309 resultados para domain size


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The morphology of plasmonic nano-assemblies has a direct influence on optical properties, such as localised surface plasmon resonance (LSPR) and surface enhanced Raman scattering (SERS) intensity. Assemblies with core-satellite morphologies are of particular interest, because this morphology has a high density of hot-spots, while constraining the overall size. Herein, a simple method is reported for the self-assembly of gold NPs nano-assemblies with a core-satellite morphology, which was mediated by hyperbranched polymer (HBP) linkers. The HBP linkers have repeat units that do not interact strongly with gold NPs, but have multiple end-groups that specifically interact with the gold NPs and act as anchoring points resulting in nano-assemblies with a large (~48 nm) core surrounded by smaller (~15 nm) satellites. It was possible to control the number of satellites in an assembly which allowed optical parameters such as SPR maxima and the SERS intensity to be tuned. These results were found to be consistent with finite-difference time domain (FDTD) simulations. Furthermore, the multiplexing of the nano-assemblies with a series of Raman tag molecules was demonstrated, without an observable signal arising from the HBP linker after tagging. Such plasmonic nano-assemblies could potentially serve as efficient SERS based diagnostics or biomedical imaging agents in nanomedicine.

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A multiscale, multiphase thermokinetic model is used to show the effective control of the growth orientation of thin Si NWs for nanoelectronic devices enabled by nanoscale plasma chemistry. It is shown that very thin Si NWs with [110] growth direction can nucleate at much lower process temperatures and pressures compared to thermal chemical vapor deposition where [111]-directed Si NWs are predominantly grown. These findings explain a host of experimental results and offer the possibility of energy- and matter-efficient, size- and orientation-controlled growth of [110] Si NWs for next-generation nanodevices.

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The possibility of fast, narrow-size/chirality nucleation of thin single-walled carbon nanotubes (SWCNTs) at low, device-tolerant process temperatures in a plasma-enhanced chemical vapor deposition (CVD) is demonstrated using multiphase, multiscale numerical experiments. These effects are due to the unique nanoscale reactive plasma chemistry (NRPC) on the surfaces and within Au catalyst nanoparticles. The computed three-dimensional process parameter maps link the nanotube incubation times and the relative differences between the incubation times of SWCNTs of different sizes/chiralities to the main plasma- and precursor gas-specific parameters and explain recent experimental observations. It is shown that the unique NRPC leads not only to much faster nucleation of thin nanotubes at much lower process temperatures, but also to better selectivity between the incubation times of SWCNTs with different sizes and chiralities, compared to thermal CVD. These results are used to propose a time-programmed kinetic approach based on fast-responding plasmas which control the size-selective, narrow-chirality nucleation and growth of thin SWCNTs. This approach is generic and can be used for other nanostructure and materials systems.

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It is shown that plasmas can minimize the adverse Gibbs-Thompson effect in thin quantum wire growth. The model of Si nanowirenucleation includes the unprecedented combination of the plasma sheath, ion- and radical-induced species creation and heating effects on the surface and within an Au catalyst nanoparticle. Compared to neutral gas thermal processes, much thinner, size-selective wires can nucleate at the same temperature and pressure while much lower energy and matter budget is needed to grow same-size wires. This explains the experimental observations and may lead to energy- and matter-efficient synthesis of a broader range of one-dimensional quantum structures.

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We present results of computational simulations of tungsten-inert-gas and metal-inert-gas welding. The arc plasma and the electrodes (including the molten weld pool when necessary) are included self-consistently in the computational domain. It is shown, using three examples, that it would be impossible to accurately estimate the boundary conditions on the weld-pool surface without including the arc plasma in the computational domain. First, we show that the shielding gas composition strongly affects the properties of the arc that influence the weld pool: heat flux density, current density, shear stress and arc pressure at the weld-pool surface. Demixing is found to be important in some cases. Second, the vaporization of the weld-pool metal and the diffusion of the metal vapour into the arc plasma are found to decrease the heat flux density and current density to the weld pool. Finally, we show that the shape of the wire electrode in metal-inert-gas welding has a strong influence on flow velocities in the arc and the pressure and shear stress at the weld-pool surface. In each case, we present evidence that the geometry and depth of the weld pool depend strongly on the properties of the arc.

