999 resultados para geometric arrays


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For a Cheby-bar shev array with a prescribed sidelobe level and given number of elements, an optimum spacing is shown to exist, for any arbitrarily prescribed steering angle, for which the beamwidth is the least obtainable. An expression for the optimum spacing is given.

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Editors' note:Flexible, large-area display and sensor arrays are finding growing applications in multimedia and future smart homes. This article first analyzes and compares current flexible devices, then discusses the implementation, requirements, and testing of flexible sensor arrays.—Jiun-Lang Huang (National Taiwan University) and Kwang-Ting (Tim) Cheng (University of California, Santa Barbara)

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We report the synthesis of aligned arrays of millimeter long carbon nanotubes (CNTs), from benzene and ferrocene as the molecular precursor and catalyst respectively, by a one-step chemical vapor deposition technique. The length of the grown CNTs depends on the reaction temperature and increases from similar to 85 mu m to similar to 1.4 mm when the synthesis temperature is raised from 650 to 1100 degrees C, while the tube diameter is almost independent of the preparation temperature and is similar to 80 nm. The parallel arrangement of the CNTs, as well as their tube diameter can be verified spectroscopically by small angle X-ray scattering (SAXS) studies. Based on electron diffraction scattering (EDS) studies of the top and the base of the CNT films, a root growth process can be deduced.

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In this paper, we present a new algorithm for learning oblique decision trees. Most of the current decision tree algorithms rely on impurity measures to assess the goodness of hyperplanes at each node while learning a decision tree in top-down fashion. These impurity measures do not properly capture the geometric structures in the data. Motivated by this, our algorithm uses a strategy for assessing the hyperplanes in such a way that the geometric structure in the data is taken into account. At each node of the decision tree, we find the clustering hyperplanes for both the classes and use their angle bisectors as the split rule at that node. We show through empirical studies that this idea leads to small decision trees and better performance. We also present some analysis to show that the angle bisectors of clustering hyperplanes that we use as the split rules at each node are solutions of an interesting optimization problem and hence argue that this is a principled method of learning a decision tree.

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Given two independent Poisson point processes Phi((1)), Phi((2)) in R-d, the AB Poisson Boolean model is the graph with the points of Phi((1)) as vertices and with edges between any pair of points for which the intersection of balls of radius 2r centered at these points contains at least one point of Phi((2)). This is a generalization of the AB percolation model on discrete lattices. We show the existence of percolation for all d >= 2 and derive bounds fora critical intensity. We also provide a characterization for this critical intensity when d = 2. To study the connectivity problem, we consider independent Poisson point processes of intensities n and tau n in the unit cube. The AB random geometric graph is defined as above but with balls of radius r. We derive a weak law result for the largest nearest-neighbor distance and almost-sure asymptotic bounds for the connectivity threshold.

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We demonstrate that aligned carbon-nanotube arrays are efficient transporters of laser-generated megaampere electron currents over distances as large as a millimeter. A direct polarimetric measurement of the temporal and the spatial evolution of the megagauss magnetic fields (as high as 120 MG) at the target rear at an intensity of (10(18)-10(19)) W/cm(2) was corroborated by the rear-side hot electron spectra. Simulations show that such high magnetic flux densities can only be generated by a very well collimated fast electron bunch.

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Realization of thermally and chemically durable, ordered gold nanostructures using bottom-up self-assembly techniques are essential for applications in a wide range of areas including catalysis, energy generation, and sensing. Herein, we describe a modular process for realizing uniform arrays of gold nanoparticles, with interparticle spacings of 2 nm and above, by using RF plasma etching to remove ligands from self-assembled arrays of ligand-coated gold nanoparticles. Both nanoscale imaging and macroscale spectroscopic characterization techniques were used to determine the optimal conditions for plasma etching, namely RF power, operating pressure, duration of treatment, and type of gas. We then studied the effect of nanoparticle size, interparticle spacing, and type of substrate on the thermal durability of plasma-treated and untreated nanoparticle arrays. Plasma-treated arrays showed enhanced chemical and thermal durability, on account of the removal of ligands. To illustrate the application potential of the developed process, robust SERS (surface-enhanced Raman scattering) substrates were formed using plasma-treated arrays of silver-coated gold nanoparticles that had a silicon wafer or photopaper as the underlying support. The measured value of the average SERS enhancement factor (2 x 10(5)) was quantitatively reproducible on both silicon and paper substrates. The silicon substrates gave quantitatively reproducible results even after thermal annealing. The paper-based SERS substrate was also used to swab and detect probe molecules deposited on a solid surface.

