13 resultados para Structural and morphological properties

em Universidad Politécnica de Madrid


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We have analyzed the structural and magnetic properties of as-grown and annealed [TbFe2/Fe3Ga]n heterostructures grown by sputtering. Evidence of the bcc structure in the Fe3Ga layers has been found. The diffraction peak related to this structure shifts to high angles with the annealing temperature. Also, we have observed a change in the microstructure of the Tb-Fe layers when the thickness layer is reduced in the as-grown heterostructures. Moreover, the Tb content is lower than 33% of the TbFe2 Laves phase and it depends on the layer thickness. The thermal treatments promote the increase of the Tb content, but only in the heterostructures with thick layers. The strong lattice mismatch between the Tb-Fe and Fe-Ga layers seems to prevent a complete Tb diffusion upon the annealing process. Thus, the crystallization of the TbFe2 Laves phase is inhibited in the heterostructures with thin layers, although our experimental results indicate the presence of potential magnetostrictive TbFeGa alloys

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The cadmium thioindate spinel CdIn2S4 semiconductor has potential applications for optoelectronic devices. We present a theoretical study of the structural and optoelectronic properties of the host and of the Cr-doped ternary spinel. For the host spinel, we analyze the direct or indirect character of the energy bandgap, the change of the energy bandgap with the anion displacement parameter and with the site cation distribution, and the optical properties. The main effect of the Cr doping is the creation of an intermediate band within the energy bandgap. The character and the occupation of this band are analyzed for two substitutions: Cr by In and Cr by Cd. This band permits more channels for the photon absorption. The optical properties are obtained and analyzed. The absorption coefficients are decomposed into contributions from the different absorption channels and from the inter-and intra-atomic components.

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ZnO nanofibre networks (NFNs) were grown by vapour transport method on Si-based substrates. One type of substrate was SiO2 thermally grown on Si and another consisted of a Si wafer onto which Si nanowires (NWs) had been grown having Au nanoparticles catalysts. The ZnO-NFN morphology was observed by scanning electron microscopy on samples grown at 600 °C and 720 °C substrate temperature, while an focused ion beam was used to study the ZnO NFN/Si NWs/Si and ZnO NFN/SiO2 interfaces. Photoluminescence, electrical conductance and photoconductance of ZnO-NFN was studied for the sample grown on SiO2. The photoluminescence spectra show strong peaks due to exciton recombination and lattice defects. The ZnO-NFN presents quasi-persistent photoconductivity effects and ohmic I-V characteristics which become nonlinear and hysteretic as the applied voltage is increased. The electrical conductance as a function of temperature can be described by a modified three dimensional variable hopping model with nanometer-ranged typical hopping distances.

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The quaternary nitride-based high electron mobility transistor (HEMT) has been recently a focus of interest because of the possibility to grow lattice-matched barrier to GaN and tune the barrier bandgap at the same time.

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The behaviour of four alkali-borosilicate glasses under homogeneous thermal neutron irradiation has been studied. These materials are used for the manufacturing of neutron guides which are installed in most facilities as devices to transport neutrons from intense sources such as nuclear reactors or spallation sources up to scientific instruments. Several experimental techniques such as Raman, NMR, SANS and STEM have been employed in order to understand the rather different macroscopic behaviour under irradiation of materials that belong to a same glass family. The results have shown that the remarkable glass shrinking observed for neutron doses below 0.5 · 10 18 n/cm 2 critically depends upon the presence of domains where silicate and borate network do not mix.

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In this work we present the assessment of the structural and piezoelectric properties of Al(0.5-x)TixN0.5 compounds (titanium content menor que6% atomic), which are expected to possess improved properties than conventional AlN films, such as larger piezoelectric activity, thermal stability of frequency and temperature resistance. Al:Ti:N films were deposited from a twin concentric target of Al and Ti by reactive AC sputtering, which provided films with a radial gradient of the Ti concentration. The properties of the films were investigated as a function of their composition, which was measured by electron dispersive energy dispersive X-ray spectroscopy and Rutherford backscattering spectrometry. The microstructure and morphology of the films were assessed by X-ray diffraction and infrared reflectance. Their electroacoustic properties and dielectric constant were derived from the frequency response of BAW test resonators. Al:Ti:N films properties appear to be strongly dependent on the Ti content, which modifies the AlN wurtzite crystal structure leading to greater dielectric constant, lower sound velocities, lower electromechanical factor and moderately improved temperature coefficient of the resonant frequency.

