Effect of hybridizing micron-sized Ti with nano-sized SiC on the microstructural evolution and mechanical response of Mg-5.6Ti composite

In this work, the effect of hybridizing micro-Ti with nano-SiC particulates on the microstructural and the mechanical behaviour of Mg-5.6Ti composite were investigated. Mg materials containing micron-sized Ti particulates hybridized with different amounts of nano-size SiC particulates were synthesized using the disintegrated melt deposition method followed by hot extrusion. The microstructural and mechanical behaviour of the developed Mg hybrid composites were studied in comparison with Mg-5.6Ti. Microstructural characterization revealed grain refinement attributed to the presence of uniformly distributed micro-Ti particles embedded with nano-SiC particulates. Electron back scattered diffraction (EBSD) analyses of Mg-(5.6Ti + 1.0SiC)(BM) hybrid composite showed relatively more localized recrystallized grains and lesser tensile twin fraction, when compared to Mg-5.6Ti. The evaluation of mechanical properties indicated that the best combination of strength and ductility was observed in the Mg-(5.6Ti + 1.0SiC)(BM) hybrid composites. The superior strength properties of the Mg-(5.6Ti + x-SiC)(BM) hybrid composites when compared to Mg-5.6Ti is attributed to the presence of nano-reinforcements, the uniform distribution of the hybridized particles and the better interfacial bonding between the matrix and the reinforcement particles, achieved by nano-SiC addition.

Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning

It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

Using heat treatment effects and EBSD analysis to tailor microstructure of hybrid Mg nanocomposite for enhanced overall mechanical response

In this study, a detailed investigation on the effect of heat treatment on the microstructural characteristics, texture evolution and mechanical properties of Mg-(5.6Ti+2.5B(4)C)(BM) hybrid nanocomposite is presented. Optimised heat treatment parameters, namely, heat treatment temperature and heat treatment time, were first identified through grain size and microhardness measurements. Initially, heat treatment of composites was conducted at temperature range between 100 and 300 degrees C for 1 h. Based on optical microscopic analysis and microhardness measurements, it was evident that significant grain growth and reduction in microhardness occurred for temperatures > 200 degrees C. The cutoff temperature that caused significant grain growth/matrix softening was thus identified. Second, at constant temperature (200 degrees C), the effect of variation of heat treatment time was carried out (ranging between 1 and 5 h) so as to identify the range wherein increase in average grain size and reduction in microhardness occurred. Furthering the study, the effect of optimised heat treatment parameters (200 degrees C, 5 h) on the microstructural texture evolution and hence, on the tensile and compressive properties of the Mg-(5.6Ti+2.5B(4)C)(BM) hybrid nanocomposite was carried out. From electron backscattered diffraction (EBSD) analysis, it was identified that the optimised heat treatment resulted in recrystallisation and residual stress relaxation, as evident from the presence of similar to 87% strain free grains, when compared to that observed in the non-heat treated/as extruded condition (i.e. 2.2 times greater than in the as extruded condition). For the heat treated composite, under both tensile and compressive loads, a significant improvement in fracture strain values (similar to 60% increase) was observed when compared to that of the non-heat treated counterpart, with similar to 20% reduction in yield strength. Based on structure-property correlation, the change in mechanical characteristics is identified to be due to: (1) the presence of less stressed matrix/reinforcement interface due to the relief of residual stresses and (2) texture weakening due to matrix recrystallisation effects, both arising due to heat treatment.

Response of shock wave deformation in AA5086 aluminum alloy

The AA5086 aluminum alloy sheets with different starting textures were subjected to shock wave deformation with an input impulse of similar to 0.2 Ns. Microstructural examination indicate no significant change in grain size; however, the evolution of substructure manifesting intra-granular misorientation was evident. The improvement in hardness indicates the absence of recovery and strain hardening during shock deformation. Shock deformed samples show characteristic texture evolution with high Brass {110}< 112 > component. The study demonstrates the viability of high velocity forming of AA5086 aluminum alloy sheet using shock wave. (C) 2014 Elsevier B.V. All rights reserved.

Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity

Predicting clinical response to anticancer drugs remains a major challenge in cancer treatment. Emerging reports indicate that the tumour microenvironment and heterogeneity can limit the predictive power of current biomarker-guided strategies for chemotherapy. Here we report the engineering of personalized tumour ecosystems that contextually conserve the tumour heterogeneity, and phenocopy the tumour microenvironment using tumour explants maintained in defined tumour grade-matched matrix support and autologous patient serum. The functional response of tumour ecosystems, engineered from 109 patients, to anticancer drugs, together with the corresponding clinical outcomes, is used to train a machine learning algorithm; the learned model is then applied to predict the clinical response in an independent validation group of 55 patients, where we achieve 100% sensitivity in predictions while keeping specificity in a desired high range. The tumour ecosystem and algorithm, together termed the CANScript technology, can emerge as a powerful platform for enabling personalized medicine.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Nano-indentation studies on polymer matrix composites reinforced by few-layer graphene

The mechanical properties of polyvinyl alcohol (PVA) and poly(methyl methacrylate) (PMMA)-matrix composites reinforced by functionalized few-layer graphene (FG) have been evaluated using the nano-indentation technique. A significant increase in both the elastic modulus and hardness is observed with the addition of 0.6 wt% of graphene. The crystallinity of PVA also increases with the addition of FG. This and the good mechanical interaction between the polymer and the FG, which provides better load transfer between the matrix and the fiber, are suggested to be responsible for the observed improvement in mechanical properties of the polymers.

Analysis of a Genomic DNA Expression Library of Mycobacterium tuberculosis Using Tuberculosis Patient Sera: Evidence for Modulation of Host Immune Response

DNA obtained from a human sputum isolate of Mycobacterium tuberculosis, NTI-64719, which showed extensive dissemination in the guinea pig model resulting in a high score for virulence was used to construct an expression library in the lambda ZAP vector. The size of DNA inserts in the library ranged from 1 to 3 kb, and recombinants represented 60% of the total plaques obtained. When probed with pooled serum from chronically infected tuberculosis patients, the library yielded 176 recombinants with a range of signal intensities. Among these, 93 recombinants were classified into 12 groups on the basis of DNA hybridization experiments, The polypeptides synthesized by the recombinants were predominantly LacZ fusion proteins, Serum obtained from patients who were clinically diagnosed to be in the early phase of M. tuberculosis infection was used to probe the 176 recombinants obtained. interestingly, some recombinants that gave very strong signals in the original screen did not react with early-phase serum; conversely, others whose signals were extremely weak in the original screen gave very intense signals with serum from recently infected patients, This indicates the differential nature of either the expression of these antigens or the immune response elicited by them as a function of disease progression.

Response And Stability Of A Stochastic Beam-Column Using Stochastic Fem

A beam-column resting on continuous Winkler foundation and discrete elastic supports is considered. The beam-column is of variable cross-section and the variation of sectional properties along the axis of the beam-column is deterministic. Young's modulus, mass per unit length and distributed axial loadings of the beam-column have a stochastic distribution. The foundation stiffness coefficient of the Winkler model, the stiffnesses of discrete elastic supports, stiffnesses of end springs and the end thrust, are all considered as random parameters. The material property fluctuations and distributed axial loadings are considered to constitute independent, one-dimension uni-variate homogeneous real stochastic fields in space. The foundation stiffness coefficient, stiffnesses of the discrete elastic supports, stiffnesses of end springs and the end thrust are considered to constitute independent random variables. Static response, free vibration and stability behaviour of the beam-column are studied. Hamilton's principle is used to formulate the problem using stochastic FEM. Sensitivity vectors of the response and stability parameters are evaluated. Using these statistics of free vibration frequencies, mode shapes, buckling parameters, etc., are evaluated. A numerical example is given.

