Study of Microstructure Evolution during Semi-Solid Processing of an In-Situ Al Alloy Composite

In the present work, effect of pouring temperature (650 degrees C, 655 degrees C, and 660 degrees C) on semi-solid microstructure evolution of in-situ magnesium silicide (Mg2Si) reinforced aluminum (Al) alloy composite has been studied. The shear force exerted by the cooling slope during gravity driven flow of the melt facilitates the formation of near spherical primary Mg2Si and primary Al grains. Shear driven melt flow along the cooling slope and grain fragmentation have been identified as the responsible mechanisms for refinement of primary Mg2Si and Al grains with improved sphericity. Results show that, while flowing down the cooling slope, morphology of primary Mg2Si and primary Al transformed gradually from coarse dendritic to mixture of near spherical particles, rosettes, and degenerated dendrites. In terms of minimum grain size and maximum sphericity, 650 degrees C has been identified as the ideal pouring temperature for the cooling slope semi-solid processing of present Al alloy composite. Formation of spheroidal grains with homogeneous distribution of reinforcing phase (Mg2Si) improves the isotropic property of the said composite, which is desirable in most of the engineering applications.

High-Temperature Deformation Processing Map Approach for Obtaining the Desired Microstructure in a Multi-component (Ni-Ti-Cu-Fe) Alloy

An equiatomic NiTiCuFe multi-component alloy with simple body-centered cubic (bcc) and face-centered cubic solid-solution phases in the microstructure was processed by vacuum induction melting furnace under dynamic Ar atmosphere. High-temperature uniaxial compression experiments were conducted on it in the temperature range of 1073 K to 1303 K (800 degrees C to 1030 degrees C) and strain rate range of 10(-3) to 10(-1) s(-1). The data generated were analyzed with the aid of the dynamic materials model through which power dissipation efficiency and instability maps were generated so as to identify the governing deformation mechanisms that are operative in different temperature-strain rate regimes with the aid of complementary microstructural analysis of the deformed specimens. Results indicate that the stable domain for the high temperature deformation of the multi-component alloy occurs in the temperature range of 1173 K to 1303 K (900 degrees C to 1030 degrees C) and (epsilon) over dot range of 10(-3) to 10(-1.2) s(-1), and the deformation is unstable at T = 1073 K to 1153 K (800 degrees C to 880 degrees C) and (epsilon) over dot = 10(-3) to 10(-1.4) s(-1) as well as T = 1223 K to 1293 K (950 degrees C to 1020 degrees C) and (epsilon) over dot = 10(-1.4) to 10(-1) s(-1), with adiabatic shear banding, localized plastic flow, or cracking being the unstable mechanisms. A constitutive equation that describes the flow stress of NiTiCuFe multi-component alloy as a function of strain rate and deformation temperature was also determined. (C) The Minerals, Metals & Materials Society and ASM International 2015

Microstructure and Crystallographic Texture Evolution During the Friction-Stir Processing of a Precipitation-Hardenable Aluminum Alloy

Friction-stir processing (FSP) has been proven as a successful method for the grain refinement of high-strength aluminum alloys. The most important attributes of this process are the fine-grain microstructure and characteristic texture, which impart suitable properties in the as-processed material. In the current work, FSP of the precipitation-hardenable aluminum alloy 2219 has been carried out and the consequent evolution of microstructure and texture has been studied. The as-processed materials were characterized using electron back-scattered diffraction, x-ray diffraction, and electron probe microanalysis. Onion-ring formation was observed in the nugget zone, which has been found to be related to the precipitation response and crystallographic texture of the alloy. Texture development in the alloy has been attributed to the combined effect of shear deformation and dynamic recrystallization. The texture was found heterogeneous even within the nugget zone. A microtexture analysis revealed the dominance of shear texture components, with C component at the top of nugget zone and the B and A(2)* components in the middle and bottom. The bulk texture measurement in the nugget zone revealed a dominant C component. The development of a weaker texture along with the presence of some large particles in the nugget zone indicates particle-stimulated nucleation as the dominant nucleation mechanism during FSP. Grain growth follows the Burke and Turnbull mechanism and geometrical coalescence.

