Optical and micro-structural properties of high photoluminescence efficiency InGaN/AlInGaN quantum well structures

We have studied the optical properties of a series of InGaN/AlInGaN 10-period multiple quantum wells (MQW) with differing well thickness grown by metal-organic vapor-phase epitaxy that emit at around 380 nm. The aim of this investigation was to optimise the room temperature internal quantum efficiency, thus the quantum well (QW) thicknesses were accordingly chosen so that the overlap of the electron/hole wave function was maximised. At low temperature, we observed a reduction of the photo luminescence decay time with decreasing well width in line with the theoretical predictions. For a structure with well thicknesses of 1.5 nm, we measured a photoluminescence internal quantum efficiency of 67% at room temperature with a peak emission wavelength of 382 nm. (c) 2006 Elsevier B.V. All rights reserved.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

Blade loading and its application in the mean-line design of low pressure turbines

In order to minimize the number of iterations to a turbine design, reasonable choices of the key parameters must be made at the earliest possible opportunity. The choice of blade loading is of particular concern in the low pressure (LP) turbine of civil aero engines, where the use of high-lift blades is widespread. This paper presents an analytical mean-line design study for a repeating-stage, axial-flow Low Pressure (LP) turbine. The problem of how to measure blade loading is first addressed. The analysis demonstrates that the Zweifel coefficient [1] is not a reasonable gauge of blade loading because it inherently depends on the flow angles. A more appropriate coefficient based on blade circulation is proposed. Without a large set of turbine test data it is not possible to directly evaluate the accuracy of a particular loss correlation. The analysis therefore focuses on the efficiency trends with respect to flow coefficient, stage loading, lift coefficient and Reynolds number. Of the various loss correlations examined, those based on Ainley and Mathieson ([2], [3], [4]) do not produce realistic trends. The profile loss model of Coull and Hodson [5] and the secondary loss models of Craig and Cox [6] and Traupel [7] gave the most reasonable results. The analysis suggests that designs with the highest flow turning are the least sensitive to increases in blade loading. The increase in Reynolds number lapse with loading is also captured, achieving reasonable agreement with experiments. Copyright © 2011 by ASME.

Heat source modelling and natural ventilation efficiency

We compare natural ventilation flows established by a range of heat source distributions at floor level. Both evenly distributed and highly localised line and point source distributions are considered. We demonstrate that modelling the ventilation flow driven by a uniformly distributed heat source is equivalent to the flow driven by a large number of localised sources. A model is developed for the transient flow development in a room with a uniform heat distribution and is compared with existing models for localised buoyancy inputs. For large vent areas the flow driven by localised heat sources reaches a steady state more rapidly than the uniformly distributed case. For small vent areas there is little difference in the transient development times. Our transient model is then extended to consider the time taken to flush a neutrally buoyant pollutant from a naturally ventilated room. Again comparisons are drawn between uniform and localised (point and line) heat source geometries. It is demonstrated that for large vent areas a uniform heat distribution provides the fastest flushing. However, for smaller vent areas, localised heat sources produce the fastest flushing. These results are used to suggest a definition for the term 'natural ventilation efficiency', and a model is developed to estimate this efficiency as a function of the room and heat source geometries. © 2006 Elsevier Ltd. All rights reserved.

Transitions to material efficiency in the UK steel economy.

Steel production is energy intensive so already has achieved impressive levels of energy efficiency. If the emissions associated with steel must be reduced in line with the requirements of the UK Climate Change Act, demand for new steel must be reduced. The strategies of 'material efficiency' aim to achieve such a reduction, while delivering the same final services. To meet the emissions targets set into UK law, UK consumption of steel must be reduced to 30 per cent of present levels by 2050. Previous work has revealed six strategies that could contribute to this target, and this paper presents an approximate analysis of the required transition. A macro-economic analysis of steel in the UK shows that while the steel industry is relatively small, the construction and manufacturing sectors are large, and it would be politically unacceptable to pursue options that lead to a major contraction in other sectors. Alternative business models are therefore required, and these are explored through four representative products--one for each final sector with particular emphasis given to options for reducing product weight, and extending product life. Preliminary evidence on the triggers that would lead to customers preferring these options is presented and organized in order to predict required policy measures. The estimated analysis of transitions explored in this paper is used to define target questions for future research in the area.

