999 resultados para trap efficiency


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In current practice, urban-rural development has been regarded as one of the key pillars in driving regenerative development that includes economic, social, and environmental balance. In association with rapid urbanization, an important contemporary issue in China is that its rural areas are increasingly lagging behind urban areas in their development and a coordinated provision of public facilities in rural areas is necessary to achieve a better balance. A model is therefore introduced for quantifying the effect of individual infrastructure projects on urban-rural balance (e-UR) by focusing on two attributes, namely, efficiency and equity. The model is demonstrated through a multi-criteria model, developed with data collected from infrastructure projects in Chongqing, with the criteria values for each project being scored by comparing data collected from the project involved with e-UR neutral “benchmark” values derived from a survey of experts in the field. The model helps evaluate the contribution of the projects to improving rural-urban balance and hence enable government decision-makers for the first time to prioritize future projects rigorously in terms of their likely contribution too.

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This thesis studied cadmium sulfide and cadmium selenide quantum dots and their performance as light absorbers in quantum dot-sensitised solar cells. This research has made contributions to the understanding of size dependent photodegradation, passivation and particle growth mechanism of cadmium sulfide quantum dots using SILAR method and the role of ZnSe shell coatings on solar cell performance improvement.

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We report a more accurate method to determine the density of trap states in a polymer field-effect transistor. In the approach, we describe in this letter, we take into consideration the sub-threshold behavior in the calculation of the density of trap states. This is very important since the sub-threshold regime of operation extends to fairly large gate voltages in these disordered semiconductor based transistors. We employ the sub-threshold drift-limited mobility model (for sub-threshold response) and the conventional linear mobility model for above threshold response. The combined use of these two models allows us to extract the density of states from charge transport data much more accurately. We demonstrate our approach by analyzing data from diketopyrrolopyrrole based co-polymer transistors with high mobility. This approach will also work well for other disordered semiconductors in which sub-threshold conduction is important.

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Unidirectional inductive power transfer (UIPT) systems allow loads to consume power while bidirectional IPT (BIPT) systems are more suitable for loads requiring two way power flow such as vehicle to grid (V2G) applications with electric vehicles (EVs). Many attempts have been made to improve the performance of BIPT systems. In a typical BIPT system, the output power is control using the pickup converter phase shift angle (PSA) while the primary converter regulates the input current. This paper proposes an optimized phase shift modulation strategy to minimize the coil losses of a series – series (SS) compensated BIPT system. In addition, a comprehensive study on the impact of power converters on the overall efficiency of the system is also presented. A closed loop controller is proposed to optimize the overall efficiency of the BIPT system. Theoretical results are presented in comparison to both simulations and measurements of a 0.5 kW prototype to show the benefits of the proposed concept. Results convincingly demonstrate the applicability of the proposed system offering high efficiency over a wide range of output power.

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Society is increasingly calling for professionals across government, industry, business and civil society to be able to problem-solve issues related to climate change and sustainable development as part of their work. In particular there is an emerging realisation of the fundamental need to swiftly reduce the growing demand for energy across society, and to then meet the demand with low emissions options. A key ingredient to addressing such issues is equipping professionals with emerging knowledge and skills to address energy challenges in all aspects of their work. The Council of Australian Governments has recognised this need, signing the National Partnership Agreement on Energy Efficiency in July 2009, which included a commitment to assist business and industry obtain the knowledge, skills and capacity to pursue cost-effective energy efficiency opportunities.2 Engineering will play a critical part among the professions, with Engineers Australia acknowledging that, ‘The need to make changes in the way energy is used and supplied throughout the world represents the greatest challenge to engineers in moving toward sustainability.’

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This report presents the findings of an investigation of energy efficiency resources for undergraduate engineering education, undertaken by web-based research, conversations with educators, and a university survey. The investigation draws on the results of a number of previous investigations undertaken by the research team for NFEE related to energy efficiency education and presents the following findings and recommendations, as explained in greater detail in the body of the report. The findings suggest that even though certain EE concepts and principles have been identified by lecturers as being important there is little to no coverage of a number of these concepts in some programs/courses. Similarly, many topics relating to the most important EE workforce skills and significant shortages as identified in industry research, do not rate highly in terms of both perceived importance by lecturers, or coverage within existing courses. Overall, these findings suggest that despite growing awareness of the importance of EE in both industry and academia, the current depth and breadth of EE content in courses does not reflect this. It confirms that efforts in these areas can be better supported.

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The Energy Efficiency (EE) Graduate Attributes Project focuses on engineering as a priority profession that has a significant role to play in addressing energy demand and supply issues in Australia. Specifically, this project aims to support embedding EE knowledge and skills throughout the engineering undergraduate curriculum, to help build capacity within the Australian workforce across major sectors of the economy, from mining, manufacturing and industrial applications to design, construction, maintenance and retrofitting built environments. The resultant report is intended to assist in future consultation with key groups such as Engineers Australia (EA), the Australian Council of Engineering Deans (ACED) and the eight EA colleges, to support systemic curriculum renewal and promote the design and development of high quality EE engineering education resources. The project is based on a whole-of-program outcomes-based approach to curriculum renewal, creating a transparent framework for integrating EE. This comprises collaborative consideration by academics and professional engineers who have experience in teaching and practising EE, to identify what students should learn to be equipped with relevant competencies by the time they graduate.

