998 resultados para PHYSICAL SCIENCES


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Snow cover is very sensitive to climate change and has a large feedback effect on the climate system due to the high albedo. Snow covers almost all surfaces in Antarctica and small changes in snow properties can mean large changes in absorbed radiation. In the ongoing discussion of climatic change, the mass balance of Antarctica has received increasing focus during recent decades, since its reaction to global warming strongly influences sea-level change. The aim of the present work was to examine the spatial and temporal variations in the physical and chemical characteristics of surface snow and annual accumulation rates in western Dronning Maud Land, Antarctica. The data were collected along a 350-km-long transect from the coast to the plateau during the years 1999-2004 as a part of the Finnish Antarctic Research Programme (FINNARP). The research focused on the most recent annual accumulation in the coastal area. The results show that the distance from the sea, and the moisture source, was the most predominant factor controlling the variations in both physical (conductivity, grain size, oxygen isotope ratio and accumulation) and chemical snow properties. The sea-salt and sulphur-containing components predominated in the coastal region. The local influences of nunataks and topographic highs were also visible on snow. The variations in all measured properties were wide within single sites mostly due to redistribution by winds and sastrugi topography, which reveals the importance of the spatially representative measurements. The mean accumulations occurred on the ice shelf, in the coastal region and on the plateau: 312 ± 28, 215 ± 43 and 92 ± 25 mm w.e., respectively. Depth hoar layers were usually found under the thin ice crust and were associated with a low dielectric constant and high concentrations of nitrate. Taking into account the vast size of the Antarctic ice sheet and its geographic characteristics, it is important to extend investigation of the distribution of surface snow properties and accumulation to provide well-documented data.

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Controlled nuclear fusion is one of the most promising sources of energy for the future. Before this goal can be achieved, one must be able to control the enormous energy densities which are present in the core plasma in a fusion reactor. In order to be able to predict the evolution and thereby the lifetime of different plasma facing materials under reactor-relevant conditions, the interaction of atoms and molecules with plasma first wall surfaces have to be studied in detail. In this thesis, the fundamental sticking and erosion processes of carbon-based materials, the nature of hydrocarbon species released from plasma-facing surfaces, and the evolution of the components under cumulative bombardment by atoms and molecules have been investigated by means of molecular dynamics simulations using both analytic potentials and a semi-empirical tight-binding method. The sticking cross-section of CH3 radicals at unsaturated carbon sites at diamond (111) surfaces is observed to decrease with increasing angle of incidence, a dependence which can be described by a simple geometrical model. The simulations furthermore show the sticking cross-section of CH3 radicals to be strongly dependent on the local neighborhood of the unsaturated carbon site. The erosion of amorphous hydrogenated carbon surfaces by helium, neon, and argon ions in combination with hydrogen at energies ranging from 2 to 10 eV is studied using both non-cumulative and cumulative bombardment simulations. The results show no significant differences between sputtering yields obtained from bombardment simulations with different noble gas ions. The final simulation cells from the 5 and 10 eV ion bombardment simulations, however, show marked differences in surface morphology. In further simulations the behavior of amorphous hydrogenated carbon surfaces under bombardment with D^+, D^+2, and D^+3 ions in the energy range from 2 to 30 eV has been investigated. The total chemical sputtering yields indicate that molecular projectiles lead to larger sputtering yields than atomic projectiles. Finally, the effect of hydrogen ion bombardment of both crystalline and amorphous tungsten carbide surfaces is studied. Prolonged bombardment is found to lead to the formation of an amorphous tungsten carbide layer, regardless of the initial structure of the sample. In agreement with experiment, preferential sputtering of carbon is observed in both the cumulative and non-cumulative simulations

