88 resultados para GRAINS


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The response of complex ionized gas systems to the presence of nonuniform distribution of charged grains is investigated using a kinetic model. Contrary to an existing view that the electron temperature inevitably increases in the grain-occupied region because of enhanced ionization to compensate for the electrons lost to the grains, it is shown that this happens only when the ionizing electric field increases in the electron depleted region. The results for two typical plasma systems suggest that when the ionizing electric field depends on the spatially averaged electron density, the electron temperature in the grain containing region can actually decrease.

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A global, or averaged, model for complex low-pressure argon discharge plasmas containing dust grains is presented. The model consists of particle and power balance equations taking into account power loss on the dust grains and the discharge wall. The electron energy distribution is determined by a Boltzmann equation. The effects of the dust and the external conditions, such as the input power and neutral gas pressure, on the electron energy distribution, the electron temperature, the electron and ion number densities, and the dust charge are investigated. It is found that the dust subsystem can strongly affect the stationary state of the discharge by dynamically modifying the electron energy distribution, the electron temperature, the creation and loss of the plasma particles, as well as the power deposition. In particular, the power loss to the dust grains can take up a significant portion of the input power, often even exceeding the loss to the wall.

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A model for electronegative plasmas containing charged dust or colloidal grains was used. Numerical solutions based on the model demonstrate how a low-pressure diffusion equilibrium of the complex electronegative plasma system is dynamically sustained through plasma particle sources.

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Experimentally observed optical and photoelectrical spectra of nitrogen-contaminated (unintentionally doped) nano-crystalline CVD diamond films are simulated using semi-empirical adiabatic General Skettrup Model (GSM), which presumes dominant contributions of defect states from sp 3-coordinated intra-granular carbon atoms to intra-band single electron spectrum N(E) of the material. This picture disagrees with a common viewpoint that the N(E) spectrum of the gap states in diamond powders and polycrystalline CVD films mainly originates from π and π* bonds of sp2-coordinated carbon atoms, which are distributed nearly uniformly over outer surfaces and/or interfaces of the diamond grains. The GSM predicts as well strong effect of granular morphology on the density of intra-band defect states in polycrystalline diamonds.

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Al-C-N-O composite thin films have been synthesized by radio frequency reactive diode sputtering of an aluminum target in plasmas of N2+O2+CH4 gas mixtures. The chemical structure and composition of the films have been investigated by means of infrared and X-ray photoelectron spectroscopy. The results reveal the formation of C-N, Al-C, Al-N and Al-O bonds. The X-ray diffraction pattern suggests that the films are of nanometer composite material and contain predominately crystalline grains of hexagonal AlN and α-Al2O3. A good thermal stability of the composite has been confirmed by the annealing treatment at temperatures up to 600 °C.

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The effect of density and size of dust grains on the electron energy distribution function (EEDF) in low-temperature complex plasmas is studied. It is found that the EEDF depends strongly on the dust density and size. The behavior of the electron temperature can differ significantly from that of a pristine plasma. For low-pressure argon glow discharge, the Druyvesteyn-like EEDF often found in pristine plasmas can become nearly Maxwellian if the dust density and/or sizes are large. One can thus control the plasma parameters by the dust grains.

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Negative ions and negatively charged micro- to nano-meter sized dust grains are ubiquitous in astrophysical as well as industrial processing plasmas. The negative ions can appear in electro-negative plasmas as a result of elementary processes such as dissociative or non-dissociative electron attachment to neutrals. They are usually rather small in number, and in general do not affect the overall plasma behavior. On the other hand, since the dust grains are almost always highly negative, even in small numbers they can take up a considerable proportion of the total negative charge in the system. The presence of dusts can affect the characteristics of most collective processes of the plasma since the charge balance in both the steady and dynamic states can be significantly altered. Another situation that often occurs is that the electron number density becomes small because of their absorption by the dust grains or the discharge walls. In this case the negative ions in the plasma can play a very important role. Here, a self-consistent theory of linear waves in complex laboratory plasmas containing dust grains and negative ions is presented. A comprehensive model for such plasmas including source and sink effects associated with the presence of dust grains and negative ions is introduced. The stationary state of the plasma as well as the dispersion and damping characteristics of the waves are investigated. All relevant processes, such as ionization, diffusion, electron attachment, negative-positive ion recombination, dust charge relaxation, and dissipation due to electron and ion elastic collisions with neutrals and dust particles, as well as charging collisions with the dusts, are taken into consideration.

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The current-driven dust ion-acoustic instability in a collisional dusty plasma is studied. The effects of dust-charge variation, electron and ion capture by the dust grains, as well as various dissipative mechanisms leading to the changes of the particles momenta, are taken into account. It is shown that the threshold for the excitation of the dust ion-acoustic waves can be high because of the large dissipation rate induced by the dusts. © 1999 American Institute of Physics.

