990 resultados para 020203 Particle Physics
Resumo:
Multiscale hybrid simulations that bridge the nine-order-of-magnitude spatial gap between the macroscopic plasma nanotools and microscopic surface processes on nanostructured solids are described. Two specific examples of carbon nanotip-like and semiconductor quantum dot nanopatterns are considered. These simulations are instrumental in developing physical principles of nanoscale assembly processes on solid surfaces exposed to low-temperature plasmas.
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Selective and controlled deposition of plasma-grown nanoparticles is one of the pressing problems of plasma-aided nanofabrication. The results of advanced numerical simulations of motion of charge-variable nanoparticles in the plasma presheath and sheath areas and in localized microscopic electric fields created by surface microstructures are reported. Conditions for site-selective deposition of such nanoparticles onto individual microstructures and open surface areas within a periodic micropattern are formulated. The effects of plasma parameters, surface potential, and micropattern features on nanoparticle deposition are investigated and explained using particle charging and plasma force arguments. The results are generic and applicable to a broad range of nanoparticle-generating plasmas and practical problems ranging from management of nanoparticle contamination in microelectronics to site-selective nanoparticle deposition into specified device locations, and synthesis of advanced microporous materials and nanoparticle superlattices. © 2007 American Institute of Physics.
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Manipulation of a single nanoparticle in the near-substrate areas of high-density plasmas of low-temperature glow discharges is studied. It is shown that the nanoparticles can be efficiently manipulated by the thermophoretic force controlled by external heating of the substrate stage. Particle deposition onto or repulsion from nanostructured carbon surfaces critically depends on the values of the neutral gas temperature gradient in the near-substrate areas, which is directly measured in situ in different heating regimes by originally developed temperature gradient probe. The measured values of the near-surface temperature gradient are used in the numerical model of nanoparticle dynamics in a variable-length presheath. Specific conditions enabling the nanoparticle to overcome the repulsive potential and deposit on the substrate during the discharge operation are investigated. The results are relevant to fabrication of various nanostructured films employing structural incorporation of the plasma-grown nanoparticles, in particular, to nanoparticle deposition in the plasma-enhanced chemical-vapor deposition of carbon nanostructures in hydrocarbon-based plasmas.
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The control of the generation and assembly of the electronegative plasma-grown particles is discussed. Due to the large number of elementary processes of particle creation and loss, electronegative complex plasmas should be treated as open systems where the stationary states are sustained by various particle creation and loss processes in the plasma bulk, on the walls, and on the dust grain surfaces. To be physically self-consistent, ionization, diffusion, electron attachment, recombination, dust charge variation, and dissipation due to electron and ion elastic collisions with neutrals and fine particles, as well as charging collisions with the dust, must be accounted for.
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An overview of dynamic self-organization phenomena in complex ionized gas systems, associated physical phenomena, and industrial applications is presented. The most recent experimental, theoretical, and modeling efforts to understand the growth mechanisms and dynamics of nano- and micron-sized particles, as well as the unique properties of the plasma-particle systems (colloidal, or complex plasmas) and the associated physical phenomena are reviewed and the major technological applications of micro- and nanoparticles are discussed. Until recently, such particles were considered mostly as a potential hazard for the microelectronic manufacturing and significant efforts were applied to remove them from the processing volume or suppress the gas-phase coagulation. Nowadays, fine clusters and particulates find numerous challenging applications in fundamental science as well as in nanotechnology and other leading high-tech industries.
Resumo:
Drying is a key processing techniques used in food engineering which demands continual developments on advanced analysis techniques in order to optimize the product and the process. In this regard, plant based materials are a frequent subject of interest where microstructural studies can provide a clearer understanding on the fundamental physical mechanisms involved. In this context, considering numerous challenges of using conventional numerical grid-based modelling techniques, a meshfree particle based model was developed to simulate extreme deformations of plant microstructure during drying. The proposed technique is based on a particle based meshfree method: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). A tissue model was developed by aggrading individual cells modelled with SPH-DEM coupled approach by initializing the cells as hexagons and aggregating them to form a tissue. The model also involves a middle lamella resembling real tissues. Using the model, different dried tissue states were simulated with different moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model is capable of simulating plant tissues at lower moisture contents which results in excessive shrinkage and cell wall wrinkling. Model predictions were compared with experimental findings and a fairly good agreement was observed both qualitatively and quantitatively.
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In recent years fine and ultra fine particles emitted from internal combustion engines have attracted an increasing level of attention. This attention has arisen from epidemiological studies conducted by a number of research groups and pointing to the health effects resulting from inhalation of fine particles. Previous studies on the influence of fuel sulfur level on diesel vehicle emissions were mainly concentrated on particle mass emissions. This study aims at investigating the influence of the reduction of diesel fuel sulfur level on the emission and formation of nanoparticles
Resumo:
An analysis of the emissions from 14 CNG and 5 Diesel buses was conducted during April & May, 2006. Studies were conducted at both steady state and transient driving modes on a vehicle dynamometer utilising a CVS dilution system. This article will focus on the volatile properties of particles from 4 CNG and 4 Diesel vehicles from within this group with a priority given to the previously un-investigated CNG emissions produced at transient loads. Particle number concentration data was collected by three CPC’s (TSI 3022, 3010 & 3782WCPC) having D50 cut-offs set to 5nm, 10nm & 20nm respectively. Size distribution data was collected using a TSI 3080 SMPS with a 3025 CPC during the steady state driving modes. During transient cycles mono-disperse “slices” of between 5nm & 25nm were measured. The volatility of these particles was determined by placing a thermodenuder before the 3022 and the SMPS and measuring the reduction in particle number concentration as the temperature in the thermodenuder was increased. This was then normalised against the total particle count given by the 3010 CPC to provide high resolution information on the reduction in particle concentration with respect to temperature.
