Catalytic combustion over platinum group catalysts: fuel-lean versus fuel-rich operation

Performance data are presented for methane oxidation on alumina-supported Pd, Pt, and Rh catalysts under both fuel-rich and fuel-lean conditions. Catalyst activity was measured in a micro-scale isothermal reactor at temperatures between 300 and 800 °C. Non-isothermal (near adiabatic) temperature and reaction data were obtained in a full-length (non-differential) sub-scale reactor operating at high pressure (0.9 MPa) and constant inlet temperature, simulating actual reactor operation in catalytic combustion applications.

Under fuel-lean conditions, Pd catalyst was the most active, although deactivation occurred above 650 °C, with reactivation upon cooling. Rh catalyst also deactivated above 750 °C, but did not reactivate. Pt catalyst was active above 600 °C. Fuel-lean reaction products were CO₂ and H₂O for all three catalysts.

The same catalysts tested under fuel-rich conditions demonstrated much higher activity. In addition, a ‘lightoff’ temperature was found (between 450 and 600 °C), where a stepwise increase in reaction rate was observed. Following ‘lightoff’ partial oxidation products (CO, H₂) appeared in the mixture, and their concentration increased with increasing temperature. All three catalysts exhibited this behavior.

High-pressure (0.9 MPa) sub-scale reactor and combustor data are shown, demonstrating the benefits of fuel-rich operation over the catalyst for ultra-low emissions combustion.     

Characterization of mixed-phase BN thin films deposited by plasma CVD

Boron nitride thin films have been deposited by plasma assisted chemical vapour deposition (PACVD) from non-toxic material and have been shown to have a high content of the cubic phase under certain conditions of substrate temperature and r.f. power, as measured by infrared absorption and refractive index. The electronic properties of these films have been measured and exhibited high resistivity and breakdown field strength. Al/BN/n-Si MIS diodes have been constructed and these show that the BN insulator contains negative charges. The interface state density is relatively low, however, and there is no Fermi level pinning within the bandgap     

Thin‐film encapsulated white organic light top‐emitting diodes using a WO3/Ag/WO3 cathode to enhance light out‐coupling

An alternative design of a semitransparent cathode for top‐emission white‐fluorescent organic light‐emitting diodes (OLEDs) has been investigated. The scope of this study was to improve the luminance of OLEDs used for displays while keeping the current density versus voltage characteristic unchanged for addressing purposes. The use of an optical simulation tool allowed the optimization of the tri‐layer cathode WO₃/Ag/WO₃ to increase the light out‐coupling coefficient of the device leading to an increased white emission compared with a reference device with a Ca/Ag cathode. An increase of ~40% in luminance has been calculated by simulation and experimentally confirmed. The p‐i‐n OLED structure underneath the tri‐layer cathode allowed an efficient injection of electrons independently from the work function of WO₃. The WO₃/Ag/WO₃ cathode has been also confirmed to be compatible with the atomic layer deposition technique for thin film encapsulation. Finally, lifetime measurements up to 600 h have been carried out to quantify the enhancements induced by the new cathode compared with the control device. It has been found that lifetimes of both cathode architectures are similar on this time scale, while the WO₃/Ag/WO₃ cathode shows a lower voltage drift versus aging.     

Multi-objective topology optimization of multi-component continuum structures via a Kriging-interpolated level set approach

This paper explores a framework for topology optimization of multi-component sheet metal structures, such as those often used in the automotive industry. The primary reason for having multiple components in a structure is to reduce the manufacturing cost, which can become prohibitively expensive otherwise. Having a multi-component structure necessitates re-joining, which often comes at sacrifices in the assembly cost, weight and structural performance. The problem of designing a multi-component structure is thus posed in a multi-objective framework. Approaches to solve the problem may be classified into single and two stage approaches. Two-stage approaches start by focusing solely on structural performance in order to obtain optimal monolithic (single piece) designs, and then the decomposition into multiple components is considered without changing the base topology (identical to the monolithic design). Single-stage approaches simultaneously attempt to optimize both the base topology and its decomposition. Decomposition is an inherently discrete problem, and as such, non-gradient methods are needed for single-stage and second stage of two-stage approaches. This paper adopts an implicit formulation (level-sets) of the design variables, which significantly reduces the number of design variables needed in either single or two stage approaches. The number of design variables in the formulation is independent from the meshing size, which enables application of non-gradient methods to realistic designs. Test results of a short cantilever and an L-shaped bracket studies show reasonable success of both single and two stage approaches, with each approach having different merits.     