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Dewatering of microalgal culture is a major bottleneck towards the industrial-scale processing of microalgae for bio-diesel production. The dilute nature of harvested microalgal cultures poses a huge operation cost to dewater; thereby rendering microalgae-based fuels less economically attractive. This study explores the influence of microalgal growth phases and intercellular interactions during cultivation on dewatering efficiency of microalgae cultures. Experimental results show that microalgal cultures harvested during a low growth rate phase (LGRP) of 0.03 d-1 allowed a higher rate of settling than those harvested during a high growth rate phase (HGRP) of 0.11 d-1, even though the latter displayed a higher average differential biomass concentration of 0.2 g L-1 d-1. Zeta potential profile during the cultivation process showed a maximum electronegative value of -43.2 ± 0.7 mV during the HGRP which declined to stabilization at -34.5 ± 0.4 mV in the LGRP. The lower settling rate observed for HGRP microalgae is hence attributed to the high stability of the microalgal cells which electrostatically repel each other during this growth phase. Tangential flow filtration of 20 L HGRP culture concentrated 23 times by consuming 0.51 kWh/m3 of supernatant removed whilst 0.38 kWh/m3 was consumed to concentrate 20 L of LGRP by 48 times.

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Embedding metallic nanoparticles in organic solar cells can enhance the photoabsorption through light trapping processes. This paper investigates how gold islands obtained by annealing 1–5 nm thick Au layers affect the photoabsorption. Using finite-difference time-domain simulations, the cell efficiency for various island geometries and thicknesses are analyzed and the properties of the islands for maximal photocurrent are discussed. It is shown that a careful choice of size and concentration of gold islands could contribute to enhance the power conversion efficiencies when compared to standard organic solar cell devices. The conclusions are then compared to experimental data for thermally annealed gold islands in bulk heterojunction solar cells. The results of this paper will contribute to the optimization of plasmonic organic solar cell systems and will pave the way for the development of highly efficient organic solar cell devices.

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Achieving high efficiency with improved power transfer range and misalignment tolerance is the major design challenge in realizing Wireless Power Transfer (WPT) systems for industrial applications. Resonant coils must be carefully designed to achieve highest possible system performance by fully utilizing the available space. High quality factor and enhanced electromagnetic coupling are key indices which determine the system performance. In this paper, design parameter extraction and quality factor optimization of multi layered helical coils are presented using finite element analysis (FEA) simulations. In addition, a novel Toroidal Shaped Spiral (TSS) coil is proposed to increase power transfer range and misalignment tolerance. The proposed shapes and recommendations can be used to design high efficiency WPT resonator in a limited space.

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Most real-life data analysis problems are difficult to solve using exact methods, due to the size of the datasets and the nature of the underlying mechanisms of the system under investigation. As datasets grow even larger, finding the balance between the quality of the approximation and the computing time of the heuristic becomes non-trivial. One solution is to consider parallel methods, and to use the increased computational power to perform a deeper exploration of the solution space in a similar time. It is, however, difficult to estimate a priori whether parallelisation will provide the expected improvement. In this paper we consider a well-known method, genetic algorithms, and evaluate on two distinct problem types the behaviour of the classic and parallel implementations.

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Background The requirement for dual screening of titles and abstracts to select papers to examine in full text can create a huge workload, not least when the topic is complex and a broad search strategy is required, resulting in a large number of results. An automated system to reduce this burden, while still assuring high accuracy, has the potential to provide huge efficiency savings within the review process. Objectives To undertake a direct comparison of manual screening with a semi‐automated process (priority screening) using a machine classifier. The research is being carried out as part of the current update of a population‐level public health review. Methods Authors have hand selected studies for the review update, in duplicate, using the standard Cochrane Handbook methodology. A retrospective analysis, simulating a quasi‐‘active learning’ process (whereby a classifier is repeatedly trained based on ‘manually’ labelled data) will be completed, using different starting parameters. Tests will be carried out to see how far different training sets, and the size of the training set, affect the classification performance; i.e. what percentage of papers would need to be manually screened to locate 100% of those papers included as a result of the traditional manual method. Results From a search retrieval set of 9555 papers, authors excluded 9494 papers at title/abstract and 52 at full text, leaving 9 papers for inclusion in the review update. The ability of the machine classifier to reduce the percentage of papers that need to be manually screened to identify all the included studies, under different training conditions, will be reported. Conclusions The findings of this study will be presented along with an estimate of any efficiency gains for the author team if the screening process can be semi‐automated using text mining methodology, along with a discussion of the implications for text mining in screening papers within complex health reviews.