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A better understanding of the limiting step in a first order phase transition, the nucleation process, is of major importance to a variety of scientific fields ranging from atmospheric sciences to nanotechnology and even to cosmology. This is due to the fact that in most phase transitions the new phase is separated from the mother phase by a free energy barrier. This barrier is crossed in a process called nucleation. Nowadays it is considered that a significant fraction of all atmospheric particles is produced by vapor-to liquid nucleation. In atmospheric sciences, as well as in other scientific fields, the theoretical treatment of nucleation is mostly based on a theory known as the Classical Nucleation Theory. However, the Classical Nucleation Theory is known to have only a limited success in predicting the rate at which vapor-to-liquid nucleation takes place at given conditions. This thesis studies the unary homogeneous vapor-to-liquid nucleation from a statistical mechanics viewpoint. We apply Monte Carlo simulations of molecular clusters to calculate the free energy barrier separating the vapor and liquid phases and compare our results against the laboratory measurements and Classical Nucleation Theory predictions. According to our results, the work of adding a monomer to a cluster in equilibrium vapour is accurately described by the liquid drop model applied by the Classical Nucleation Theory, once the clusters are larger than some threshold size. The threshold cluster sizes contain only a few or some tens of molecules depending on the interaction potential and temperature. However, the error made in modeling the smallest of clusters as liquid drops results in an erroneous absolute value for the cluster work of formation throughout the size range, as predicted by the McGraw-Laaksonen scaling law. By calculating correction factors to Classical Nucleation Theory predictions for the nucleation barriers of argon and water, we show that the corrected predictions produce nucleation rates that are in good comparison with experiments. For the smallest clusters, the deviation between the simulation results and the liquid drop values are accurately modelled by the low order virial coefficients at modest temperatures and vapour densities, or in other words, in the validity range of the non-interacting cluster theory by Frenkel, Band and Bilj. Our results do not indicate a need for a size dependent replacement free energy correction. The results also indicate that Classical Nucleation Theory predicts the size of the critical cluster correctly. We also presents a new method for the calculation of the equilibrium vapour density, surface tension size dependence and planar surface tension directly from cluster simulations. We also show how the size dependence of the cluster surface tension in equimolar surface is a function of virial coefficients, a result confirmed by our cluster simulations.

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In recent years there has been growing interest in selecting suitable wood raw material to increase end product quality and to increase the efficiency of industrial processes. Genetic background and growing conditions are known to affect properties of growing trees, but only a few parameters reflecting wood quality, such as volume and density can be measured on an industrial scale. Therefore research on cellular level structures of trees grown in different conditions is needed to increase understanding of the growth process of trees leading to desired wood properties. In this work the cellular and cell wall structures of wood were studied. Parameters, such as the mean microfibril angle (MFA), the spiral grain angles, the fibre length, the tracheid cell wall thickness and the cross-sectional shape of the tracheid, were determined as a function of distance from the pith towards the bark and mutual dependencies of these parameters were discussed. Samples from fast-grown trees, which belong to a same clone, grown in fertile soil and also from fertilised trees were measured. It was found that in fast-grown trees the mean MFA decreased more gradually from the pith to the bark than in reference stems. In fast-grown samples cells were shorter, more thin-walled and their cross-sections were rounder than in slower-grown reference trees. Increased growth rate was found to cause an increase in spiral grain variation both within and between annual rings. Furthermore, methods for determination of the mean MFA using x-ray diffraction were evaluated. Several experimental arrangements including the synchrotron radiation based microdiffraction were compared. For evaluation of the data analysis procedures a general form for diffraction conditions in terms of angles describing the fibre orientation and the shape of the cell was derived. The effects of these parameters on the obtained microfibril angles were discussed. The use of symmetrical transmission geometry and tangentially cut samples gave the most reliable MFA values.

