Critical current anisotropy in high temperature superconductors

After nearly 15 years of research effort, High Temperature Superconductors (HTS) are finding a wide range of practical applications. A clear understanding of the factors controlling the current carrying capacity of these materials is a prerequisite to their successful technological development. The critical current density (Jc) in HTS is directly dependent on the structure and pinning of the Flux Line Lattice (FLL) in these materials. This thesis presents an investigation of the Jc anisotropy in HTS. The use of thin films grown on off c-axis (vicinal) substrates allowed the effect of current directions outside the cuprate planes to be studied. With this experimental geometry Berghuis, et al. (Phys. Rev. Lett. 79, 12, pg. 2332) observed a striking flux channelling effect in vicinal YBa2Cu3O7-δ (YBCO) films. By confirming, and extending, this observation, it is demonstrated that this is an intrinsic effect. The results obtained, appear to fit well with the predictions of a field angle dependent cross-over from a three dimensional rectilinear FLL to a kinked lattice of strings and pancakes. The pinning force density for movement of strings inside the cuprate planes is considerably less than that on vortex pancake elements. When the FLL is entirely string-like this reduced pinning leads to the observed channelling minima. It is observed that anti-phase boundaries enhance the Jc in vicinal YBCO films by strongly pinning vortex strings. The effect on the FLL structure cross-over of increasing anisotropy has been elucidated using de-oxygenated vicinal YBCO films. Intriguingly, the counter intuitive prediction that the range of applied field angle for which the kinked lattice is fully developed reduces with increasing anisotropy, appears to be confirmed. Although vortex channelling cannot be observed in c-axis YBCO films, the pinning force density for vortex string channelling has been extracted by observing string dragging. By studying the effect of rotating the applied field at a constant angle to the cuprate planes, it is possible to observe the cross-over into the string pancake regime in c-axis films. In the 3D region, the observed behaviour is well explained by the anisotropic Ginzburg-Landau model. Measurements were also made on thin films of the much more anisotropic Bi 2Sr2CaCu2O8+x material, grown on vicinal substrates. The absence of any flux channelling effect and clear adherence to the expected Kes-Law behaviour in the observed Jc characteristics does not provide evidence for the existence of the predicted ‘crossing lattice’ in Bi 2Sr2CaCu2O8+x .

Language model cross adaptation for LVCSR system combination

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. In normal cross adaptation it is assumed that useful diversity among systems exists only at acoustic level. However, complimentary features among complex LVCSR systems also manifest themselves in other layers of modelling hierarchy, e.g., subword and word level. It is thus interesting to also cross adapt language models (LM) to capture them. In this paper cross adaptation of multi-level LMs modelling both syllable and word sequences was investigated to improve LVCSR system combination. Significant error rate gains up to 6.7% rel. were obtained over ROVER and acoustic model only cross adaptation when combining 13 Chinese LVCSR subsystems used in the 2010 DARPA GALE evaluation. © 2010 ISCA.

Decision tree-based context clustering based on cross validation and hierarchical priors

The standard, ad-hoc stopping criteria used in decision tree-based context clustering are known to be sub-optimal and require parameters to be tuned. This paper proposes a new approach for decision tree-based context clustering based on cross validation and hierarchical priors. Combination of cross validation and hierarchical priors within decision tree-based context clustering offers better model selection and more robust parameter estimation than conventional approaches, with no tuning parameters. Experimental results on HMM-based speech synthesis show that the proposed approach achieved significant improvements in naturalness of synthesized speech over the conventional approaches. © 2011 IEEE.

Transmission performance of adaptively modulated optical OFDM modems using subcarrier modulation over SMF IMDD links for access and metropolitan area networks.

Detailed investigations are undertaken, for the first time, of the transmission performance of recently proposed novel Adaptively Modulated Optical OFDM (AMOOFDM) modems using Subcarrier Modulation (AMOOFDM-SCM) in single-channel, SMF-based IMDD links without optical amplification and chromatic dispersion compensation. The cross-talk effect induced by beatings among subcarriers of various types is a crucial factor limiting the maximum achievable AMOOFDM-SCM performance. By applying single sideband modulation and/or spectral gapping to AMOOFDM-SCM, three AMOOFDM-SCM designs of varying complexity are proposed, which achieve >60Gb/s signal transmission over 20 km, 40 km and 60 km. Such performances are >1.5 times higher than those supported by conventional AMOOFDM modems.

