective Mass and High Bandgap 2-D Channel Material for Future FETs

We investigate the electronic properties of Germanane and analyze its importance as 2-D channel material in switching devices. Considering two types of morphologies, namely, chair and boat, we study the real band structure, the effective mass variation, and the complex band structure of unstrained Germanane by density-functional theory. The chair morphology turns out to be a more effective channel material for switching devices than the boat morphology. Furthermore, we study the effect of elastic strain, van der Waals force, and vertical electric field on these band structure properties. Due to its very low effective mass with relatively high-energy bandgap, in comparison with the other 2-D materials, Germanane appears to provide superior performance in switching device applications.

Diffusing-wave spectroscopy in an inhomogeneous object: Local viscoelastic spectra from ultrasound-assisted measurement of correlation decay arising from the ultrasound focal volume

We demonstrate diffusing-wave spectroscopy (DWS) in a localized region of a viscoelastically inhomogeneous object by measurement of the intensity autocorrelation g(2)(tau)] that captures only the decay introduced by the temperature-induced Brownian motion in the region. The region is roughly specified by the focal volume of an ultrasound transducer which introduces region specific mechanical vibration owing to insonification. Essential characteristics of the localized non-Markovian dynamics are contained in the decay of the modulation depth M(tau)], introduced by the ultrasound forcing in the focal volume selected, on g(2)(tau). The modulation depth M(tau(i)) at any delay time tau(i) can be measured by short-time Fourier transform of g(2)(tau) and measurement of the magnitude of the spectrum at the ultrasound drive frequency. By following the established theoretical framework of DWS, we are able to connect the decay in M(tau) to the mean-squared displacement (MSD) of scattering centers and the MSD to G*(omega), the complex viscoelastic spectrum. A two-region composite polyvinyl alcohol phantom with different viscoelastic properties is selected for demonstrating local DWS-based recovery of G*(omega) corresponding to these regions from the measured region specific M(tau(i))vs tau(i). The ultrasound-assisted measurement of MSD is verified by simulating, using a generalized Langevin equation (GLE), the dynamics of the particles in the region selected as well as by the usual DWS experiment without the ultrasound. It is shown that whereas the MSD obtained by solving the GLE without the ultrasound forcing agreed with its experimental counterpart covering small and large values of tau, the match was good only in the initial transients in regard to experimental measurements with ultrasound.

Haloarchaeal gas vesicle nanoparticles displaying Salmonella SopB antigen reduce bacterial burden when administered with live attenuated bacteria

Innovative vaccines against typhoid and other Salmonella diseases that are safe, effective, and inexpensive are urgently needed. In order to address this need, buoyant, self-adjuvating gas vesicle nanoparticles (GVNPs) from the halophilic archaeon Halobacterium sp. NRC-1 were bioengineered to display the highly conserved Salmonella enterica antigen SopB, a secreted inosine phosphate effector protein injected by pathogenic bacteria during infection into the host cell. Two highly conserved sopB gene segments near the 3'-coding region, named sopB4 and B5, were each fused to the gvpC gene, and resulting GVNPs were purified by centrifugally accelerated flotation. Display of SopB4 and B5 antigenic epitopes on GVNPs was established by Western blotting analysis using antisera raised against short synthetic peptides of SopB. Immunostimulatory activities of the SopB4 and B5 nanoparticles were tested by intraperitoneal administration of recombinant GVNPs to BALB/c mice which had been immunized with S. enterica serovar Typhimurium 14028 Delta pmrG-HM-D (DV-STM-07), a live attenuated vaccine strain. Proinflammatory cytokines IFN-gamma, IL-2, and IL-9 were significantly induced in mice boosted with SopB5-GVNPs, consistent with a robust Th1 response. After challenge with virulent S. enterica serovar Typhimurium 14028, bacterial burden was found to be diminished in spleen of mice boosted with SopB4-GVNPs and absent or significantly diminished in liver, mesenteric lymph node, and spleen of mice boosted with SopB5-GVNPs, indicating that the C-terminal portions of SopB displayed on GVNPs elicit a protective response to Salmonella infection in mice. SopB antigen-GVNPs were found to be stable at elevated temperatures for extended periods without refrigeration in Halobacterium cells. The results all together show that bioengineered GVNPs are likely to represent a valuable platform for the development of improved vaccines against Salmonella diseases. (C) 2014 Elsevier Ltd. All rights reserved.

