965 resultados para Diffusion Processes
Resumo:
The efficiency of the charge-carrier photogeneration processes in poly(2,5-bis(3',7'-dimethyl-octyloxy)-1,4-phenylene vinylene) (OC(1)OC10-PPV) has been analyzed by the spectral response of the photocurrent of devices in ITO/polymer/Al structures. The symbatic response of the photocurrent action spectra of the OC1OC10-PPV devices, obtained for light-excitation through the ITO electrode and for forward bias, has been fitted using a phenomenological model which considers that the predominant transport mechanism under external applied electric field is the drift of photogenerated charge-carriers, neglecting charge-carrier diffusion. The proposed model takes into account that charge-carrier photogeneration occurs via intermediate stages of bounded pairs (excitonic states), followed by dissociation processes. Such processes result in two different contributions to the photoconductivity: The first one, associated to direct creation of unbound polaron pairs due to intrinsic photoionization; and the second one is associated to secondary processes like extrinsic photoinjection at the metallic electrodes. The results obtained from the model have shown that the intrinsic component of the photoconductivity at higher excitation energies has a considerably higher efficiency than the extrinsic one, suggesting a dependence on the photon energy for the efficiency of the photogeneration process.
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We developed a stochastic lattice model to describe the vector-borne disease (like yellow fever or dengue). The model is spatially structured and its dynamical rules take into account the diffusion of vectors. We consider a bipartite lattice, forming a sub-lattice of human and another occupied by mosquitoes. At each site of lattice we associate a stochastic variable that describes the occupation and the health state of a single individual (mosquito or human). The process of disease transmission in the human population follows a similar dynamic of the Susceptible-Infected-Recovered model (SIR), while the disease transmission in the mosquito population has an analogous dynamic of the Susceptible-Infected-Susceptible model (SIS) with mosquitos diffusion. The occurrence of an epidemic is directly related to the conditional probability of occurrence of infected mosquitoes (human) in the presence of susceptible human (mosquitoes) on neighborhood. The probability of diffusion of mosquitoes can facilitate the formation of pairs Susceptible-Infected enabling an increase in the size of the epidemic. Using an asynchronous dynamic update, we study the disease transmission in a population initially formed by susceptible individuals due to the introduction of a single mosquito (human) infected. We find that this model exhibits a continuous phase transition related to the existence or non-existence of an epidemic. By means of mean field approximations and Monte Carlo simulations we investigate the epidemic threshold and the phase diagram in terms of the diffusion probability and the infection probability.
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The use of Magnetic Resonance Imaging (MRI) as a diagnostic tool is increasingly employing functional contrast agents to study or contrast entire mechanisms. Contrast agents in MRI can be classified in two categories. One type of contrast agents alters the NMR signal of the protons in its surrounding, e.g. lowers the T1 relaxation time. The other type enhances the Nuclear Magnetic Resonance (NMR) signal of specific nuclei. For hyperpolarized gases the NMR signal is improved up to several orders of magnitude. However, gases have a high diffusivity which strongly influences the NMR signal strength, hence the resolution and appearance of the images. The most interesting question in spatially resolved experiments is of course the achievable resolution and contrast by controlling the diffusivity of the gas. The influence of such diffusive processes scales with the diffusion coefficient, the strength of the magnetic field gradients and the timings used in the experiment. Diffusion may not only limit the MRI resolution, but also distort the line shape of MR images for samples, which contain boundaries or diffusion barriers within the sampled space. In addition, due to the large polarization in gaseous 3He and 129Xe, spin diffusion (different from particle diffusion) could play a role in MRI experiments. It is demonstrated that for low temperatures some corrections to the NMR measured diffusion coefficient have to be done, which depend on quantum exchange effects for indistinguishable particles. Physically, if these effects can not change the spin current, they can do it indirectly by modifying the velocity distribution of the different spin states separately, so that the subsequent collisions between atoms and therefore the diffusion coefficient can eventually be affected. A detailed study of the hyperpolarized gas diffusion coefficient is presented, demonstrating the absence of spin diffusion (different from particle diffusion) influence in MRI at clinical conditions. A novel procedure is proposed to control the diffusion coefficient of gases in MRI by admixture of inert buffer gases. The experimental measured diffusion agrees with theoretical simulations. Therefore, the molecular mass and concentration enter as additional parameters into the equations that describe structural contrast. This allows for setting a structural threshold up to which structures contribute to the image. For MRI of the lung this allows for images of very small structural elements (alveoli) only, or in the other extreme, all airways can be displayed with minimal signal loss due to diffusion.
