RF plasma enhanced MOCVD of yttria stabilized zirconia thin films using octanedionate precursors and their characterization

Yttria stabilized zirconia thin films have been deposited by RF plasma enhanced MOCVD technique on silicon substrates at substrate temperature of 400 degrees C. Plasma of precursor vapors of (2,7,7-trimethyl-3,5-octanedionate) yttrium (known as Y(tod)(3)), (2,7,7-trimethyl-3,5-octanedionate) zirconium (known as Zr(tod)(4)), oxygen and argon gases is used for deposition. To the best of our knowledge, plasma assisted MOCVD of YSZ films using octanediaonate precursors have not been reported in the literature so far. The deposited films have been characterized by GIXRD, FTIR, XPS, FESEM, AFM, XANES, EXAFS, EDAX and spectroscopic ellipsometry. Thickness of the films has been measured by stylus profilometer while tribological property measurement has been done to study mechanical behavior of the coatings. Characterization by different techniques indicates that properties of the films are dependent on the yttria content as well as on the structure of the films. (C) 2015 Elsevier B.V. All rights reserved.

Gold catalyzed intramolecular hydroalkoxylation assisted ring opening of furans to the corresponding saturated gamma-keto esters

A facile ring opening of furans in furyl propargyl alcohols to the corresponding saturated gamma-keto esters is observed in the gold(III) chloride catalyzed reaction with MeOH. It is found that the ring opening of furan is driven by the intramolecular hydroalkoxylation. Mitigating the intramolecular hydroalkoxylation led to the expected conjugated enyne resulting from the dehydration. (C) 2015 Elsevier Ltd. All rights reserved.

Detection and estimation of liquid flow through a pipe in a tissue-like object with ultrasound-assisted diffuse correlation spectroscopy

Using coherent light interrogating a turbid object perturbed by a focused ultrasound (US) beam, we demonstrate localized measurement of dynamics in the focal region, termed the region-of-interest (ROI), from the decay of the modulation in intensity autocorrelation of light. When the ROI contains a pipe flow, the decay is shown to be sensitive to the average flow velocity from which the mean-squared displacement (MSD) of the scattering centers in the flow can be estimated. While the MSD estimated is seen to be an order of magnitude higher than that obtainable through the usual diffusing wave spectroscopy (DWS) without the US, it is seen to be more accurate as verified by the volume flow estimated from it. It is further observed that, whereas the MSD from the localized measurement grows with time as tau(alpha) with alpha approximate to 1.65, without using the US, a is seen to be much less. Moreover, with the local measurement, this super-diffusive nature of the pipe flow is seen to persist longer, i.e., over a wider range of initial tau, than with the unassisted DWS. The reason for the super-diffusivity of flow, i.e., alpha < 2, in the ROI is the presence of a fluctuating (thermodynamically nonequilibrium) component in the dynamics induced by the US forcing. Beyond this initial range, both methods measure MSDs that rise linearly with time, indicating that ballistic and near-ballistic photons hardly capture anything beyond the background Brownian motion. (C) 2015 Optical Society of America

A survey on compressed domain video analysis techniques

Image and video analysis requires rich features that can characterize various aspects of visual information. These rich features are typically extracted from the pixel values of the images and videos, which require huge amount of computation and seldom useful for real-time analysis. On the contrary, the compressed domain analysis offers relevant information pertaining to the visual content in the form of transform coefficients, motion vectors, quantization steps, coded block patterns with minimal computational burden. The quantum of work done in compressed domain is relatively much less compared to pixel domain. This paper aims to survey various video analysis efforts published during the last decade across the spectrum of video compression standards. In this survey, we have included only the analysis part, excluding the processing aspect of compressed domain. This analysis spans through various computer vision applications such as moving object segmentation, human action recognition, indexing, retrieval, face detection, video classification and object tracking in compressed videos.

No More HF: Teflon-Assisted Ultrafast Removal of Silica to Generate High-Surface-Area Mesostructured Carbon for Enhanced CO2 Capture and Supercapacitor Performance

An innovative technique to obtain high-surface-area mesostructured carbon (2545m(2)g(-1)) with significant microporosity uses Teflon as the silica template removal agent. This method not only shortens synthesis time by combining silica removal and carbonization in a single step, but also assists in ultrafast removal of the template (in 10min) with complete elimination of toxic HF usage. The obtained carbon material (JNC-1) displays excellent CO2 capture ability (ca. 26.2wt% at 0 degrees C under 0.88bar CO2 pressure), which is twice that of CMK-3 obtained by the HF etching method (13.0wt%). JNC-1 demonstrated higher H-2 adsorption capacity (2.8wt%) compared to CMK-3 (1.2wt%) at -196 degrees C under 1.0bar H-2 pressure. The bimodal pore architecture of JNC-1 led to superior supercapacitor performance, with a specific capacitance of 292Fg(-1) and 182Fg(-1) at a drain rate of 1Ag(-1) and 50Ag(-1), respectively, in 1m H2SO4 compared to CMK-3 and activated carbon.