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A donor-acceptor polymer semiconductor, PDQT, comprising diketopyrrolopyrrole (DPP) and β-unsubstituted quaterthiophene (QT) for organic thin film transistors (OTFTs) is reported. This polymer forms ordered layer-by-layer lamellar packing with an edge-on orientation in thin films even without thermal annealing. The strong intermolecular interactions arising from the fused aromatic DPP moiety and the DPP-QT donor-acceptor interaction facilitate the spontaneous self-assembly of the polymer chains into close proximity and form a large π-π overlap, which are favorable for intermolecular charge hopping. The well-interconnected crystalline grains form efficient intergranular charge transport pathways. The desirable chemical, electronic, and morphological structures of PDQT bring about high hole mobility of up to 0.97 cm2/(V·s) in OTFTs with polymer thin films annealed at a mild temperature of 100 °C and similarly high mobility of 0.89 cm2/(V·s) for polymer thin films even without thermal annealing.

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Detailed knowledge of the past history of an active volcano is crucial for the prediction of the timing, frequency and style of future eruptions, and for the identification of potentially at-risk areas. Subaerial volcanic stratigraphies are often incomplete, due to a lack of exposure, or burial and erosion from subsequent eruptions. However, many volcanic eruptions produce widely-dispersed explosive products that are frequently deposited as tephra layers in the sea. Cores of marine sediment therefore have the potential to provide more complete volcanic stratigraphies, at least for explosive eruptions. Nevertheless, problems such as bioturbation and dispersal by currents affect the preservation and subsequent detection of marine tephra deposits. Consequently, cryptotephras, in which tephra grains are not sufficiently concentrated to form layers that are visible to the naked eye, may be the only record of many explosive eruptions. Additionally, thin, reworked deposits of volcanic clasts transported by floods and landslides, or during pyroclastic density currents may be incorrectly interpreted as tephra fallout layers, leading to the construction of inaccurate records of volcanism. This work uses samples from the volcanic island of Montserrat as a case study to test different techniques for generating volcanic eruption records from marine sediment cores, with a particular relevance to cores sampled in relatively proximal settings (i.e. tens of kilometres from the volcanic source) where volcaniclastic material may form a pervasive component of the sedimentary sequence. Visible volcaniclastic deposits identified by sedimentological logging were used to test the effectiveness of potential alternative volcaniclastic-deposit detection techniques, including point counting of grain types (component analysis), glass or mineral chemistry, colour spectrophotometry, grain size measurements, XRF core scanning, magnetic susceptibility and X-radiography. This study demonstrates that a set of time-efficient, non-destructive and high-spatial-resolution analyses (e.g. XRF core-scanning and magnetic susceptibility) can be used effectively to detect potential cryptotephra horizons in marine sediment cores. Once these horizons have been sampled, microscope image analysis of volcaniclastic grains can be used successfully to discriminate between tephra fallout deposits and other volcaniclastic deposits, by using specific criteria related to clast morphology and sorting. Standard practice should be employed when analysing marine sediment cores to accurately identify both visible tephra and cryptotephra deposits, and to distinguish fallout deposits from other volcaniclastic deposits.

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This article analyses co-movements in a wide group of commodity prices during the time period 1992–2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co-movement of the commodity prices in our time sample, however from mid-2008 to the end of 2009 co-movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains, and oilseeds) and which have increased their degree of co-movement during the sampled period.

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Graphene/hexagonal boron nitride (G/h-BN) heterostructure has attracted tremendous research efforts owing to its great potential for applications in nano-scale electronic devices. In such hybrid materials, tilt grain boundaries (GBs) between graphene and h-BN grains may have unique physical properties, which have not been well understood. Here we have conducted non-equilibrium molecular dynamics simulations to study the energetic and thermal properties of tilt GBs in G/h-BN heterostructures. The effect of misorientation angles of tilt GBs on both GB energy and interfacial thermal conductance are investigated.

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We describe an investigation into how Massey University’s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University’s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder’s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.

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We describe an investigation into how Massey University's Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University's pollen reference collection (2890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set. In addition to the Classifynder's native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples. © 2013 AIP Publishing LLC.

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Three thousand liters of water were infiltrated from a 4 m diameter pond to track flow and transport inside fractured carbonates with 20-40 % porosity. Sixteen time-lapse 3D Ground Penetrating Radar (GPR) surveys with repetition intervals between 2 hrs and 5 days monitored the spreading of the water bulb in the subsurface. Based on local travel time shifts between repeated GPR survey pairs, localized changes of volumetric water content can be related to the processes of wetting, saturation and drainage. Deformation bands consisting of thin sub vertical sheets of crushed grains reduce the magnitude of water content changes but enhance flow in sheet parallel direction. This causes an earlier break through across a stratigraphic boundary compared to porous limestone without deformation bands. This experiment shows how time-lapse 3D GPR or 4D GPR can non-invasively track ongoing flow processes in rock-volumes of over 100 m3.