Production and characterization of bioflocculants for mineral processing applications

A comparative study of two bacterial strains namely, Bacillus licheniformis and Bacillus firmus in the production of bioflocculants was made. The highest bioflocculant yield of 16.55 g/L was obtained from B. licheniformis (L) and 10 g/L from B. firmus (F). The bioflocculants obtained from the bacterial species were water soluble and insoluble in organic solvents. FTIR spectral analysis revealed the presence of hydroxyl, carboxyl and sugar derivatives in the bioflocculants. Thermal characterization by differential scanning calorimetry (DSC) showed the crystalline transition and the melting point (T-m) at 90-100 degrees C. Effects of bioflocculant dosage and pH on the flocculation of clay fines were evaluated. Highest bioflocculation efficiency on kaolin clay suspensions was observed at an optimum bioflocculant dosage of 5 g/L. The optimum pH range for the maximum bioflocculation was at pH 7-9. Bioflocculants exhibited high efficiency in dye decolorization. The maximum Cr (VI) removal was found to be 85 % for L (bioflocculant dosage at 2 g/L). This study demonstrates that microbial bioflocculants find potential applications in mineral processing such as selective flocculation of mineral fines, decolorization of dye solutions and in the remediation of toxic metal solutions. (C) 2015 Elsevier B.V. All rights reserved.

Restoration Mechanisms During the Friction Stir Processing of Aluminum Alloys

In the current study, correlation of microstructure evolution with bulk crystallographic texture formation during friction stir processing (FSP) of commercial aluminum alloys has been attempted. Electron back-scattered diffraction and X-ray diffraction techniques were employed for characterizing the nugget zone of optimum friction stir processed samples. Volume fraction of measured texture components revealed that the texture formation in aluminum alloys is similar irrespective of the alloy composition. Recrystallization behavior during FSP was more of a composition dependent phenomenon.

Oriented nanometric aggregates of partially inverted zinc ferrite: One-step processing and tunable high-frequency magnetic properties

In this work, it is demonstrated that the in situ growth of oriented nanometric aggregates of partially inverted zinc ferrite can potentially pave a way to alter and tune magnetocrystalline anisotropy that, in turn, dictates ferromagnetic resonance frequency (f(FMR)) by inducing strain due to aggregation. Furthermore, the influence of interparticle interaction on magnetic properties of the aggregates is investigated. Mono-dispersed zinc ferrite nanoparticles (<5 nm) with various degrees of aggregation were prepared through decomposition of metal-organic compounds of zinc (II) and iron (III) in an alcoholic solution under controlled microwave irradiation, below 200 degrees C. The nanocrystallites were found to possess high degree of inversion (>0.5). With increasing order of aggregation in the samples, saturation magnetization (at 5 K) is found to decrease from 38 emu/g to 24 emu/g, while coercivity is found to increase gradually by up to 100% (525 Oe to 1040 Oe). Anisotropy-mediated shift of f(FMR) has also been measured and discussed. In essence, the result exhibits an easy way to control the magnetic characteristics of nanocrystalline zinc ferrite, boosted with significant degree of inversion, at GHz frequencies. (C) 2015 AIP Publishing LLC.

Robust Whisper Activity Detection Using Long-Term Log Energy Variation of Sub-Band Signal

The goal in the whisper activity detection (WAD) is to find the whispered speech segments in a given noisy recording of whispered speech. Since whispering lacks the periodic glottal excitation, it resembles an unvoiced speech. This noise-like nature of the whispered speech makes WAD a more challenging task compared to a typical voice activity detection (VAD) problem. In this paper, we propose a feature based on the long term variation of the logarithm of the short-time sub-band signal energy for WAD. We also propose an automatic sub-band selection algorithm to maximally discriminate noisy whisper from noise. Experiments with eight noise types in four different signal-to-noise ratio (SNR) conditions show that, for most of the noises, the performance of the proposed WAD scheme is significantly better than that of the existing VAD schemes and whisper detection schemes when used for WAD.