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A novel class of graphs, here named quasiperiodic, are const ructed via application of the Horizontal Visibility algorithm to the time series generated along the quasiperiodic route to chaos. We show how the hierarchy of mode-locked regions represented by the Far ey tree is inherited by their associated graphs. We are able to establish, via Renormalization Group (RG) theory, the architecture of the quasiperiodic graphs produced by irrational winding numbers with pure periodic continued fraction. And finally, we demonstrate that the RG fixed-point degree distributions are recovered via optimization of a suitably defined graph entropy

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Novel poly(phenylene sulphide) (PPS) nanocomposites reinforced with an aminated derivative (PPS-NH2) covalently attached to acid-treated single-walled carbon nanotubes (SWCNTs) were prepared via simple melt-blending technique. Their morphology, viscoelastic behaviour, electrical conductivity, mechanical and tribological properties were investigated. Scanning electron microscopy revealed that the grafting process was effective in uniformly dispersing the SWCNTs within the matrix. The storage and loss moduli as a function of frequency increased with the SWCNT content, tending to a plateau in the low-frequency regime. The electrical conductivity of the nanocomposites was considerably enhanced in the range 0.1?0.5 wt% SWCNTs; electrical and rheological percolation thresholds occurred at similar nanotube concentrations. Mechanical tests demonstrated that with only 1.0 wt% SWCNTs the Young's modulus and tensile strength of the matrix improved by 51 and 37%, respectively, without decrement in toughness, ascribed to a very efficient load transfer. A moderate decrease in the friction coefficient and a 75% reduction in wear rate were found for the abovementioned nanotube loading, indicating that PPS-NH2-g-SWCNTs are good tribological additives for thermoplastic polymers. Based on the promising results obtained in this work, it is expected that these nanofillers will be used to develop high-performance thermoplastic/CNT nanocomposites for structural applications.

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The influence of nanosecond laser pulses applied by laser shock peening without absorbent coating (LSPwC) with a Q-switched Nd:YAG laser operating at a wavelength of λ = 1064 nm on 6082-T651 Al alloy has been investigated. The first portion of the present study assesses laser shock peening effect at two pulse densities on three-dimensional (3D) surface topography characteristics. In the second part of the study, the peening effect on surface texture orientation and micro-structure modification, i.e. the effect of surface craters due to plasma and shock waves, were investigated in both longitudinal (L) and transverse (T) directions of the laser-beam movement. In the final portion of the study, the changes of mechanical properties were evaluated with a residual stress profile and Vickers micro-hardness through depth variation in the near surface layer, whereas factorial design with a response surface methodology (RSM) was applied. The surface topographic and micro-structural effect of laser shock peening were characterised with optical microscopy, InfiniteFocus® microscopy and scanning electron microscopy (SEM). Residual stress evaluation based on a hole-drilling integral method confirmed higher compression at the near surface layer (33 μm) in the transverse direction (σmin) of laser-beam movement, i.e. − 407 ± 81 MPa and − 346 ± 124 MPa, after 900 and 2500 pulses/cm2, respectively. Moreover, RSM analysis of micro-hardness through depth distribution confirmed an increase at both pulse densities, whereas LSPwC-generated shock waves showed the impact effect of up to 800 μm below the surface. Furthermore, ANOVA results confirmed the insignificant influence of LSPwC treatment direction on micro-hardness distribution indicating essentially homogeneous conditions, in both L and T directions.

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We present a theoretical study of the structural and electronic properties of the M-doped MgIn2S4 ternary spinel semiconductor with M = V, Cr, and Mn. All substitutions, in the normal and in the inverse structure, are analyzed. Some of these possible substitutions present intermediate-band states in the band gap with a different occupation for a spin component. It increases the possibilities of inter-band transitions and could be interesting for applications in optoelectronic devices. The contribution to, and the electronic configuration of, these intermediate bands for the octahedral and tetrahedral sites is analyzed and discussed. The study of the substitutional energies indicates that these substitutions are favorable. Comparison between the pure and doped hosts absorption coefficients shows that this deeper band opens up more photon absorption channels and could therefore increase the solar-light absorption with respect to the host.

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La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

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Long-length ultrafine-grained (UFG) Ti rods are produced by equal-channel angular pressing via the conform scheme (ECAP-C) at 200 °C, which is followed by drawing at 200 °C. The evolution of microstructure, macrotexture, and mechanical properties (yield strength, ultimate tensile strength, failure stress, uniform elongation, elongation to failure) of pure Ti during this thermo-mechanical processing is studied. Special attention is also paid to the effect of microstructure on the mechanical behavior of the material after macrolocalization of plastic flow. The number of ECAP-C passes varies in the range of 1–10. The microstructure is more refined with increasing number of ECAP-C passes. Formation of homogeneous microstructure with a grain/subgrain size of 200 nm and its saturation after 6 ECAP-C passes are observed. Strength properties increase with increasing number of ECAP passes and saturate after 6 ECAP-C passes to a yield strength of 973 MPa, an ultimate tensile strength of 1035 MPa, and a true failure stress of 1400 MPa (from 625, 750, and 1150 MPa in the as-received condition). The true strain at failure failure decreases after ECAP-C processing. The reduction of area and true strain to failure values do not decrease after ECAP-C processing. The sample after 6 ECAP-C passes is subjected to drawing at 200¯C resulting in reduction of a grain/subgrain size to 150 nm, formation of (10 View the MathML source1¯0) fiber texture with respect to the rod axis, and further increase of the yield strength up to 1190 MPa, the ultimate tensile strength up to 1230 MPa and the true failure stress up to 1600 MPa. It is demonstrated that UFG CP Ti has low resistance to macrolocalization of plastic deformation and high resistance to crack formation after necking.

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The EFDA-ITER programme for materials wants to develop new structural materials for future nuclear magnetic fusion reactors. In this context, special attention must be paid in the development of new composite materials that could support the hard working conditions of the nuclear fusion reactors: high temperature, high stresses, and high radiation.