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We have investigated the current-voltage characteristics of carbon nanotube arrays and shown that the current through the arrays increases rapidly with applied voltage before the breakdown occurs. Simultaneous measurements of current and temperature at one end of the arrays suggest that the rapid increase of current is due to Joule heating. The current through the array and the threshold voltage are found to increase with decreasing pressure. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.3702777]

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We describe the fabrication of silver nanotriangle array using angle resolved nanosphere lithography and utilizing the same for enhancing fluorescence. The well established nanosphere lithography is modified by changing the angle of deposition between the nanosphere mask and the beam of silver being deposited resulting in nanotriangles of varying surface area and density. The 470 nm plasmon resonance wavelength of the substrate was determined using minimum reflectivity method which closely matches with excitation wavelength of the fluorophore. Ten times enhancement in fluorescence emission intensity is obtained from fluorescein isothiocyanate coated on top of silver nanotriangle array separated by a spacer layer of poly vinyl alcohol as compared to glass. The enhanced fluorescence emission is attributed to the increase in local field enhancement.

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Three-dimensional numerical study of natural convection in a vertical channel with flush-mounted discrete heaters on opposite conductive substrate walls is carried out in the present work. Detailed flow and heat transfer characteristics are presented for various Grashof numbers. The heat transfer effects on one wall by the presence of heaters on its opposite wall is examined. It is found that heat transfer rates on one wall are increased by the presence of heaters on its opposite wall. The thermal boundary layers on the opposite walls complement each other for enhanced heat transfer. The effects of spacing between the heated walls, spacings between heaters and substrate conductivity on flow and heat transfer are examined. Existence of optimum spacings between the heated walls for maximum heat transfer and mass flow are observed. It is found that the heat transfer and fluid flow do not follow the same optimum spacings. Mass flow rate reaches maximum value at a wall spacing greater than the spacing for maximum heat transfer. This is because the interaction of thermal boundary layers on individual walls ceases at a lower spacing before the velocity boundary layers separate each other. It is found that increased spacings between heaters reduce individual heater temperatures provided the heaters close to exit on both substrates avail sufficient substrate potions on the exit side. Insufficient substrate portions between the exit heaters and the exit cause abnormal local temperature rise in the exit heaters which are the hottest ones among all the heaters. Optimal heater spacings exist for minimum hottest heater temperature rise. Correlations are presented for dimensionless mass flow rate, temperature maximum, and average Nusselt number.

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We report on the electrical transport properties of buckled carbon nanotube arrays synthesized by pyrolysis. Analyzing the experimental data based on the general theory of semiconductors, the arrays are predicted to be semiconducting and the band gap can be evaluated. The band gap of different arrays is in 25-50 meV range.

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Plasmonic interactions in a well-defined array of metallic nanoparticles can lead to interesting optical effects, such as local electric field enhancement and shifts in the extinction spectra, which are of interest in diverse technological applications, including those pertaining to biochemical sensing and photonic circuitry. Here, we report on a single-step wafer scale fabrication of a three-dimensional array of metallic nanoparticles whose sizes and separations can be easily controlled to be anywhere between fifty to a few hundred nanometers, allowing the optical response of the system to be tailored with great control in the visible region of the spectrum. The substrates, apart from having a large surface area, are inherently porous and therefore suitable for optical sensing applications, such as surface enhanced Raman scattering, containing a high density of spots with enhanced local electric fields arising from plasmonic couplings.

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Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

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We report the geometrical effect of graded buckled multiwalled carbon nanotube arrays on the electrical transport properties in the diffusive regime, via successive breakdown caused by the Joule heating. This breakdown occurs in the straighter region. Empirical relations involving the current-carrying ability, resistance, breakdown power, threshold voltage, diameter and length of carbon nanotube arrays are discussed on the basis of an extensive set of experimental data along with justification. The experimental results are corroborated by the density functional tight-binding calculations of electronic band structure. The band gap decreases as buckleness increases leading to the enhancement in the current-carrying ability and elucidating the role of buckleness in carbon nanotubes. Copyright (c) EPLA, 2012

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We propose a distribution-free approach to the study of random geometric graphs. The distribution of vertices follows a Poisson point process with intensity function n f(center dot), where n is an element of N, and f is a probability density function on R-d. A vertex located at x connects via directed edges to other vertices that are within a cut-off distance r(n)(x). We prove strong law results for (i) the critical cut-off function so that almost surely, the graph does not contain any node with out-degree zero for sufficiently large n and (ii) the maximum and minimum vertex degrees. We also provide a characterization of the cut-off function for which the number of nodes with out-degree zero converges in distribution to a Poisson random variable. We illustrate this result for a class of densities with compact support that have at most polynomial rates of decay to zero. Finally, we state a sufficient condition for an enhanced version of the above graph to be almost surely connected eventually.