Unsupervised intra-lingual and cross-lingual speaker adaptation for HMM-based speech synthesis using two-pass decision tree construction

Hidden Markov model (HMM)-based speech synthesis systems possess several advantages over concatenative synthesis systems. One such advantage is the relative ease with which HMM-based systems are adapted to speakers not present in the training dataset. Speaker adaptation methods used in the field of HMM-based automatic speech recognition (ASR) are adopted for this task. In the case of unsupervised speaker adaptation, previous work has used a supplementary set of acoustic models to estimate the transcription of the adaptation data. This paper first presents an approach to the unsupervised speaker adaptation task for HMM-based speech synthesis models which avoids the need for such supplementary acoustic models. This is achieved by defining a mapping between HMM-based synthesis models and ASR-style models, via a two-pass decision tree construction process. Second, it is shown that this mapping also enables unsupervised adaptation of HMM-based speech synthesis models without the need to perform linguistic analysis of the estimated transcription of the adaptation data. Third, this paper demonstrates how this technique lends itself to the task of unsupervised cross-lingual adaptation of HMM-based speech synthesis models, and explains the advantages of such an approach. Finally, listener evaluations reveal that the proposed unsupervised adaptation methods deliver performance approaching that of supervised adaptation.

High temperature robust SOI ethanol sensor

In this paper we present a robust SOI-CMOS ethanol sensor based on a tungsten-doped lanthanum iron oxide sensing material. The device shows response to gas, has low power consumption, good uniformity, high temperature stability and can be manufactured at low cost and with integrated circuitry. The platform is a tungsten-based CMOS micro-hotplate that has been shown to be stable for over two thousand hours at a high temperature (600°C) in a form of accelerated life test. The tungsten-doped lanthanum iron oxide was deposited on the micro-hotplate as a slurry with terpineol using a syringe, dried and annealed. Preliminary gas testing was done and the material shows response to ethanol vapour. These results are promising and we believe that this combination of a robust CMOS micro-hotplate and a good sensing material can form the basis for a commercial CMOS gas sensor. © 2011 Published by Elsevier Ltd.

Cold-gas chemical vapor deposition to identify the key precursor for rapidly growing vertically-aligned single-wall and few-wall carbon nanotubes from pyrolyzed ethanol

Vertically-aligned carbon nanotubes (VA-CNTs) were rapidly grown from ethanol and their chemistry has been studied using a "cold-gas" chemical vapor deposition (CVD) method. Ethanol vapor was preheated in a furnace, cooled down and then flowed over cobalt catalysts upon ribbon-shaped substrates at 800 °C, while keeping the gas unheated. CNTs were obtained from ethanol on a sub-micrometer scale without preheating, but on a millimeter scale with preheating at 1000 °C. Acetylene was predicted to be the direct precursor by gas chromatography and gas-phase kinetic simulation, and actually led to millimeter-tall VA-CNTs without preheating when fed with hydrogen and water. There was, however a difference in CNT structure, i.e. mainly few-wall tubes from pyrolyzed ethanol and mainly single-wall tubes for unheated acetylene, and the by-products from ethanol pyrolysis possibly caused this difference. The "cold-gas" CVD, in which the gas-phase and catalytic reactions are separately controlled, allowed us to further understand CNT growth. © 2012 Elsevier Ltd. All rights reserved.

Use of wavefront encoding in optical interconnects and fiber switches for cross talk mitigation

A technique of cross talk mitigation developed for liquid crystal on silicon spatial light modulator based optical interconnects and fiber switches is demonstrated. By purposefully introducing an appropriate aberration into the system, it is possible to reduce the worst-case cross talk by over 10 dB compared to conventional Fourier-transform-based designs. Tests at a wavelength of 674nm validate this approach, and show that there is no noticeable reduction in diffraction efficiency. A 27% spot increase in beam diameter is observed, which is predicted to reduce at longer datacom and telecom wavelengths. © 2012 Optical Society of America.

Improving LVCSR system combination using neural network language model cross adaptation

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. The standard approach involves only cross adapting acoustic models. To fully exploit the complimentary features among sub-systems, language model (LM) cross adaptation techniques can be used. Previous research on multi-level n-gram LM cross adaptation is extended to further include the cross adaptation of neural network LMs in this paper. Using this improved LM cross adaptation framework, significant error rate gains of 4.0%-7.1% relative were obtained over acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. Copyright © 2011 ISCA.