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In this thesis we consider systems of finitely many particles moving on paths given by a strong Markov process and undergoing branching and reproduction at random times. The branching rate of a particle, its number of offspring and their spatial distribution are allowed to depend on the particle's position and possibly on the configuration of coexisting particles. In addition there is immigration of new particles, with the rate of immigration and the distribution of immigrants possibly depending on the configuration of pre-existing particles as well. In the first two chapters of this work, we concentrate on the case that the joint motion of particles is governed by a diffusion with interacting components. The resulting process of particle configurations was studied by E. Löcherbach (2002, 2004) and is known as a branching diffusion with immigration (BDI). Chapter 1 contains a detailed introduction of the basic model assumptions, in particular an assumption of ergodicity which guarantees that the BDI process is positive Harris recurrent with finite invariant measure on the configuration space. This object and a closely related quantity, namely the invariant occupation measure on the single-particle space, are investigated in Chapter 2 where we study the problem of the existence of Lebesgue-densities with nice regularity properties. For example, it turns out that the existence of a continuous density for the invariant measure depends on the mechanism by which newborn particles are distributed in space, namely whether branching particles reproduce at their death position or their offspring are distributed according to an absolutely continuous transition kernel. In Chapter 3, we assume that the quantities defining the model depend only on the spatial position but not on the configuration of coexisting particles. In this framework (which was considered by Höpfner and Löcherbach (2005) in the special case that branching particles reproduce at their death position), the particle motions are independent, and we can allow for more general Markov processes instead of diffusions. The resulting configuration process is a branching Markov process in the sense introduced by Ikeda, Nagasawa and Watanabe (1968), complemented by an immigration mechanism. Generalizing results obtained by Höpfner and Löcherbach (2005), we give sufficient conditions for ergodicity in the sense of positive recurrence of the configuration process and finiteness of the invariant occupation measure in the case of general particle motions and offspring distributions.
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Biosensors find wide application in clinical diagnostics, bioprocess control and environmental monitoring. They should not only show high specificity and reproducibility but also a high sensitivity and stability of the signal. Therefore, I introduce a novel sensor technology based on plasmonic nanoparticles which overcomes both of these limitations. Plasmonic nanoparticles exhibit strong absorption and scattering in the visible and near-infrared spectral range. The plasmon resonance, the collective coherent oscillation mode of the conduction band electrons against the positively charged ionic lattice, is sensitive to the local environment of the particle. I monitor these changes in the resonance wavelength by a new dark-field spectroscopy technique. Due to a strong light source and a highly sensitive detector a temporal resolution in the microsecond regime is possible in combination with a high spectral stability. This opens a window to investigate dynamics on the molecular level and to gain knowledge about fundamental biological processes.rnFirst, I investigate adsorption at the non-equilibrium as well as at the equilibrium state. I show the temporal evolution of single adsorption events of fibrinogen on the surface of the sensor on a millisecond timescale. Fibrinogen is a blood plasma protein with a unique shape that plays a central role in blood coagulation and is always involved in cell-biomaterial interactions. Further, I monitor equilibrium coverage fluctuations of sodium dodecyl sulfate and demonstrate a new approach to quantify the characteristic rate constants which is independent of mass transfer interference and long term drifts of the measured signal. This method has been investigated theoretically by Monte-Carlo simulations but so far there has been no sensor technology with a sufficient signal-to-noise ratio.rnSecond, I apply plasmonic nanoparticles as sensors for the determination of diffusion coefficients. Thereby, the sensing volume of a single, immobilized nanorod is used as detection volume. When a diffusing particle enters the detection volume a shift in the resonance wavelength is introduced. As no labeling of the analyte is necessary the hydrodynamic radius and thus the diffusion properties are not altered and can be studied in their natural form. In comparison to the conventional Fluorescence Correlation Spectroscopy technique a volume reduction by a factor of 5000-10000 is reached.
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Given its origins in traditional dialectology, and given advances in our understanding of the social embedding of language variation, it is paradoxical that space should be one of the categories that has received least attention of all in variationist sociolinguistics. Until recently, space has largely been treated as an empty stage on which sociolinguistic processes are enacted. It has been unexamined, untheorized, and its role in shaping and being shaped by variation and change untested. One function of this chapter, therefore, is to assert that space makes a difference, and to begin, in a very hesitant way, to map out what a geographically informed variation analysis might need to address. It also examines variationist interactions with the related concept of mobility. It might be reasonable to think that human geographers would provide some clues on how to proceed. As we will see, they have engaged in a great deal of soul searching about the goals of their discipline, its very existence as a separate field of enquiry, and the directions it should take. Indeed there are remarkable parallels between the recent history of human geographic thought, and interest in language variation across space. Although space has been undertheorized in variation studies, a number of researchers, from the traditional dialectologists through to those interested in the dialectology of mobility and contact, have, of course, been actively engaged in research on geographical variation and language use. Their work will be contextualized here to highlight both the parallels with theory-building in human geography, but also some of the criticisms of earlier approaches which have fed through to human geography, but remain largely unquestioned in variationist practice. The chapter therefore presents a brief theoretical background to space and mobility, before exemplifying these concepts in variationist research through an examination of, for example, the spatial diffusion of linguistic innovations, the spatial configuration of linguistic boundaries and initial steps to examine the consequences of mobility for variationist research.
