31 resultados para multi-layer dielectric gratings
em Universidade do Minho
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Scientific and technological advancements in the area of fibrous and textile materials have greatly enhanced their application potential in several high-end technical and industrial sectors including construction, transportation, medical, sports, aerospace engineering, electronics and so on. Excellent performance accompanied by light-weight, mechanical flexibility, tailor-ability, design flexibility, easy fabrication and relatively lower cost are the driving forces towards wide applications of these materials. Cost-effective fabrication of various advanced and functional materials for structural parts, medical devices, sensors, energy harvesting devices, capacitors, batteries, and many others has been possible using fibrous and textile materials. Structural membranes are one of the innovative applications of textile structures and these novel building skins are becoming very popular due to flexible design aesthetics, durability, lightweight and cost benefits. Current demand on high performance and multi-functional materials in structural applications has motivated to go beyond the basic textile structures used for structural membranes and to use innovative textile materials. Structural membranes with self-cleaning, thermoregulation and energy harvesting capability (using solar cells) are examples of such recently developed multi-functional membranes. Besides these, there exist enormous opportunities to develop wide varieties of multi-functional membranes using functional textile materials. Additionally, it is also possible to further enhance the performance and functionalities of structural membranes using advanced fibrous architectures such as 2D, 3D, hybrid, multi-layer and so on. In this context, the present paper gives an overview of various advanced and functional fibrous and textile materials which have enormous application potential in structural membranes.
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We report on the growth and structural and morphologic characterization of stacked layers of self-assembled GeSn dots grown on Si (100) substrates by molecular beam epitaxy at low substrate temperature T = 350 °C. Samples consist of layers (from 1 up to 10) of Ge0.96Sn0.04 self-assembled dots separated by Si spacer layers, 10 nm thick. Their structural analysis was performed based on transmission electron microscopy, atomic force microscopy and Raman scattering. We found that up to 4 stacks of dots could be grown with good dot layer homogeneity, making the GeSn dots interesting candidates for optoelectronic device applications.
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Autor proof
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Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.
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Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.
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Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.
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In this work the dielectric properties and ferromagnetic resonance of Polyvinylidene- uoride embedded with 10 wt. % of NiFe2O4 or Ni0.5Zn0.5Fe2O4 nanoparticles are presented. The mechanisms of the dielectric relaxation in these two composites do not differ from each other. For more precise characterization of the dielectric relaxation, a two dimensional distribution of relaxation times was calculated from the temperature dependencies of the complex dielectric permittivity. The results obtained from the 2D distribution and the mean relaxation time are found to be consistent. The dynamics of the dielectric permittivity is described by the Arrhenius law. The energy and attempt time of the dielectric relaxators lie in a narrow energy and time region thus proving that the single type chains of polymer are responsible for a dispersion. The magnetic properties of the composites were investigated using the fer- romagnetic resonance. A single resonance line was observed for both samples. From the temperature dependence (100 K - 310 K) of the resonance eld and linewidth, the origin of the observed line was attributed to the NiFe2O4 and Ni0.5Zn0.5Fe2O4 superparamagnetic nanoparticles. By measuring lms at dif- ferent orientations with respect to the external magnetic eld, the angular dependence of the resonance was observed, indicating the magnetic dipolar in-plane interactions.
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Polyimide co-polymers have been prepared based on different diamines as co-monomers: a diamine without CN groups and a novel synthesized diamine with two CN groups prepared by polycondensation reaction followed by thermal cyclodehydration. Dielectric spectroscopy measurements were performed and the dielectric complex function, ac conductivity and electric modulus of the co-polymers were investigated as a function of CN group content in the frequency range from 0.1 Hz to 107 Hz at temperatures from 25 to 260 °C. For all samples and temperatures above 150ºC, the dielectric constant increases with increasing temperature due to increaseing conductivity. The α-relaxation is just detected for the sample without CN groups, being this relaxation overlapped by the electrical conductivity contributions in the remaining samples. For the copolymer samples and the polymer with CN groups an important Maxwell-Wagner-Sillars contribution is detected. The mechanisms responsible for the dielectric relaxation, conduction process and electric modulus response have been discussed as a function of the CN groups content present in the samples.