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A simple, effective, and innovative approach based on ion-assisted self-organization is proposed to synthesize size-selected Si quantum dots (QDs) on SiC substrates at low substrate temperatures. Using hybrid numerical simulations, the formation of Si QDs through a self-organization approach is investigated by taking into account two distinct cases of Si QD formation using the ionization energy approximation theory, which considers ionized in-fluxes containing Si3+ and Si1+ ions in the presence of a microscopic nonuniform electric field induced by a variable surface bias. The results show that the highest percentage of the surface coverage by 1 and 2 nm size-selected QDs was achieved using a bias of -20 V and ions in the lowest charge state, namely, Si1+ ions in a low substrate temperature range (227-327 °C). As low substrate temperatures (≤500 °C) are desirable from a technological point of view, because (i) low-temperature deposition techniques are compatible with current thin-film Si-based solar cell fabrication and (ii) high processing temperatures can frequently cause damage to other components in electronic devices and destroy the tandem structure of Si QD-based third-generation solar cells, our results are highly relevant to the development of the third-generation all-Si tandem photovoltaic solar cells.

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The results of large-scale (∼109 atoms) numerical simulations of the growth of different-diameter vertically-aligned single-walled carbon nanotubes in plasma systems with different sheath widths and in neutral gases with the same operating parameters are reported. It is shown that the nanotube lengths and growth rates can be effectively controlled by varying the process conditions. The SWCNT growth rates in the plasma can be up to two orders of magnitude higher than in the equivalent neutral gas systems. Under specific process conditions, thin SWCNTs can grow much faster than their thicker counterparts despite the higher energies required for catalyst activation and nanotube nucleation. This selective growth of thin SWCNTs opens new avenues for the solution of the currently intractable problem of simultaneous control of the nanotube chirality and length during the growth stage.

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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 kinetics of saturation of Ni catalyst nanoparticle patterns of the three different degrees of order, used as a model for the growth of carbon nanotips on Si, is investigated numerically using a complex model that involves surface diffusion and ion motion equations. It is revealed that Ni catalyst patterns of different degrees of order, with Ni nanoparticle sizes up to 12.5 nm, exhibit different kinetics of saturation with carbon on the Si surface. It is shown that in the cases examined (surface coverage in the range of 1-50%, highly disordered Ni patterns) the relative pattern saturation factor calculated as the ratio of average incubation times for the processes conducted in the neutral and ionized gas environments reaches 14 and 3.4 for Ni nanoparticles of 2.5 and 12.5 nm, respectively. In the highly ordered Ni patterns, the relative pattern saturation factor reaches 3 for nanoparticles of 2.5 nm and 2.1 for nanoparticles of 12.5 nm. Thus, more simultaneous saturation of Ni catalyst nanoparticles of sizes in the range up to 12.5 nm, deposited on the Si substrate, can be achieved in the low-temperature plasma environment than with the neutral gas-based process.

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Many properties of single-walled carbon nanotube (SWCNT) arrays are determined by the size and surface coverage of the metal catalyst islands from which they are nucleated. Methods using thermal fragmentation of continuous metal films frequently fail to produce size-uniform islands. Hybrid numerical simulations are used to propose a new approach to controlled self-assembly of Ni islands of the required size and surface coverage using tailored gas-phase generated nanocluster fluxes and adjusted surface temperatures. It is shown that a maximum surface coverage of 0.359 by 0.96-1.02 nm Ni catalyst islands can be achieved at a low surface temperature of 500 K. Optimized growth of Ni catalyst islands can lead to fabrication of size-uniform SWCNT arrays, suitable for numerous nanoelectronic applications. This approach is deterministic and is applicable to a range of nanoassemblies where high surface coverage and island size uniformity are required.

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Fault identification in industrial machine is a topic of major importance under engineering point of view. In fact, the possibility to identify not only the type, but also the severity and the position of a fault occurred along a shaft-line allows quick maintenance and shorten the downtime. This is really important in the power generation industry where the units are often of several tenths of meters long and where the rotors are enclosed by heavy and pressure-sealed casings. In this paper, an industrial experimental case is presented related to the identification of the unbalance on a large size steam turbine of about 1.3 GW, belonging to a nuclear power plant. The case history is analyzed by considering the vibrations measured by the condition monitoring system of the unit. A model-based method in the frequency domain, developed by the authors, is introduced in detail and it is then used to identify the position of the fault and its severity along the shaft-line. The complete model of the unit (rotor – modeled by means of finite elements, bearings – modeled by linearized damping and stiffness coefficients and foundation – modeled by means of pedestals) is analyzed and discussed before being used for the fault identification. The assessment of the actual fault was done by inspection during a scheduled maintenance and excellent correspondence was found with the identified one by means of authors’ proposed method. Finally a complete discussion is presented about the effectiveness of the method, even in presence of a not fine tuned machine model and considering only few measuring planes for the machine vibration.