Agent societies and social networks for ubiquitous computing

In ubiquitous computing environments, providing appropriate services and information to users at the right place in the right way is challenging for many reasons: different user interests, heterogeneous devices and services, dynamic networks, information overload, or differing privacy levels, for example. Agent technology is a paradigm expected to play an increasing role in complex computing environments, and due to the increasing popularity of social networking services, we expect to see the convergence of agent and social web technologies. The goal of this theme issue is to bring together state-of-the-art research contributions that examine the convergence of agent technologies and social networks for ubiquitous computing.     

Predicting defect-prone software modules using support vector machines

Effective prediction of defect-prone software modules can enable software developers to focus quality assurance activities and allocate effort and resources more efficiently. Support vector machines (SVM) have been successfully applied for solving both classification and regression problems in many applications. This paper evaluates the capability of SVM in predicting defect-prone software modules and compares its prediction performance against eight statistical and machine learning models in the context of four NASA datasets. The results indicate that the prediction performance of SVM is generally better than, or at least, is competitive against the compared models.     

Dynamic Hotlinks

Consider a directed rooted tree T=(V,E) representing a collection V of n web pages connected via a set E of links all reachable from a source home page, represented by the root of T. Each web page i carries a weight w _i representative of the frequency with which it is visited. By adding hotlinks, shortcuts from a node to one of its descendants, we are interested in minimizing the expected number of steps needed to visit pages from the home page. We give the first linear time algorithm for assigning hotlinks so that the number of steps to access a page i from the root of the tree reaches the entropy bound, i.e. is at most O(log (W/w _i )) where W=∑ _i∈T w _i . The best previously known algorithm for this task runs in time O(n ²). We also give the first efficient data structure for maintaining hotlinks when nodes are added, deleted or their weights modified, in amortized time O(log (W/w _i )) per update. The data structure can be made adaptive, i.e. reaches the entropy bound in the amortized sense without knowing the weights w _i in advance.     

Cytotoxicity of aggregated fullerene C60 particles on CHO and MDCK cells

The cytotoxicity of fullerene C60 particles on two mammalian cell lines, i.e. the Chinese hamster ovary (CHO) cells and the Madin-Darby canine kidney (MDCK) cells, has been investigated. Although innate fullerene particles have a very low solubility in deionized (DI) water, these particles can be dissolved in the tetrahydrofuran (THF) solvent at a great value. Further, the dissolved fullerene particles in the THF solvent could be extracted into a DI water solution at a significantly increased solubility. The formation of fullerene particle aggregates is believed to be the cause of the increased solubility. Results presented here show that once the concentration of the fullerene aggregates reaches a certain level, the cells start to die. The lethal dosage LD50, which is defined as the lowest fullerene concentration that results in a 50% cell death within 24 h, has been determined. Furthermore, the percentage of cell mortality increased with increasing fullerene concentration and incubation time yielding a negative effect on cell viability. These results, illustrated by atomic force microscopy (AFM), dynamic light scattering (DLS) and other microscopic techniques, will help to better understand the side effects of fullerene particles in mammalian cells.     

Filter-feature-based rotation-invariant joint Fourier transform correlator

Rotation-invariant target detection using a trained filter-feature-based joint Fourier transform (JFT) correlator is investigated. First, a composite reference image is obtained from a training set of targets. An optimum filter formulation is then applied on this composite image to come up with a new feature that we refer to as a filter feature. This feature is then used in a JFT correlator, which results in a simple and robust rotation-invariant target recognition system.     

Low voltage second-order alpha function synapse

This paper introduces a Transimpedance Amplifier (TIA) design capable of producing an incremental input resistance in the ohmic range, for input signals in the microampere range, such as are encountered in the design of instrumentation for electrochemical ampero-metric sensors, optical-sensing and current-mode circuits. This low input-resistance is achieved using an input stage incorporating negative feedback. In a Cadence simulation of an exemplary design using a 180 nm CMOS process and operating with?±?1.8 V supply rails, the input resistance is 1.05 ohms and the power dissipation is 93.6 µW. The bandwidth, for a gain of 100 dBohm, exceeded 9 MHz. For a 1µA, 1 MHz sinusoidal input signal the Total Harmonic Distortion, with this gain, is less than 1%. The input referred noise current with zero photodiode capacitance is 2.09 pA/√Hz and with a photodiode capacitance of 2pF is 8.52 pA/√Hz. Graphical data is presented to show the effect of a photodiode capacitance varying from 0.5 to 2 pF, when the TIA is used in optical sensing. In summary, the required very low input resistance, at a low input current level (µA) is achieved and furthermore a Table is included comparing the characteristics and a widely used Figure of Merit (FOM) for the proposed TIA and similar published low-power TIAs. It is apparent from the Table that the FOM of the proposed TIA is better than the FOMs of the other TIAs mentioned.