Resumo:
Particle emission measurements from a fleet of 14 CNG and 5 Diesel buses were measured both for transient and steady state mode s on a chassis dynamometer with a CVS dilution system. Several transient DT80 cycles and 4 steady sate modes (0, 25, 50 100% of maximum load) were measured for each bus tested. Particle number concentration data was collected by three CPC’s (TSI 3022, 3010 3782WCPC) having D50 cut-offs set to 5, 10 and 20nm respectively. The size distributions were measured with a TSI 3080 SMPS with a 3025 CPC during the steady state modes. Particle mass emissions were measured with a TSI Dustrak. Particle mass emissions for Diesel buses were upto 2 orders of magnitude higher than for CNG buses. Particle number emissions during steady state modes for Diesel busses were 2 to 5 times higher than for CNG busses for all of the tested loads. On the other hand for the DT80 transient cycle particle number emissions were up to 3 times higher for the CNG buses. More detailed analysis of the transient cycles revealed that the reason for this was due to high particle number emissions from CNG busses during the acceleration parts of the cycles. Particles emitted by the CNG busses during acceleration were in the nucleation mode with the majority being smaller than 10nm. Volatility measurements have also shown that they were highly volatile.
Resumo:
Analysis of the particulate size and number concentration emissions from a fleet of inner city medium duty CNG buses was conducted using the newly available Diffusion Size Classifier in comparison with more traditional SMPS's and CPC's. Studies were conducted at both steady state and transient driving modes on a vehicle dynamometer utilising a CVS dilution system. Comparative analysis of the results showed that the DiSC provided equivalent information during steady state conditions and was able to provide additional information during transient conditions, namely, the modal diameter of the particle size distribution.
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We present a theoretical model describing a plasma-assisted growth of carbon nanofibers (CNFs), which involves two competing channels of carbon incorporation into stacked graphene sheets: via surface diffusion and through the bulk of the catalyst particle (on the top of the nanofiber), accounting for a range of ion- and radical-assisted processes on the catalyst surface. Using this model, it is found that at low surface temperatures, Ts, the CNF growth is indeed controlled by surface diffusion, thus quantifying the semiempirical conclusions of earlier experiments. On the other hand, both the surface and bulk diffusion channels provide a comparable supply of carbon atoms to the stacked graphene sheets at elevated synthesis temperatures. It is also shown that at low Ts, insufficient for effective catalytic precursor decomposition, the plasma ions play a key role in the production of carbon atoms on the catalyst surface. The model is used to compute the growth rates for the two extreme cases of thermal and plasma-enhanced chemical vapor deposition of CNFs. More importantly, these results quantify and explain a number of observations and semiempirical conclusions of earlier experiments.
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Corona discharge is responsible for the small ions found near overhead power lines, and these are capable of modifying the ambient electrical environment such as the dc electric field at ground level (Fews, Wilding et al. 2002). Once produced, small ions quickly attach to aerosol particles in the air, producing ‘large ions’ which are roughly 1 nm to 1 µm in diameter. However, very few studies have reported measurements of ions produced by power lines and its impact on particle charge concentrations. In this present study, the measurements were conducted as a function of normal downwind distance from a 275kV power line for investigating the effect of corona ions on air ions, aerosol particle charge concentration and dc e-filed.
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A simple, fast and low-cost atmospheric-pressure chemical vapor deposition technique is developed to synthesize high-yield carbon nanocoils (CNCs) using amorphous Co–P alloy as catalyst and thiophene as nucleation agent. The uniform catalyst pattern with the mean particle size of 350 nm was synthesized using a simple electroless plating process. This uniformity of the Co–P nanoparticles results in a high yield, very uniform size/shape distribution and regular structure of CNCs at the optimum growth temperature of 800 ◦C. The yield of CNCs reaches ∼76%; 70% of the CNCs have fiber diameters approximately 250 nm. The CNC coil diameters and lengths are 450–550nm and 0.5–2mm, respectively. The CNC nucleation and growth mechanism are also discussed.
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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.
Resumo:
A single plant cell was modeled with smoothed particle hydrodynamics (SPH) and a discrete element method (DEM) to study the basic micromechanics that govern the cellular structural deformations during drying. This two-dimensional particle-based model consists of two components: a cell fluid model and a cell wall model. The cell fluid was approximated to a highly viscous Newtonian fluid and modeled with SPH. The cell wall was treated as a stiff semi-permeable solid membrane with visco-elastic properties and modeled as a neo-Hookean solid material using a DEM. Compared to existing meshfree particle-based plant cell models, we have specifically introduced cell wall–fluid attraction forces and cell wall bending stiffness effects to address the critical shrinkage characteristics of the plant cells during drying. Also, a moisture domain-based novel approach was used to simulate drying mechanisms within the particle scheme. The model performance was found to be mainly influenced by the particle resolution, initial gap between the outermost fluid particles and wall particles and number of particles in the SPH influence domain. A higher order smoothing kernel was used with adaptive smoothing length to improve the stability and accuracy of the model. Cell deformations at different states of cell dryness were qualitatively and quantitatively compared with microscopic experimental findings on apple cells and a fairly good agreement was observed with some exceptions. The wall–fluid attraction forces and cell wall bending stiffness were found to be significantly improving the model predictions. A detailed sensitivity analysis was also done to further investigate the influence of wall–fluid attraction forces, cell wall bending stiffness, cell wall stiffness and the particle resolution. This novel meshfree based modeling approach is highly applicable for cellular level deformation studies of plant food materials during drying, which characterize large deformations.