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Our research aims to answer the research questions “How do we commonly describe the global start-ups profile as evidenced in prior inductive research?” and “Does this global start-ups profile can effectively explain phenomena in Australian global start-up firms?” We systematically review 29 global start-ups (144 firms) qualitative articles to understand descriptive definitions of global-startup firms. We then triangulate this finding with an Australian high-tech firm. Our contribution is to form a descriptive profile of global start-up phenomenon and raise interesting issues that have potentially fruitful findings for both research and practice. This profile might well be just a deviant from the traditional model that describes how firms establish their footprints, first in their domestic markets followed by moves into cross-border activities. Regardless, government agencies, consultants, and entrepreneurs need to understand the phenomenon. Thus we anticipate that this phenomenon will continue to provide interesting issues for pursuit, both by researchers as well as the practitioner community.

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The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared using samples of actual and simulated aerosol particle size distribution (PSD) data. Measurements of aerosol PSDs refer to the concentration of aerosol particles in terms of their size, which is typically multimodal in nature and collected at frequent time intervals. The use of informative priors is found to better identify component parameters at each time point and more clearly establish patterns in the parameters over time. Some caveats to this finding are discussed.

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With the increasing importance of Application Domain Specific Processor (ADSP) design, a significant challenge is to identify special-purpose operations for implementation as a customized instruction. While many methodologies have been proposed for this purpose, they all work for a single algorithm chosen from the target application domain. Such algorithm-specific approaches are not suitable for designing instruction sets applicable to a whole family of related algorithms. For an entire range of related algorithms, this paper develops a methodology for identifying compound operations, as a basis for designing “domain-specific” Instruction Set Architectures (ISAs) that can efficiently run most of the algorithms in a given domain. Our methodology combines three different static analysis techniques to identify instruction sequences common to several related algorithms: identification of (non-branching) instruction sequences that occur commonly across the algorithms; identification of instruction sequences nested within iterative constructs that are thus executed frequently; and identification of commonly-occurring instruction sequences that span basic blocks. Choosing different combinations of these results enables us to design domain-specific special operations with different desired characteristics, such as performance or suitability as a library function. To demonstrate our approach, case studies are carried out for a family of thirteen string matching algorithms. Finally, the validity of our static analysis results is confirmed through independent dynamic analysis experiments and performance improvement measurements.

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Aerial applications of granular insecticides are preferable because they can effectively penetrate vegetation, there is less drift, and no loss of product due to evaporation. We aimed to 1) assess the field efficacy ofVectoBac G to control Aedes vigilax (Skuse) in saltmarsh pools, 2) develop a stochastic-modeling procedure to monitor application quality, and 3) assess the distribution of VectoBac G after an aerial application. Because ground-based studies with Ae. vigilax immatures found that VectoBac G provided effective control below the recommended label rate of 7 kg/ha, we trialed a nominated aerial rate of 5 kg/ha as a case study. Our distribution pattern modeling method indicated that the variability in the number of VectoBac G particles captured in catch-trays was greater than expected for 5 kg/ha and that the widely accepted contour mapping approach to visualize the deposition pattern provided spurious results and therefore was not statistically appropriate. Based on the results of distribution pattern modeling, we calculated the catch tray size required to analyze the distribution of aerially applied granular formulations. The minimum catch tray size for products with large granules was 4 m2 for Altosid pellets and 2 m2 for VectoBac G. In contrast, the minimum catch-tray size for Altosid XRG, Aquabac G, and Altosand, with smaller granule sizes, was 1 m2. Little gain in precision would be made by increasing the catch-tray size further, when the increased workload and infrastructure is considered. Our improved methods for monitoring the distribution pattern of aerially applied granular insecticides can be adapted for use by both public health and agricultural contractors.