Effect of processing route on phase stability in equiatomic multicomponent Ti20Fe20Ni20Co20Cu20 high entropy alloy

The evolution of microstructure and phase formation in equiatomic Ti20Fe20Ni20Co20Cu20 high entropy alloy synthesised by conventional arc melting followed with suction casting and ball milling with spark plasma sintering route is distinctly different. The cast microstructure exhibits one body centre cubic and two face centre cubic high entropy phases based on titanium, cobalt and copper respectively along with a eutectic containing Ti2Ni type Laves phase. On the contrary, spinodal decomposed microstructure consisting of cobalt and copper solid solution is obtained in the sintered sample. However, long term annealing of cast sample at 950 degrees C reveals a eutectoid transformation with different phases than the cast sample. The aforementioned observations are discussed using CALPHAD thermodynamical approach and available literature.

Processing of EEG Signals for Study of Coupling in Brain Regions for Eyes Open and Eyes Closed Conditions

This paper deals with processing the EEG signals obtained from 16 spatially arranged electrodes to measure coupling or synchrony between the frontal, parietal, occipital and temporal lobes of the cerebrum under the eyes open and eyes closed conditions. This synchrony was measured using magnitude squared coherence, Short Time Fourier Transform and wavelet based coherences. We found a pattern in the time-frequency coherence as we moved from the nasion to the inion of the subject's head. The coherence pattern obtained from the wavelet approach was found to be far more capable of picking up peaks in coherence with respect to frequency when compared to the regular Fourier based coherence. We detected high synchrony between frontal polar electrodes that is missing in coherence plots between other electrode pairs. The study has potential applications in healthcare.

A novel in-situ polymer derived nano ceramic MMC by friction stir processing

Fiction stir processing (FSP) is a solid state technique used for material processing. Tool wear and the agglomeration of ceramic particles have been serious issues in FSP of metal matrix composites. In the present study, FSP has been employed to disperse the nanoscale particles of a polymer-derived silicon carbonitride (SiCN) ceramic phase into copper by an in-situ process. SiCN cross linked polymer particles were incorporated using multi-pass ESP into pure copper to form bulk particulate metal matrix composites. The polymer was then converted into ceramic through an in-situ pyrolysis process and dispersed by ESP. Multi-pass processing was carried out to remove porosity from the samples and also for the uniform dispersion of polymer derived ceramic particles. Microstructural observations were carried out using Field Emission Scanning Electron Microscopy (FE-SEM) and Transmission Electron Microscopy (TEM) of the composite. The results indicate a uniform distribution of similar to 100 nm size particles of the ceramic phase in the copper matrix after ESP. The nanocomposite exhibits a five fold increase in microhardness (260HV(100)) which is attributed to the nano scale dispersion of ceramic particles. A mechanism has been proposed for the fracturing of PDC particles during multi pass FSP. (C) 2015 Elsevier Ltd. All rights reserved

Ancilla-assisted measurements on quantum ensembles: general protocols and applications in NMR quantum information processing

Quantum ensembles form easily accessible architectures for studying various phenomena in quantum physics, quantum information science and spectroscopy. Here we review some recent protocols for measurements in quantum ensembles by utilizing ancillary systems. We also illustrate these protocols experimentally via nuclear magnetic resonance techniques. In particular, we shall review noninvasive measurements, extracting expectation values of various operators, characterizations of quantum states and quantum processes, and finally quantum noise engineering.