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To a large extent, lakes can be described with a one-dimensional approach, as their main features can be characterized by the vertical temperature profile of the water. The development of the profiles during the year follows the seasonal climate variations. Depending on conditions, lakes become stratified during the warm summer. After cooling, overturn occurs, water cools and an ice cover forms. Typically, water is inversely stratified under the ice, and another overturn occurs in spring after the ice has melted. Features of this circulation have been used in studies to distinguish between lakes in different areas, as basis for observation systems and even as climate indicators. Numerical models can be used to calculate temperature in the lake, on the basis of the meteorological input at the surface. The simple form is to solve the surface temperature. The depth of the lake affects heat transfer, together with other morphological features, the shape and size of the lake. Also the surrounding landscape affects the formation of the meteorological fields over the lake and the energy input. For small lakes the shading by the shores affects both over the lake and inside the water body bringing limitations for the one-dimensional approach. A two-layer model gives an approximation for the basic stratification in the lake. A turbulence model can simulate vertical temperature profile in a more detailed way. If the shape of the temperature profile is very abrupt, vertical transfer is hindered, having many important consequences for lake biology. One-dimensional modelling approach was successfully studied comparing a one-layer model, a two-layer model and a turbulence model. The turbulence model was applied to lakes with different sizes, shapes and locations. Lake models need data from the lakes for model adjustment. The use of the meteorological input data on different scales was analysed, ranging from momentary turbulent changes over the lake to the use of the synoptical data with three hour intervals. Data over about 100 past years were used on the mesoscale at the range of about 100 km and climate change scenarios for future changes. Increasing air temperature typically increases water temperature in epilimnion and decreases ice cover. Lake ice data were used for modelling different kinds of lakes. They were also analyzed statistically in global context. The results were also compared with results of a hydrological watershed model and data from very small lakes for seasonal development.

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The ever-increasing demand for faster computers in various areas, ranging from entertaining electronics to computational science, is pushing the semiconductor industry towards its limits on decreasing the sizes of electronic devices based on conventional materials. According to the famous law by Gordon E. Moore, a co-founder of the world s largest semiconductor company Intel, the transistor sizes should decrease to the atomic level during the next few decades to maintain the present rate of increase in the computational power. As leakage currents become a problem for traditional silicon-based devices already at sizes in the nanometer scale, an approach other than further miniaturization is needed to accomplish the needs of the future electronics. A relatively recently proposed possibility for further progress in electronics is to replace silicon with carbon, another element from the same group in the periodic table. Carbon is an especially interesting material for nanometer-sized devices because it forms naturally different nanostructures. Furthermore, some of these structures have unique properties. The most widely suggested allotrope of carbon to be used for electronics is a tubular molecule having an atomic structure resembling that of graphite. These carbon nanotubes are popular both among scientists and in industry because of a wide list of exciting properties. For example, carbon nanotubes are electronically unique and have uncommonly high strength versus mass ratio, which have resulted in a multitude of proposed applications in several fields. In fact, due to some remaining difficulties regarding large-scale production of nanotube-based electronic devices, fields other than electronics have been faster to develop profitable nanotube applications. In this thesis, the possibility of using low-energy ion irradiation to ease the route towards nanotube applications is studied through atomistic simulations on different levels of theory. Specifically, molecular dynamic simulations with analytical interaction models are used to follow the irradiation process of nanotubes to introduce different impurity atoms into these structures, in order to gain control on their electronic character. Ion irradiation is shown to be a very efficient method to replace carbon atoms with boron or nitrogen impurities in single-walled nanotubes. Furthermore, potassium irradiation of multi-walled and fullerene-filled nanotubes is demonstrated to result in small potassium clusters in the hollow parts of these structures. Molecular dynamic simulations are further used to give an example on using irradiation to improve contacts between a nanotube and a silicon substrate. Methods based on the density-functional theory are used to gain insight on the defect structures inevitably created during the irradiation. Finally, a new simulation code utilizing the kinetic Monte Carlo method is introduced to follow the time evolution of irradiation-induced defects on carbon nanotubes on macroscopic time scales. Overall, the molecular dynamic simulations presented in this thesis show that ion irradiation is a promisingmethod for tailoring the nanotube properties in a controlled manner. The calculations made with density-functional-theory based methods indicate that it is energetically favorable for even relatively large defects to transform to keep the atomic configuration as close to the pristine nanotube as possible. The kinetic Monte Carlo studies reveal that elevated temperatures during the processing enhance the self-healing of nanotubes significantly, ensuring low defect concentrations after the treatment with energetic ions. Thereby, nanotubes can retain their desired properties also after the irradiation. Throughout the thesis, atomistic simulations combining different levels of theory are demonstrated to be an important tool for determining the optimal conditions for irradiation experiments, because the atomic-scale processes at short time scales are extremely difficult to study by any other means.