84 resultados para Dynamics of pollutant removal

em Cambridge University Engineering Department Publications Database


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Thin film transistors (TFTs) utilizing an hydrogenated amorphous silicon (a-Si:H) channel layer exhibit a shift in the threshold voltage with time under the application of a gate bias voltage due to the creation of metastable defects. These defects are removed by annealing the device with zero gate bias applied. The defect removal process can be characterized by a thermalization energy which is, in turn, dependent upon an attempt-to-escape frequency for defect removal. The threshold voltage of both hydrogenated and deuterated amorphous silicon (a-Si:D) TFTs has been measured as a function of annealing time and temperature. Using a molecular dynamics simulation of hydrogen and deuterium in a silicon network in the H2 * configuration, it is shown that the experimental results are consistent with an attempt-to-escape frequency of (4.4 ± 0.3) × 1013 Hz and (5.7 ± 0.3) × 1013 Hz for a-Si:H and a-Si:D respectively which is attributed to the oscillation of the Si-H and Si-D bonds. Using this approach, it becomes possible to describe defect removal in hydrogenated and deuterated material by the thermalization energies of (1.552 ± 0.003) eV and (1.559 ± 0.003) eV respectively. This correlates with the energy per atom of the Si-H and Si-D bonds. © 2006 Elsevier B.V. All rights reserved.

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The physicochemical and droplet impact dynamics of superhydrophobic carbon nanotube arrays are investigated. These superhydrophobic arrays are fabricated simply by exposing the as-grown carbon nanotube arrays to a vacuum annealing treatment at a moderate temperature. This treatment, which allows a significant removal of oxygen adsorbates, leads to a dramatic change in wettability of the arrays, from mildly hydrophobic to superhydrophobic. Such change in wettability is also accompanied by a substantial change in surface charge and electrochemical properties. Here, the droplet impact dynamics are characterized in terms of critical Weber number, coefficient of restitution, spreading factor, and contact time. Based on these characteristics, it is found that superhydrophobic carbon nanotube arrays are among the best water-repellent surfaces ever reported. The results presented herein may pave a way for the utilization of superhydrophobic carbon nanotube arrays in numerous industrial and practical applications, including inkjet printing, direct injection engines, steam turbines, and microelectronic fabrication.

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An understanding of within-host dynamics of pathogen interactions with eukaryotic cells can shape the development of effective preventive measures and drug regimes. Such investigations have been hampered by the difficulty of identifying and observing directly, within live tissues, the multiple key variables that underlay infection processes. Fluorescence microscopy data on intracellular distributions of Salmonella enterica serovar Typhimurium (S. Typhimurium) show that, while the number of infected cells increases with time, the distribution of bacteria between cells is stationary (though highly skewed). Here, we report a simple model framework for the intensity of intracellular infection that links the quasi-stationary distribution of bacteria to bacterial and cellular demography. This enables us to reject the hypothesis that the skewed distribution is generated by intrinsic cellular heterogeneities, and to derive specific predictions on the within-cell dynamics of Salmonella division and host-cell lysis. For within-cell pathogens in general, we show that within-cell dynamics have implications across pathogen dynamics, evolution, and control, and we develop novel generic guidelines for the design of antibacterial combination therapies and the management of antibiotic resistance.

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Mechanistic determinants of bacterial growth, death, and spread within mammalian hosts cannot be fully resolved studying a single bacterial population. They are also currently poorly understood. Here, we report on the application of sophisticated experimental approaches to map spatiotemporal population dynamics of bacteria during an infection. We analyzed heterogeneous traits of simultaneous infections with tagged Salmonella enterica populations (wild-type isogenic tagged strains [WITS]) in wild-type and gene-targeted mice. WITS are phenotypically identical but can be distinguished and enumerated by quantitative PCR, making it possible, using probabilistic models, to estimate bacterial death rate based on the disappearance of strains through time. This multidisciplinary approach allowed us to establish the timing, relative occurrence, and immune control of key infection parameters in a true host-pathogen combination. Our analyses support a model in which shortly after infection, concomitant death and rapid bacterial replication lead to the establishment of independent bacterial subpopulations in different organs, a process controlled by host antimicrobial mechanisms. Later, decreased microbial mortality leads to an exponential increase in the number of bacteria that spread locally, with subsequent mixing of bacteria between organs via bacteraemia and further stochastic selection. This approach provides us with an unprecedented outlook on the pathogenesis of S. enterica infections, illustrating the complex spatial and stochastic effects that drive an infectious disease. The application of the novel method that we present in appropriate and diverse host-pathogen combinations, together with modelling of the data that result, will facilitate a comprehensive view of the spatial and stochastic nature of within-host dynamics. © 2008 Grant et al.

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An understanding of within-host dynamics of pathogen interactions with eukaryotic cells can shape the development of effective preventive measures and drug regimes. Such investigations have been hampered by the difficulty of identifying and observing directly, within live tissues, the multiple key variables that underlay infection processes. Fluorescence microscopy data on intracellular distributions of Salmonella enterica serovar Typhimurium (S. Typhimurium) show that, while the number of infected cells increases with time, the distribution of bacteria between cells is stationary (though highly skewed). Here, we report a simple model framework for the intensity of intracellular infection that links the quasi-stationary distribution of bacteria to bacterial and cellular demography. This enables us to reject the hypothesis that the skewed distribution is generated by intrinsic cellular heterogeneities, and to derive specific predictions on the within-cell dynamics of Salmonella division and host-cell lysis. For within-cell pathogens in general, we show that within-cell dynamics have implications across pathogen dynamics, evolution, and control, and we develop novel generic guidelines for the design of antibacterial combination therapies and the management of antibiotic resistance.

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