962 resultados para RESONANCE EFFECT


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The possibility to discriminate between the relative importance of the fluxes of energy and matter in plasma-surface interaction is demonstrated by the energy flux measurements in low-temperature plasmas ignited by the radio frequency discharge (power and pressure ranges 50-250 W and 8-11.5 Pa) in Ar, Ar+ H2, and Ar+ H2 + CH4 gas mixtures typically used in nanoscale synthesis and processing of silicon- and carbon-based nanostructures. It is shown that by varying the gas composition and pressure, the discharge power, and the surface bias one can effectively control the surface temperature and the matter supply rates. The experimental findings are explained in terms of the plasma-specific reactions in the plasma bulk and on the surface.

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We report on the application low-temperature plasmas for roughening Si surfaces which is becoming increasingly important for a number of applications ranging from Si quantum dots to cell and protein attachment for devices such as "laboratory on a chip" and sensors. It is a requirement that Si surface roughening is scalable and is a single-step process. It is shown that the removal of naturally forming SiO2 can be used to assist in the roughening of the surface using a low-temperature plasma-based etching approach, similar to the commonly used in semiconductor micromanufacturing. It is demonstrated that the selectivity of SiO2 /Si etching can be easily controlled by tuning the plasma power, working gas pressure, and other discharge parameters. The achieved selectivity ranges from 0.4 to 25.2 thus providing an effective means for the control of surface roughness of Si during the oxide layer removal, which is required for many advance applications in bio- and nanotechnology.

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Titanium dioxide thin films with a rutile crystallinite size around 20 nm were fabricated by pulsed laser deposition (PLD) aided with an electron cyclotron resonance (ECR) plasma. With annealing treatment, the crystal size of the rutile crystallinite increased to 100 nm. The apatite-forming ability of the films as deposited and after annealing was investigated in a kind of simulated body fluid with ion concentrations nearly equal to those of human blood plasma. The results indicate that ECR aided PLD is an effective way both to fabricate bioactive titanium dioxide thin films and to optimize the bioactivity of titanium dioxide, with both crystal size and defects of the film taken into account.

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Carbon nanotips have been synthesized from a thin carbon film deposited on silicon by bias-enhanced hot filament chemical vapor deposition under different process parameters. The results of scanning electron microscopy indicate that high-quality carbon nanotips can only be obtained under conditions when the ion flux is effectively drawn from the plasma sustained in a CH4 + NH3 + H2 gas mixture. It is shown that the morphology of the carbon nanotips can be controlled by varying the process parameters such as the applied bias, gas pressure, and the NH3 / H2 mass flow ratios. The nanotip formation process is examined through a model that accounts for surface diffusion, in addition to sputtering and deposition processes included in the existing models. This model makes it possible to explain the major difference in the morphologies of the carbon nanotips formed without and with the aid of the plasma as well as to interpret the changes of their aspect ratio caused by the variation in the ion/gas fluxes. Viable ways to optimize the plasma-based process parameters to synthesize high-quality carbon nanotips are suggested. The results are relevant to the development of advanced plasma-/ion-assisted methods of nanoscale synthesis and processing.

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This paper reports on ab initio numerical simulations of the effect of Co and Cu dopings on the electronic structure and optical properties of ZnO, pursued to develop diluted magnetic semiconductors vitally needed for spintronic applications. The simulations are based upon the Perdew-Burke-Enzerh generalized gradient approximation on the density functional theory. It is revealed that the electrons with energies close to the Fermi level effectively transfer only between Cu and Co ions which substitute Zn atoms, and are located in the neighbor sites connected by an O ion. The simulation results are consistent with the experimental observations that addition of Cu helps achieve stable ferromagnetism of Co-doped ZnO. It is shown that simultaneous insertion of Co and Cu atoms leads to smaller energy band gap, redshift of the optical absorption edge, as well as significant changes in the reflectivity, dielectric function, refractive index, and electron energy loss function of ZnO as compared to the doping with either Co or Cu atoms. These highly unusual optical properties are explained in terms of the computed electronic structure and are promising for the development of the next-generation room-temperature ferromagnetic semiconductors for future spintronic devices on the existing semiconductor micromanufacturing platform.

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A high level of control over quantum dot (QD) properties such as size and composition during fabrication is required to precisely tune the eventual electronic properties of the QD. Nanoscale synthesis efforts and theoretical studies of electronic properties are traditionally treated quite separately. In this paper, a combinatorial approach has been taken to relate the process synthesis parameters and the electron confinement properties of the QDs. First, hybrid numerical calculations with different influx parameters for Si1-x Cx QDs were carried out to simulate the changes in carbon content x and size. Second, the ionization energy theory was applied to understand the electronic properties of Si1-x Cx QDs. Third, stoichiometric (x=0.5) silicon carbide QDs were grown by means of inductively coupled plasma-assisted rf magnetron sputtering. Finally, the effect of QD size and elemental composition were then incorporated in the ionization energy theory to explain the evolution of the Si1-x Cx photoluminescence spectra. These results are important for the development of deterministic synthesis approaches of self-assembled nanoscale quantum confinement structures.

