8 resultados para radial distribution function

em Universidad de Alicante


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The change in the carbonaceous skeleton of nanoporous carbons during their activation has received limited attention, unlike its counterpart process in the presence of an inert atmosphere. Here we adopt a multi-method approach to elucidate this change in a poly(furfuryl alcohol)-derived carbon activated using cyclic application of oxygen saturation at 250 °C before its removal (with carbon) at 800 °C in argon. The methods used include helium pycnometry, synchrotron-based X-ray diffraction (XRD) and associated radial distribution function (RDF) analysis, transmission electron microscopy (TEM) and, uniquely, electron energy-loss spectroscopy spectrum-imaging (EELS-SI), electron nanodiffraction and fluctuation electron microscopy (FEM). Helium pycnometry indicates the solid skeleton of the carbon densifies during activation from 78% to 93% of graphite. RDF analysis, EELS-SI, and FEM all suggest this densification comes through an in-plane growth of sp2 carbon out to the medium range without commensurate increase in order normal to the plane. This process could be termed ‘graphenization’. The exact way in which this process occurs is not clear, but TEM images of the carbon before and after activation suggest it may come through removal of the more reactive carbon, breaking constraining cross-links and creating space that allows the remaining carbon material to migrate in an annealing-like process.

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We have studied the radial dependence of the energy deposition of the secondary electron generated by swift proton beams incident with energies T = 50 keV–5 MeV on poly(methylmethacrylate) (PMMA). Two different approaches have been used to model the electronic excitation spectrum of PMMA through its energy loss function (ELF), namely the extended-Drude ELF and the Mermin ELF. The singly differential cross section and the total cross section for ionization, as well as the average energy of the generated secondary electrons, show sizeable differences at T ⩽ 0.1 MeV when evaluated with these two ELF models. In order to know the radial distribution around the proton track of the energy deposited by the cascade of secondary electrons, a simulation has been performed that follows the motion of the electrons through the target taking into account both the inelastic interactions (via electronic ionizations and excitations as well as electron-phonon and electron trapping by polaron creation) and the elastic interactions. The radial distribution of the energy deposited by the secondary electrons around the proton track shows notable differences between the simulations performed with the extended-Drude ELF or the Mermin ELF, being the former more spread out (and, therefore, less peaked) than the latter. The highest intensity and sharpness of the deposited energy distributions takes place for proton beams incident with T ~ 0.1–1 MeV. We have also studied the influence in the radial distribution of deposited energy of using a full energy distribution of secondary electrons generated by proton impact or using a single value (namely, the average value of the distribution); our results show that differences between both simulations become important for proton energies larger than ~0.1 MeV. The results presented in this work have potential applications in materials science, as well as hadron therapy (due to the use of PMMA as a tissue phantom) in order to properly consider the generation of electrons by proton beams and their subsequent transport and energy deposition through the target in nanometric scales.

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Dada la gran popularidad que están alcanzando los recubrimientos gonioaparentes en la industria, ha comenzado a ser de especial importancia su caracterización en términos de color. La reflectancia espectral de estos recubrimientos cambia de forma compleja con las condiciones geométricas de iluminación y observación, y, en consecuencia, su color no se puede describir en términos sencillos. En este trabajo se midió la Función de Distribución Bidireccional de Reflectancia espectral (spectral Bidirectional Reflectance Distribution Function, sBRDF) para dos recubrimientos gonioaparentes diferentes. El número de geometrías de medida utilizado permitió entender mejor las características a tener en cuenta para una mejor comprensión del cambio de color de estos recubrimientos.

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A reduced set of measurement geometries allows the spectral reflectance of special effect coatings to be predicted for any other geometry. A physical model based on flake-related parameters has been used to determine nonredundant measurement geometries for the complete description of the spectral bidirectional reflectance distribution function (BRDF). The analysis of experimental spectral BRDF was carried out by means of principal component analysis. From this analysis, a set of nine measurement geometries was proposed to characterize special effect coatings. It was shown that, for two different special effect coatings, these geometries provide a good prediction of their complete color shift.

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A representation of the color gamut of special effect coatings is proposed and shown for six different samples, whose colors were calculated from spectral bidirectional reflectance distribution function (BRDF) measurements at different geometries. The most important characteristic of the proposed representation is that it allows a straightforward understanding of the color shift to be done both in terms of conventional irradiation and viewing angles and in terms of flake-based parameters. A different line was proposed to assess the color shift of special effect coatings on a*,b*-diagrams: the absorption line. Similar to interference and aspecular lines (constant aspecular and irradiation angles, respectively), an absorption line is the locus of calculated color coordinates from measurement geometries with a fixed bistatic angle. The advantages of using the absorption lines to characterize the contributions to the spectral BRDF of the scattering at the absorption pigments and the reflection at interference pigments for different geometries are shown.

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A new classification of microtidal sand and gravel beaches with very different morphologies is presented below. In 557 studied transects, 14 variables were used. Among the variables to be emphasized is the depth of the Posidonia oceanica. The classification was performed for 9 types of beaches: Type 1: Sand and gravel beaches, Type 2: Sand and gravel separated beaches, Type 3: Gravel and sand beaches, Type 4: Gravel and sand separated beaches, Type 5: Pure gravel beaches, Type 6: Open sand beaches, Type 7: Supported sand beaches, Type 8: Bisupported sand beaches and Type 9: Enclosed beaches. For the classification, several tools were used: discriminant analysis, neural networks and Support Vector Machines (SVM), the results were then compared. As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer. Finally, an architecture with 30 neurons was chosen. Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid). The results obtained for the discriminant analysis were not as good as those obtained for the other two methods (ANN and SVM) which showed similar success.

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Background and objective: In this paper, we have tested the suitability of using different artificial intelligence-based algorithms for decision support when classifying the risk of congenital heart surgery. In this sense, classification of those surgical risks provides enormous benefits as the a priori estimation of surgical outcomes depending on either the type of disease or the type of repair, and other elements that influence the final result. This preventive estimation may help to avoid future complications, or even death. Methods: We have evaluated four machine learning algorithms to achieve our objective: multilayer perceptron, self-organizing map, radial basis function networks and decision trees. The architectures implemented have the aim of classifying among three types of surgical risk: low complexity, medium complexity and high complexity. Results: Accuracy outcomes achieved range between 80% and 99%, being the multilayer perceptron method the one that offered a higher hit ratio. Conclusions: According to the results, it is feasible to develop a clinical decision support system using the evaluated algorithms. Such system would help cardiology specialists, paediatricians and surgeons to forecast the level of risk related to a congenital heart disease surgery.

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Context. The Gaia-ESO Survey (GES) is a large public spectroscopic survey at the European Southern Observatory Very Large Telescope. Aims. A key aim is to provide precise radial velocities (RVs) and projected equatorial velocities (vsini) for representative samples of Galactic stars, which will complement information obtained by the Gaia astrometry satellite. Methods. We present an analysis to empirically quantify the size and distribution of uncertainties in RV and vsini using spectra from repeated exposures of the same stars. Results. We show that the uncertainties vary as simple scaling functions of signal-to-noise ratio (S/N) and vsini, that the uncertainties become larger with increasing photospheric temperature, but that the dependence on stellar gravity, metallicity and age is weak. The underlying uncertainty distributions have extended tails that are better represented by Student’s t-distributions than by normal distributions. Conclusions. Parametrised results are provided, which enable estimates of the RV precision for almost all GES measurements, and estimates of the vsini precision for stars in young clusters, as a function of S/N, vsini and stellar temperature. The precision of individual high S/N GES RV measurements is 0.22–0.26 km s-1, dependent on instrumental configuration.