Blade Loading and Its Application in the Mean-Line Design of Low Pressure Turbines

In order to minimize the number of iterations to a turbine design, reasonable choices of the key parameters must be made at the preliminary design stage. The choice of blade loading is of particular concern in the low pressure (LP) turbine of civil aero engines, where the use of high-lift blades is widespread. This paper considers how blade loading should be measured, compares the performance of various loss correlations, and explores the impact of blade lift on performance and lapse rates. To these ends, an analytical design study is presented for a repeating-stage, axial-flow LP turbine. It is demonstrated that the long-established Zweifel lift coefficient (Zweifel, 1945, "The Spacing of Turbomachine Blading, Especially with Large Angular Deflection" Brown Boveri Rev., 32(1), pp. 436-444) is flawed because it does not account for the blade camber. As a result the Zweifel coefficient is only meaningful for a fixed set of flow angles and cannot be used as an absolute measure of blade loading. A lift coefficient based on circulation is instead proposed that accounts for the blade curvature and is independent of the flow angles. Various existing profile and secondary loss correlations are examined for their suitability to preliminary design. A largely qualitative comparison demonstrates that the loss correlations based on Ainley and Mathieson (Ainley and Mathieson, 1957, "A Method of Performance Estimation for Axial-Flow Turbines," ARC Reports and Memoranda No. 2974; Dunham and Came, 1970, "Improvements to the Ainley-Mathieson Method of Turbine Performance Prediction," Trans. ASME: J. Eng. Gas Turbines Power, July, pp. 252-256; Kacker and Okapuu, 1982, "A Mean Line Performance Method for Axial Flow Turbine Efficiency," J. Eng. Power, 104, pp. 111-119). are not realistic, while the profile loss model of Coull and Hodson (Coull and Hodson, 2011, "Predicting the Profile Loss of High-Lift Low Pressure Turbines," J. Turbomach., 134(2), pp. 021002) and the secondary loss model of (Traupel, W, 1977, Thermische Turbomaschinen, Springer-Verlag, Berlin) are arguably the most reasonable. A quantitative comparison with multistage rig data indicates that, together, these methods over-predict lapse rates by around 30%, highlighting the need for improved loss models and a better understanding of the multistage environment. By examining the influence of blade lift across the Smith efficiency chart, the analysis demonstrates that designs with higher flow turning will tend to be less sensitive to increases in blade loading. © 2013 American Society of Mechanical Engineers.

Low-cost high-efficiency GaN LED on large-area si substrate

The use of large size Si substrates for epitaxy of nitride light emitting diode (LED) structures has attracted great interest because Si wafers are readily available in large diameter at low cost. In addition, such wafers are compatible with existing processing lines for the 6-inch and larger wafer sizes commonly used in the electronics industry. With the development of various methods to avoid wafer cracking and reduce the defect density, the performance of GaN-based LED and electronic devices has been greatly improved. In this paper, we review our methods of growing crack-free InGaN-GaN multiple quantum well (MQW) LED structures of high crystalline quality on Si(111) substrates. The performance of processed LED devices and its dependence on the threading dislocation density were studied. Full wafer-level LED processing using a conventional 6-inch III-V processing line is also presented, demonstrating the great advantage of using large-size Si substrates for mass production of GaN LED devices.

High photoluminescence quantum efficiency InGaN multiple quantum well structures emitting at 380 nm

In this paper we report the design of high room temperature photoluminescence internal efficiency InGaN-based quantum well structures emitting in the near ultraviolet at 380 nm. To counter the effects of nonradiative recombination the quantum wells were designed to have a large indium fraction, high barriers, and a small quantum well thickness. To minimize the interwell and interbarrier thickness fluctuations we used Al0.2In0.005Ga0.795N barriers, where the inclusion of the small fraction of indium was found to lead to fewer structural defects and a reduction in the layer thickness fluctuations. This approach has led us to achieve, for an In0.08Ga0.92N/Al0.2In0.005Ga0.795N multiple quantum well structure with a well width of 1.5 nm, a photoluminescence internal efficiency of 67% for peak emission at 382 nm at room temperature. (c) 2007 American Institute of Physics.

The MHP36 line of murine neural stem cells expresses functional CXCR1 chemokine receptors that initiate chemotaxis in vitro.

Chemokines help to establish cerebral inflammation after ischemia, which comprises a major component of secondary brain injury. The CXCR4 chemokine receptor system induces neural stem cell migration, and hence has been implicated in brain repair. We show that CXCR1 and interleukin-8 also stimulate chemotaxis in murine neural stem cells from the MHP36 cell line. The presence of CXCR1 was confirmed by reverse transcriptase PCR and immunohistochemistry. Interleukin-8 evoked intracellular calcium currents, upregulated doublecortin (a protein expressed by migrating neuroblasts), and elicited positive chemotaxis in vitro. Therefore, effectors of the early innate immune response may also influence brain repair mechanisms.