No More HF: Teflon-Assisted Ultrafast Removal of Silica to Generate High-Surface-Area Mesostructured Carbon for Enhanced CO2 Capture and Supercapacitor Performance

An innovative technique to obtain high-surface-area mesostructured carbon (2545m(2)g(-1)) with significant microporosity uses Teflon as the silica template removal agent. This method not only shortens synthesis time by combining silica removal and carbonization in a single step, but also assists in ultrafast removal of the template (in 10min) with complete elimination of toxic HF usage. The obtained carbon material (JNC-1) displays excellent CO2 capture ability (ca. 26.2wt% at 0 degrees C under 0.88bar CO2 pressure), which is twice that of CMK-3 obtained by the HF etching method (13.0wt%). JNC-1 demonstrated higher H-2 adsorption capacity (2.8wt%) compared to CMK-3 (1.2wt%) at -196 degrees C under 1.0bar H-2 pressure. The bimodal pore architecture of JNC-1 led to superior supercapacitor performance, with a specific capacitance of 292Fg(-1) and 182Fg(-1) at a drain rate of 1Ag(-1) and 50Ag(-1), respectively, in 1m H2SO4 compared to CMK-3 and activated carbon.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

Structural, Optical, and Piezoelectric Response of Lead-Free Ba0.95Mg0.05Zr0.1Ti0.9O3 Nanocrystalline Powder

Nanocrystalline powders of Ba1-xMgxZr0.1Ti0.9O3 (x = 0.025-0.1) were synthesized via citrate assisted sol-gel method. Interestingly, the one with x = 0.05 in the system Ba1-xMgxZr0.1Ti0.9O3 exhibited fairly good piezoelectric response aside from the other physical properties. The phase and structural confirmation of synthesized powder was established by X-ray powder diffraction (XRD) and Raman Spectroscopic techniques. Two distinct Raman bands i.e., 303 and 723 cm(-1) characteristic of tetragonal phase were observed. Thermogravimetric analysis (TGA) was performed to evaluate the phase decomposition of the as-synthesized Ba0.95Mg0.05Zr0.1Ti0.9O3 sample as a function of temperature. The average crystallite size associated with Ba0.95Mg0.05Zr0.1Ti0.9O3 was calculated using Scherrer formula based on the XRD data and was found to be 25 nm. However, Scanning and Transmission Electron Microscopy studies revealed the average crystallite size to be in the range of 30-40 nm, respectively. Kubelka-Munk function was employed to determine the optical band gap of these nanocrystallites. A piezoelectric response of 26 pm/V was observed for Ba0.95Mg0.05Zr0.1Ti0.9O3 nanocrystal by Piezoresponse Force Microscopy (PFM) technique. Photoluminescence (PL) study carried out on these nanocrystals exhibited a blue emission (470 nm) at room temperature.

Nitrogen-assisted electroless assembling of 3D nanodendrites consisting of Pd and N-doped carbon nanoparticles as bifunctional catalysts

We report a facile synthesis of three-dimensional (3D) nanodendrites of Pd nanoparticles (NPs) and nitrogen-doped carbon NPs (N-CNPs) by electroless deposition of Pd2+ ions. N-CNPs being an electron-enriched material act as a reducing agent. Moreover, the availability of a variety of nitrogen species in N-CNPs promotes the open arm structure as well as stabilizes the oriented 3D assembly of primary Pd NPs. The dendrites exhibit superior catalytic activity for methanol (0.5 M) oxidation in alkaline media (1 M NaOH) which is ascribed to the large electrochemical active surface area and the enhanced mass activity with repeated use. Further mass activity improvement has been realized after acid-treatment of dendrites which is attributed to the increment in the -OH group. The dendrites show higher mass activity (J(f) similar to 653 A g(-1)) in comparison with a commercial Pt-carbon/Pd-carbon (Pt-C/Pd-C) catalyst (J(f) similar to 46 and 163 A g(-1), respectively), better operational stability, superior CO tolerance with I-f/I-b (similar to 3.7) over a commercial Pt-C/Pd-C catalyst (I-f/I-b similar to 1.6 and 1.75, respectively) and may serve as a promising alternative to commercial Pt-C catalysts for anode application in alkaline fuel cells. To ensure the adaptability of our 3D-nanodendrites for other catalytic activities, we studied 4-nitrophenol reduction at room temperature. The 3D-nanodendrites show excellent catalytic activity toward 4-nitrophenol reduction, as well.

A mode-shape classification technique for robust speech rate estimation and syllable nuclei detection

Acoustic feature based speech (syllable) rate estimation and syllable nuclei detection are important problems in automatic speech recognition (ASR), computer assisted language learning (CALL) and fluency analysis. A typical solution for both the problems consists of two stages. The first stage involves computing a short-time feature contour such that most of the peaks of the contour correspond to the syllabic nuclei. In the second stage, the peaks corresponding to the syllable nuclei are detected. In this work, instead of the peak detection, we perform a mode-shape classification, which is formulated as a supervised binary classification problem - mode-shapes representing the syllabic nuclei as one class and remaining as the other. We use the temporal correlation and selected sub-band correlation (TCSSBC) feature contour and the mode-shapes in the TCSSBC feature contour are converted into a set of feature vectors using an interpolation technique. A support vector machine classifier is used for the classification. Experiments are performed separately using Switchboard, TIMIT and CTIMIT corpora in a five-fold cross validation setup. The average correlation coefficients for the syllable rate estimation turn out to be 0.6761, 0.6928 and 0.3604 for three corpora respectively, which outperform those obtained by the best of the existing peak detection techniques. Similarly, the average F-scores (syllable level) for the syllable nuclei detection are 0.8917, 0.8200 and 0.7637 for three corpora respectively. (C) 2016 Elsevier B.V. All rights reserved.