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The migration of radioactive and chemical contaminants in clay materials and argillaceous host rocks is characterised by diffusion and retention processes. Valuable information on such processes can be gained by combining diffusion studies at laboratory scale with field migration tests. In this work, the outcome of a multi-tracer in situ migration test performed in the Opalinus Clay formation in the Mont Terri underground rock laboratory (Switzerland) is presented. Thus, 1.16 x 10(5) Bq/L of HTO, 3.96 x 10(3) Bq/L of Sr-85, 6.29 x 10(2) Bq/L of Co-60, 2.01 x 10(-3) mol/L Cs, 9.10 x 10(-4) mol/L I and 1.04 x 10(-3) mol/L Br were injected into the borehole. The decrease of the radioisotope concentrations in the borehole was monitored using in situ gamma-spectrometry. The other tracers were analyzed with state-of-the-art laboratory procedures after sampling of small water aliquots from the reservoir. The diffusion experiment was carried out over a period of one year after which the interval section was overcored and analyzed. Based on the experimental data from the tracer evolution in the borehole and the tracer profiles in the rock, the diffusion of tracers was modelled with the numerical code CRUNCH. The results obtained for HTO (H-3), I- and Br- confirm previous lab and in situ diffusion data. Anionic fluxes into the formation were smaller compared to HTO because of anion exclusion effects. The migration of the cations Sr-85(2+), Cs+ and Co-60(2+) was found to be governed by both diffusion and sorption processes. For Sr-85(2+), the slightly higher diffusivity relative to HTO and the low sorption value are consistent with laboratory diffusion measurements on small-scale samples. In the case of Cs+, the numerically deduced high diffusivity and the Freundlich-type sorption behaviour is also supported by ongoing laboratory data. For Co, no laboratory diffusion data were yet available for comparison; however, the modelled data suggests that Co-60(2+) sorption was weaker than would be expected from available batch sorption data. Overall, the results demonstrate the feasibility of the experimental setup for obtaining high-quality diffusion data for conservative and sorbing tracers. (C) 2007 Elsevier Ltd. All rights reserved.
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With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.
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In previous work, Alpine glaciers have been identified as a secondary source of persistent organic pollutants (POPs). However, detailed understanding of the processes organic chemicals undergo in a glacial system was missing. Here, we present results from a chemical fate model describing deposition and incorporation of polychlorinated biphenyls (PCBs) into an Alpine glacier (Fiescherhorn, Switzerland) and an Arctic glacier (Lomonosovfonna, Norway). To understand PCB fate and dynamics, we investigate the interaction of deposition, sorption to ice and particles in the atmosphere and within the glacier, revolatilization, diffusion and degradation, and discuss the effects of these processes on the fate of individual PCB congeners. The model is able to reproduce measured absolute concentrations in the two glaciers for most PCB congeners. While the model generally predicts concentration profiles peaking in the 1970s, in the measurements, this behavior can only be seen for higher-chlorinated PCB congeners on Fiescherhorn glacier. We suspect seasonal melt processes are disturbing the concentration profiles of the lower-chlorinated PCB congeners. While a lower-chlorinated PCB congener is mainly deposited by dry deposition and almost completely revolatilized after deposition, a higher-chlorinated PCB congener is predominantly transferred to the glacier surface by wet deposition and then is incorporated into the glacier ice. The incorporated amounts of PCBs are higher on the Alpine glacier than on the Arctic glacier due to the higher precipitation rate and aerosol particle concentration on the former. Future studies should include the effects of seasonal melt processes, calculate the quantities of PCBs incorporated into the entire glacier surface, and estimate the quantity of chemicals released from glaciers to determine the importance of glaciers as a secondary source of organic chemicals to remote aquatic ecosystems.