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The effect of charged particulates or dusts on surface wave produced microwave discharges is studied. The frequencies of the standing electromagnetic eigenmodes of large-area flat plasmas are calculated. The dusts absorb a significant amount of the plasma electrons and can lead to a modification of the electromagnetic field structure in the discharge by shifting the originally excited operating mode out of resonance. For certain given proportions of dusts, mode conversion is found to be possible. The power loss in the discharge is also increased because of dust-specific dissipations, leading to a decrease of the operating mode quality factor.

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The effect of the film thickness and postannealing temperature on visible photoluminescence (PL) from Si Nx films synthesized by plasma-assisted radio frequency magnetron sputtering on Si O2 buffer layers is investigated. It is shown that strong visible PL is achieved at annealing temperatures above 650 °C. The optimum annealing temperature for the maximum PL yield strongly depends on the film thickness and varies from 800 to 1200°C. A comparative composition-structure-property analysis reveals that the PL intensity is directly related to the content of the Si-O and Si-N bonds in the Si Nx films. Therefore, sufficient oxidation and moderate nitridation of Si Nx Si O2 films during the plasma-based growth process are crucial for a strong PL yield. Excessively high annealing temperatures lead to weakened Si-N bonds in thinner Si Nx films, which eventually results in a lower PL intensity.

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The results of studies on the growth of high-aspect nanostructures in low-temperature non-equilibrium plasmas of reactive gas mixtures with or without hydrogen are presented. The results suggest that the hydrogen in the reactive plasma strongly affects the length of the nanostructures. This phenomenon is explained in terms of selective hydrogen passivation of the lateral and top surfaces of the surface-supported nanostructures. The theoretical model describes the effect of the atomic hydrogen passivation on the nanostructure shape and predicts the critical hydrogen coverage of the lateral surfaces necessary to achieve the nanostructure growth with the pre-determined shape. Our results demonstrate that the use of a strongly non-equilibrium plasma is very effective in significantly improving the shape control of quasi-one-dimensional single-crystalline nanostructures.

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The effect of near-sheath dusts on the rf power loss in a surface-wave-sustained gas discharge is studied. The planar plasma is bounded by a dielectric and consists of an inhomogeneous near-wall transition layer (sheath), a dusty plasma layer and an outer dust-free plasma. The discharge is maintained by high-frequency axially symmetrical surface waves. The surface-wave power loss from the most relevant dissipative mechanisms in typical discharge plasmas is analysed.

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The growth of carbon nanocone arrays on metal catalyst particles by deposition from a low-temperature plasma is studied by multiscale Monte Carlo/surface diffusion numerical simulation. It is demonstrated that the variation in the degree of ionization of the carbon flux provides an effective control of the growth kinetics of the carbon nanocones, and leads to the formation of more uniform arrays of nanostructures. In the case of zero degree of ionization (neutral gas process), a width of the distribution of nanocone heights reaches 360 nm with the nanocone mean height of 150 nm. When the carbon flux of 75% ionization is used, the width of the distribution of nanocone heights decreases to 100 nm, i.e., by a factor of 3.6. A higher degree of ionization leads to a better uniformity of the metal catalyst saturation and the nanocone growth, thus contributing to the formation of more height-uniform arrays of carbon nanostructures.

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The effect of ambipolar fluxes on nanoparticle charging in a typical low-pressure parallel-plate glow discharge is considered. It is shown that the equilibrium values of the nanoparticle charge in the plasma bulk and near-electrode areas are strongly affected by the ratio S ath i of the ambipolar flux and the ion thermal velocities. Under typical experimental conditions the above ratio is neither S ath i≪ 1 nor S ath i≫1, which often renders the commonly used approximations of the purely thermal or "ion wind" ion charging currents inaccurate. By using the general approximation for the ambipolar drift-affected ion flux on the nanoparticle surface, it appears possible to obtain more accurate values of the nanoparticle charge that usually deviate within 10-25 % from the values obtained without a proper accounting for the ambipolar ion fluxes. The implications of the results obtained for glow discharge modeling and nanoparticle manipulation in low-pressure plasmas are discussed.

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The effects of an inductively rotating current were observed on low-frequency inductively coupled plasmas. The spatial distribution of electromagnetic fields was investigated in a cylindrical metallic chamber filled with dense plasma. The distribution of the magnetic field in plasma chamber was observed for rarefied and dense plasmas. The plasma was assumed as uniform in the electromagnetic fields. The results showed the plasma density increased with power and the electron density increased with pressure.

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Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

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Previous behavioral studies reported a robust effect of increased naming latencies when objects to be named were blocked within semantic category, compared to items blocked between category. This semantic context effect has been attributed to various mechanisms including inhibition or excitation of lexico-semantic representations and incremental learning of associations between semantic features and names, and is hypothesized to increase demands on verbal self-monitoring during speech production. Objects within categories also share many visual structural features, introducing a potential confound when interpreting the level at which the context effect might occur. Consistent with previous findings, we report a significant increase in response latencies when naming categorically related objects within blocks, an effect associated with increased perfusion fMRI signal bilaterally in the hippocampus and in the left middle to posterior superior temporal cortex. No perfusion changes were observed in the middle section of the left middle temporal cortex, a region associated with retrieval of lexical-semantic information in previous object naming studies. Although a manipulation of visual feature similarity did not influence naming latencies, we observed perfusion increases in the perirhinal cortex for naming objects with similar visual features that interacted with the semantic context in which objects were named. These results provide support for the view that the semantic context effect in object naming occurs due to an incremental learning mechanism, and involves increased demands on verbal self-monitoring.