Microstructural Features of Hot Deformed Nb-1Zr-0.1C Alloy

Niobium-based alloys are well-established refractory materials; as a result of their high melting temperature and good creep properties, these alloys find their applications in nuclear reactors. The present study deals with a microstructural response of these materials during hot working. The evolution of microstructure and texture during high-temperature deformation has been investigated in the temperature range 1500-1700A degrees C and strain rate range of 0.001-0.1 s(-1). For each deformed sample, the microstructure has been examined in detail. The microstructural features clearly revealed the formation of a substructure and the occurrence of dynamic recrystallization in a proper temperature-strain rate window. At low strain rates, the necklace structure formation was more prominent.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

A perturbed martingale approach to global optimization

A new global stochastic search, guided mainly through derivative-free directional information computable from the sample statistical moments of the design variables within a Monte Carlo setup, is proposed. The search is aided by imparting to the directional update term additional layers of random perturbations referred to as `coalescence' and `scrambling'. A selection step, constituting yet another avenue for random perturbation, completes the global search. The direction-driven nature of the search is manifest in the local extremization and coalescence components, which are posed as martingale problems that yield gain-like update terms upon discretization. As anticipated and numerically demonstrated, to a limited extent, against the problem of parameter recovery given the chaotic response histories of a couple of nonlinear oscillators, the proposed method appears to offer a more rational, more accurate and faster alternative to most available evolutionary schemes, prominently the particle swarm optimization. (C) 2014 Elsevier B.V. All rights reserved.

Solubilities of n-Butyl Esters in Supercritical Carbon Dioxide

The solubilities of butyl stearate and butyl laurate were determined in the temperature range of 308 K to 323 K and 313 K to 328 K, respectively, at pressures of 10 MPa to 16 MPa. The solubility of butyl laurate was higher than that of butyl stearate by almost an order in magnitude. Retrograde behavior was observed throughout the investigated pressure range. Semiempirical models such as Mendez-Teja, Chrastil, and other density-based models were used to correlate the experimental data of our work as well as several other liquid solutes.

pentahexoctite: A new two-dimensional allotrope of carbon

The ability of carbon to exist in many forms across dimensions has spawned search in exploring newer allotropes consisting of either, different networks of polygons or rings. While research on various 3D phases of carbon has been extensive, 2D allotropes formed from stable rings are yet to be unearthed. Here, we report a new sp(2) hybridized two-dimensional allotrope consisting of continuous 5-6-8 rings of carbon atoms, named as ``pentahexoctite''. The absence of unstable modes in the phonon spectra ensures the stability of the planar sheet. Furthermore, this sheet has mechanical strength comparable to graphene. Electronically, the sheet is metallic with direction-dependent flat and dispersive bands at the Fermi level ensuring highly anisotropic transport properties. This sheet serves as a precursor for stable 1D nanotubes with chirality-dependent electronic and mechanical properties. With these unique properties, this sheet becomes another exciting addition to the family of robust novel 2D allotropes of carbon.

Simple three parameter equations for correlating liquid phase compositions in subcritical and supercritical systems

Two Chrastil type expressions have been developed to model the solubility of supercritical fluids/gases in liquids. The three parameter expressions proposed correlates the solubility as a function of temperature, pressure and density. The equation can also be used to check the self-consistency of the experimental data of liquid phase compositions for supercritical fluid-liquid equilibria. Fifty three different binary systems (carbon-dioxide + liquid) with around 2700 data points encompassing a wide range of compounds like esters, alcohols, carboxylic acids and ionic liquids were successfully modeled for a wide range of temperatures and pressures. Besides the test for self-consistency, based on the data at one temperature, the model can be used to predict the solubility of supercritical fluids in liquids at different temperatures. (C) 2014 Elsevier B.V. All rights reserved.