Speaker verification based on the fusion of speech acoustics and inverted articulatory signals

We propose apractical, feature-level and score-level fusion approach by combining acoustic and estimated articulatory information for both text independent and text dependent speaker verification. From a practical point of view, we study how to improve speaker verification performance by combining dynamic articulatory information with the conventional acoustic features. On text independent speaker verification, we find that concatenating articulatory features obtained from measured speech production data with conventional Mel-frequency cepstral coefficients (MFCCs) improves the performance dramatically. However, since directly measuring articulatory data is not feasible in many real world applications, we also experiment with estimated articulatory features obtained through acoustic-to-articulatory inversion. We explore both feature level and score level fusion methods and find that the overall system performance is significantly enhanced even with estimated articulatory features. Such a performance boost could be due to the inter-speaker variation information embedded in the estimated articulatory features. Since the dynamics of articulation contain important information, we included inverted articulatory trajectories in text dependent speaker verification. We demonstrate that the articulatory constraints introduced by inverted articulatory features help to reject wrong password trials and improve the performance after score level fusion. We evaluate the proposed methods on the X-ray Microbeam database and the RSR 2015 database, respectively, for the aforementioned two tasks. Experimental results show that we achieve more than 15% relative equal error rate reduction for both speaker verification tasks. (C) 2015 Elsevier Ltd. All rights reserved.

MULTI-INSTRUMENT DETECTION IN POLYPHONIC MUSIC USING GAUSSIAN MIXTURE BASED FACTORIAL HMM

We formulate the problem of detecting the constituent instruments in a polyphonic music piece as a joint decoding problem. From monophonic data, parametric Gaussian Mixture Hidden Markov Models (GM-HMM) are obtained for each instrument. We propose a method to use the above models in a factorial framework, termed as Factorial GM-HMM (F-GM-HMM). The states are jointly inferred to explain the evolution of each instrument in the mixture observation sequence. The dependencies are decoupled using variational inference technique. We show that the joint time evolution of all instruments' states can be captured using F-GM-HMM. We compare performance of proposed method with that of Student's-t mixture model (tMM) and GM-HMM in an existing latent variable framework. Experiments on two to five polyphony with 8 instrument models trained on the RWC dataset, tested on RWC and TRIOS datasets show that F-GM-HMM gives an advantage over the other considered models in segments containing co-occurring instruments.

Dictionary-Learning-Based Post-Filter for HMM-Based Speech Synthesis

Oversmoothing of speech parameter trajectories is one of the causes for quality degradation of HMM-based speech synthesis. Various methods have been proposed to overcome this effect, the most recent ones being global variance (GV) and modulation-spectrum-based post-filter (MSPF). However, there is still a significant quality gap between natural and synthesized speech. In this paper, we propose a two-fold post-filtering technique to alleviate to a certain extent the oversmoothing of spectral and excitation parameter trajectories of HMM-based speech synthesis. For the spectral parameters, we propose a sparse coding-based post-filter to match the trajectories of synthetic speech to that of natural speech, and for the excitation trajectory, we introduce a perceptually motivated post-filter. Experimental evaluations show quality improvement compared with existing methods.

SPEECH ENHANCEMENT USING DISCRIMINATIVE RANDOM FIELDS

Speech enhancement in stationary noise is addressed using the ideal channel selection framework. In order to estimate the binary mask, we propose to classify each time-frequency (T-F) bin of the noisy signal as speech or noise using Discriminative Random Fields (DRF). The DRF function contains two terms - an enhancement function and a smoothing term. On each T-F bin, we propose to use an enhancement function based on likelihood ratio test for speech presence, while Ising model is used as smoothing function for spectro-temporal continuity in the estimated binary mask. The effect of the smoothing function over successive iterations is found to reduce musical noise as opposed to using only enhancement function. The binary mask is inferred from the noisy signal using Iterated Conditional Modes (ICM) algorithm. Sentences from NOIZEUS corpus are evaluated from 0 dB to 15 dB Signal to Noise Ratio (SNR) in 4 kinds of additive noise settings: additive white Gaussian noise, car noise, street noise and pink noise. The reconstructed speech using the proposed technique is evaluated in terms of average segmental SNR, Perceptual Evaluation of Speech Quality (PESQ) and Mean opinion Score (MOS).