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Printed electronics represent an alternative solution for the manufacturing of low-temperature and large area flexible electronics. The use of inkjet printing is showing major advantages when compared to other established printing technologies such as, gravure, screen or offset printing, allowing the reduction of manufacturing costs due to its efficient material usage and the direct-writing approach without requirement of any masks. However, several technological restrictions for printed electronics can hinder its application potential, e.g. the device stability under atmospheric or even more stringent conditions. Here, we study the influence of specific mechanical, chemical, and temperature treatments usually appearing in manufacturing processes for textiles on the electrical performance of all-inkjet-printed organic thin-film transistors (OTFTs). Therefore, OTFTs where manufactured with silver electrodes, a UV curable dielectric, and 6,13-bis(triisopropylsilylethynyl) pentance (TIPS-pentacene) as the active semiconductor layer. All the layers were deposited using inkjet printing. After electrical characterization of the printed OTFTs, a simple encapsulation method was applied followed by the degradation study allowing a comparison of the electrical performance of treated and not treated OTFTs. Industrial calendering, dyeing, washing and stentering were selected as typical textile processes and treatment methods for the printed OTFTs. It is shown that the all-inkjet-printed OTFTs fabricated in this work are functional after their submission to the textiles processes but with degradation in the electrical performance, exhibiting higher degradation in the OTFTs with shorter channel lengths (L=10 μm).
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We search for evidence of physics beyond the Standard Model in the production of final states with multiple high transverse momentum jets, using 20.3 fb−1 of proton-proton collision data recorded by the ATLAS detector at s√ = 8 TeV. No excess of events beyond Standard Model expectations is observed, and upper limits on the visible cross-section for non-Standard Model production of multi-jet final states are set. Using a wide variety of models for black hole and string ball production and decay, the limit on the cross-section times acceptance is as low as 0.16 fb at the 95% CL for a minimum scalar sum of jet transverse momentum in the event of about 4.3 TeV. Using models for black hole and string ball production and decay, exclusion contours are determined as a function of the production mass threshold and the gravity scale. These limits can be interpreted in terms of lower-mass limits on black hole and string ball production that range from 4.6 to 6.2 TeV.
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A search for heavy long-lived multi-charged particles is performed using the ATLAS detector at the LHC. Data collected in 2012 at s√=8 TeV from pp collisions corresponding to an integrated luminosity of 20.3 fb−1 are examined. Particles producing anomalously high ionisation, consistent with long-lived massive particles with electric charges from |q|=2e to |q|=6e are searched for. No signal candidate events are observed, and 95% confidence level cross-section upper limits are interpreted as lower mass limits for a Drell--Yan production model. The mass limits range between 660 and 785 GeV.
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In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.
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Gold nanoparticles were dispersed in two different dielectric matrices, TiO2 and Al2O3, using magnetron sputtering and a post-deposition annealing treatment. The main goal of the present work was to study how the two different host dielectric matrices, and the resulting microstructure evolution (including both the nanoparticles and the host matrix itself) promoted by thermal annealing, influenced the physical properties of the films. In particular, the structure and morphology of the nanocomposites were correlated with the optical response of the thin films, namely their localized surface plasmon resonance (LSPR) characteristics. Furthermore, and in order to scan the future application of the two thin film system in different types of sensors (namely biological ones), their functional behaviour (hardness and Young's modulus change) was also evaluated. Despite the similar Au concentrations in both matrices (~ 11 at.%), very different microstructural features were observed, which were found to depend strongly on the annealing temperature. The main structural differences included: (i) the early crystallization of the TiO2 host matrix, while the Al2O3 one remained amorphous up to 800 °C; (ii) different grain size evolution behaviours with the annealing temperature, namely an almost linear increase for the Au:TiO2 system (from 3 to 11 nm), and the approximately constant values observed in the Au:Al2O3 system (4–5 nm). The results from the nanoparticle size distributions were also found to be quite sensitive to the surrounding matrix, suggesting different mechanisms for the nanoparticle growth (particle migration and coalescence dominating in TiO2 and Ostwald ripening in Al2O3). These different clustering behaviours induced different transmittance-LSPR responses and a good mechanical stability, which opens the possibility for future use of these nanocomposite thin film systems in some envisaged applications (e.g. LSPR-biosensors).
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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Biomateriais, Reabilitação e Biomecânica)