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Climate models predict more frequent and more severe extreme events (e.g., heat waves, extended drought periods, flooding) in many regions for the next decades. The impact of adverse environmental conditions on crop plants is ecologically and economically relevant. This review is focused on drought and heat effects on physiological status and productivity of agronomically important plants. Stomatal opening represents an important regulatory mechanism during drought and heat stress since it influences simultaneously water loss via transpiration and CO2 diffusion into the leaf apoplast which further is utilized in photosynthesis. Along with the reversible short-term control of stomatal opening, stomata and leaf epidermis may produce waxy deposits and irreversibly down-regulate the stomatal conductance and non-stomatal transpiration. As a consequence photosynthesis will be negatively affected. Rubisco activase—a key enzyme in keeping the Calvin cycle functional—is heat-sensitive and may become a limiting factor at elevated temperature. The accumulated reactive oxygen species (ROS) during stress represent an additional challenge under unfavorable conditions. Drought and heat cause accumulation of free amino acids which are partially converted into compatible solutes such as proline. This is accompanied by lower rates of both nitrate reduction and de novo amino acid biosynthesis. Protective proteins (e.g., dehydrins, chaperones, antioxidant enzymes or the key enzyme for proline biosynthesis) play an important role in leaves and may be present at higher levels under water deprivation or high temperatures. On the whole plant level, effects on long-distance translocation of solutes via xylem and phloem and on leaf senescence (e.g., anticipated, accelerated or delayed senescence) are important. The factors mentioned above are relevant for the overall performance of crops under drought and heat and must be considered for genotype selection and breeding programs.
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The spatial distributions of non-reactive natural tracers (anions, stable water isotopes, noble gases) in pore water of clay-rich formations were studied at nine sites. Regular curved profiles were identified in most cases. Transport modeling considering diffusion, advection and available constraints on the paleo-hydrogeological evolution indicates generally that diffusion alone can explain the observations, whereas a marked advective component would distort the profiles and so is not consistent with the data.
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This article provides importance sampling algorithms for computing the probabilities of various types ruin of spectrally negative Lévy risk processes, which are ruin over the infinite time horizon, ruin within a finite time horizon and ruin past a finite time horizon. For the special case of the compound Poisson process perturbed by diffusion, algorithms for computing probabilities of ruins by creeping (i.e. induced by the diffusion term) and by jumping (i.e. by a claim amount) are provided. It is shown that these algorithms have either bounded relative error or logarithmic efficiency, as t,x→∞t,x→∞, where t>0t>0 is the time horizon and x>0x>0 is the starting point of the risk process, with y=t/xy=t/x held constant and assumed either below or above a certain constant.
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Since no single experimental or modeling technique provides data that allow a description of transport processes in clays and clay minerals at all relevant scales, several complementary approaches have to be combined to understand and explain the interplay between transport relevant phenomena. In this paper molecular dynamics simulations (MD) were used to investigate the mobility of water in the interlayer of montmorillonite (Mt), and to estimate the influence of mineral surfaces and interlayer ions on the water diffusion. Random Walk (RW) simulations based on a simplified representation of pore space in Mt were used to estimate and understand the effect of the arrangement of Mt particles on the meso- to macroscopic diffusivity of water. These theoretical calculations were complemented with quasielastic neutron scattering (QENS) measurements of aqueous diffusion in Mt with two pseudo-layers of water performed at four significantly different energy resolutions (i.e. observation times). The size of the interlayer and the size of Mt particles are two characteristic dimensions which determine the time dependent behavior of water diffusion in Mt. MD simulations show that at very short time scales water dynamics has the characteristic features of an oscillatory motion in the cage formed by neighbors in the first coordination shell. At longer time scales, the interaction of water with the surface determines the water dynamics, and the effect of confinement on the overall water mobility within the interlayer becomes evident. At time scales corresponding to an average water displacement equivalent to the average size of Mt particles, the effects of tortuosity are observed in the meso- to macroscopic pore scale simulations. Consistent with the picture obtained in the simulations, the QENS data can be described using a (local) 3D diffusion at short observation times, whereas at sufficiently long observation times a 2D diffusive motion is clearly observed. The effects of tortuosity measured in macroscopic tracer diffusion experiments are in qualitative agreement with RW simulations. By using experimental data to calibrate molecular and mesoscopic theoretical models, a consistent description of water mobility in clay minerals from the molecular to the macroscopic scale can be achieved. In turn, simulations help in choosing optimal conditions for the experimental measurements and the data interpretation. (C) 2014 Elsevier B.V. All rights reserved.
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We study the real-time evolution of large open quantum spin systems in two spatial dimensions, whose dynamics is entirely driven by a dissipative coupling to the environment. We consider different dissipative processes and investigate the real-time evolution from an ordered phase of the Heisenberg or XY model towards a disordered phase at late times, disregarding unitary Hamiltonian dynamics. The corresponding Kossakowski-Lindblad equation is solved via an efficient cluster algorithm. We find that the symmetry of the dissipative process determines the time scales, which govern the approach towards a new equilibrium phase at late times. Most notably, we find a slow equilibration if the dissipative process conserves any of the magnetization Fourier modes. In these cases, the dynamics can be interpreted as a diffusion process of the conserved quantity.