Frictional response of fatty acids on steel

Self-assembled monolayers of fatty acids were formed on stainless steel by room-temperature solution deposition. The acids are covalently bound to the Surface as carboxylate in a bidentate manner. To explore the effect Of Saturation in the carbon backbone on friction in sliding tribology, we Study the response of saturated stearic acid (SA) and unsaturated linoleic acid (LA) as self-assembled monolayers using lateral force microscopy and nanotribometry and when the molecules are dispersed in hexadecane, using pin-on-disc tribometry. Over a very wide range (10 MPa-2.5 GPa) of contact pressures it is consistently demonstrated that the unsaturated linoleic acid molecules yield friction which is significantly lower than that of the saturated stearic acid. it is argued, using density functional theory predictions and XPS of slid track, that when the molecular backbone of unsaturated fatty acids are tilted and pressed strongly by a probe, in tribological contact, the high charge density of the double bond region of the backbone allows coupling with the steel Substrate. The interaction yields a low friction carboxylate soap film on the substrate. The saturated fatty acid does not show this effect.

Synergy between tribo-oxidation and strain rate response on governing the dry sliding wear behavior of titanium.

The present work provides an insight into the dry sliding wear behavior of titanium based on synergy between tribo-oxidation and strain rate response. Pin-on-disc tribometer was used to characterize the friction and wear behavior of titanium pin in sliding contact with polycrystalline alumina disk under ambient and vacuum condition. The sliding speed was varied from 0.01 to 1.4 ms(-1), normal load was varied from 15.3 to 76 N and with a sliding distance of 1500 m. It was seen that dry sliding wear behavior of titanium was governed by combination of tribo-oxidation and strain rate response in near surface region of titanium. Strain rate response of titanium was recorded by conducting uni-axial compression tests at constant true strain rate of 100 s(-1) in the temperature range from 298 to 873 K. Coefficient of friction and wear rate were reduced with increased sliding speed from 0.01 to 1.0 ms(-1). This is attributed to the formation of in situ self lubricating oxide film (TiO) and reduction in the intensity of adiabatic shear band cracking in the near surface region. This trend was confirmed by performing series of dry sliding tests under vacuum condition of 2 x 10(-4) Torr. Characterization tools such as optical microscopy, scanning electron microscopy, and X-ray diffractometer provided evidence of such processes. These experimental findings can be applied to enhance the dry sliding wear behavior of titanium with proper choice of operating conditions such as sliding speed, normal load, and environment.

On the probability that the determinant of an nxn matrix over a finite field vanishe

An expression is derived for the probability that the determinant of an n x n matrix over a finite field vanishes; from this it is deduced that for a fixed field this probability tends to 1 as n tends to.

Fast matrix transposition computer implementation

Eklundh's (1972) algorithm to transpose a large matrix stored on an external device such as a disc has been programmed and tested. A simple description of computer implementation is given in this note.

Systematic stability analysis of the renormalization group flow for the normal-superconductor-normal junction of Luttinger liquid wires

We study the renormalization group flows of the two terminal conductance of a superconducting junction of two Luttinger liquid wires. We compute the power laws associated with the renormalization group flow around the various fixed points of this system using the generators of the SU(4) group to generate the appropriate parametrization of an matrix representing small deviations from a given fixed point matrix [obtained earlier in S. Das, S. Rao, and A. Saha, Phys. Rev. B 77, 155418 (2008)], and we then perform a comprehensive stability analysis. In particular, for the nontrivial fixed point which has intermediate values of transmission, reflection, Andreev reflection, and crossed Andreev reflection, we show that there are eleven independent directions in which the system can be perturbed, which are relevant or irrelevant, and five directions which are marginal. We obtain power laws associated with these relevant and irrelevant perturbations. Unlike the case of the two-wire charge-conserving junction, here we show that there are power laws which are nonlinear functions of V(0) and V(2kF) [where V(k) represents the Fourier transform of the interelectron interaction potential at momentum k]. We also obtain the power law dependence of linear response conductance on voltage bias or temperature around this fixed point.

Don't-cares in the concurrency matrix for bit steering

The concurrency matrix aids the detection of bit steerability of microcommand sets in a microprogram. In the present work, the concept of don't-cares is introduced into the concurrency matrix to identify the bit steerable microcommand sets.