Language model cross adaptation for LVCSR system combination

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple sub-systems that may even be developed at different sites. Cross system adaptation, in which model adaptation is performed using the outputs from another sub-system, can be used as an alternative to hypothesis level combination schemes such as ROVER. Normally cross adaptation is only performed on the acoustic models. However, there are many other levels in LVCSR systems' modelling hierarchy where complimentary features may be exploited, for example, the sub-word and the word level, to further improve cross adaptation based system combination. It is thus interesting to also cross adapt language models (LMs) to capture these additional useful features. In this paper cross adaptation is applied to three forms of language models, a multi-level LM that models both syllable and word sequences, a word level neural network LM, and the linear combination of the two. Significant error rate reductions of 4.0-7.1% relative were obtained over ROVER and acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. © 2012 Elsevier Ltd. All rights reserved.

Effects of ethanol on vehicle energy efficiency and implications on ethanol life-cycle greenhouse gas analysis.

Bioethanol is the world's largest-produced alternative to petroleum-derived transportation fuels due to its compatibility within existing spark-ignition engines and its relatively mature production technology. Despite its success, questions remain over the greenhouse gas (GHG) implications of fuel ethanol use with many studies showing significant impacts of differences in land use, feedstock, and refinery operation. While most efforts to quantify life-cycle GHG impacts have focused on the production stage, a few recent studies have acknowledged the effect of ethanol on engine performance and incorporated these effects into the fuel life cycle. These studies have broadly asserted that vehicle efficiency increases with ethanol use to justify reducing the GHG impact of ethanol. These results seem to conflict with the general notion that ethanol decreases the fuel efficiency (or increases the fuel consumption) of vehicles due to the lower volumetric energy content of ethanol when compared to gasoline. Here we argue that due to the increased emphasis on alternative fuels with drastically differing energy densities, vehicle efficiency should be evaluated based on energy rather than volume. When done so, we show that efficiency of existing vehicles can be affected by ethanol content, but these impacts can serve to have both positive and negative effects and are highly uncertain (ranging from -15% to +24%). As a result, uncertainties in the net GHG effect of ethanol, particularly when used in a low-level blend with gasoline, are considerably larger than previously estimated (standard deviations increase by >10% and >200% when used in high and low blends, respectively). Technical options exist to improve vehicle efficiency through smarter use of ethanol though changes to the vehicle fleets and fuel infrastructure would be required. Future biofuel policies should promote synergies between the vehicle and fuel industries in order to maximize the society-wise benefits or minimize the risks of adverse impacts of ethanol.

Kelvin-Helmholtz-like instability of turbulent flows over riblets

The turbulent drag reduction due to riblets is a function of their size and, for different configurations, collapses well with a length scale l+g=(A+g)1/2, based in the groove cross-section Ag. The initially linear drag reduction breaks down for l+g≈11, which agrees in our DNS with the previously reported appearance of quasi-two-dimensional spanwise rollers immediately above the riblets. They are similar to those found over porous surfaces and plant canopies, and can be traced to a Kelvin-Helmholtz-like instability associated with the relaxation of the impermeability condition for the wall-normal velocity. The extra Reynolds stress associated with them accounts quantitatively for the drag degradation. An inviscid model for the instability confirms its nature, agreeing well with the observed perturbation wavelengths and shapes. The onset of the instability is determined by a length scale L+w that, for conventional riblet geometries, is proportional to l+g. The instability onset, L+w≥4, corresponds to the empirical breakdown point l+g≈11.

The forming of variable cross-section I-beams by hot rolling

A process is presented for the forming of variable cross-section I-beams by hot rolling. Optimized I-beams with variable cross-section offer a significant weight advantage over prismatic beams. By tailoring the cross-section to the bending moment experienced within the beam, around 30% of the material can be saved compared to a standard section. Production of such beams by hot rolling would be advantageous, as It combines high volume capacity with high material yields. Through controlled variation of the roll gap during multiple passes, beams with a variable cross-section have been created using shaped rolls similar to those used for conventional I-beam rolling. The process was tested experimentally on a small scale rolling mill, using plasticine as the modelling material. These results were then compared to finite element simulations of individual stages of the process conducted using Abaqus/Standard. Results here show that the process can successfully form a beam with a variable depth web. The main failure modes of the process, and the limitations on the achievable variations In geometry are also presented. Finally, the question of whether or not optimal beam geometries can be created by this process Is discussed. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Weinheim.