6 resultados para experimental techniques

em Helda - Digital Repository of University of Helsinki


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Thin film applications have become increasingly important in our search for multifunctional and economically viable technological solutions of the future. Thin film coatings can be used for a multitude of purposes, ranging from a basic enhancement of aesthetic attributes to the addition of a complex surface functionality. Anything from electronic or optical properties, to an increased catalytic or biological activity, can be added or enhanced by the deposition of a thin film, with a thickness of only a few atomic layers at the best, on an already existing surface. Thin films offer both a means of saving in materials and the possibility for improving properties without a critical enlargement of devices. Nanocluster deposition is a promising new method for the growth of structured thin films. Nanoclusters are small aggregates of atoms or molecules, ranging in sizes from only a few nanometers up to several hundreds of nanometers in diameter. Due to their large surface to volume ratio, and the confinement of atoms and electrons in all three dimensions, nanoclusters exhibit a wide variety of exotic properties that differ notably from those of both single atoms and bulk materials. Nanoclusters are a completely new type of building block for thin film deposition. As preformed entities, clusters provide a new means of tailoring the properties of thin films before their growth, simply by changing the size or composition of the clusters that are to be deposited. Contrary to contemporary methods of thin film growth, which mainly rely on the deposition of single atoms, cluster deposition also allows for a more precise assembly of thin films, as the configuration of single atoms with respect to each other is already predetermined in clusters. Nanocluster deposition offers a possibility for the coating of virtually any material with a nanostructured thin film, and therein the enhancement of already existing physical or chemical properties, or the addition of some exciting new feature. A clearer understanding of cluster-surface interactions, and the growth of thin films by cluster deposition, must, however, be achieved, if clusters are to be successfully used in thin film technologies. Using a combination of experimental techniques and molecular dynamics simulations, both the deposition of nanoclusters, and the growth and modification of cluster-assembled thin films, are studied in this thesis. Emphasis is laid on an understanding of the interaction between metal clusters and surfaces, and therein the behaviour of these clusters during deposition and thin film growth. The behaviour of single metal clusters, as they impact on clean metal surfaces, is analysed in detail, from which it is shown that there exists a cluster size and deposition energy dependent limit, below which epitaxial alignment occurs. If larger clusters are deposited at low energies, or cluster-surface interactions are weaker, non-epitaxial deposition will take place, resulting in the formation of nanocrystalline structures. The effect of cluster size and deposition energy on the morphology of cluster-assembled thin films is also determined, from which it is shown that nanocrystalline cluster-assembled films will be porous. Modification of these thin films, with the purpose of enhancing their mechanical properties and durability, without destroying their nanostructure, is presented. Irradiation with heavy ions is introduced as a feasible method for increasing the density, and therein the mechanical stability, of cluster-assembled thin films, without critically destroying their nanocrystalline properties. The results of this thesis demonstrate that nanocluster deposition is a suitable technique for the growth of nanostructured thin films. The interactions between nanoclusters and their supporting surfaces must, however, be carefully considered, if a controlled growth of cluster-assembled thin films, with precisely tailored properties, is to be achieved.

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Fusion energy is a clean and safe solution for the intricate question of how to produce non-polluting and sustainable energy for the constantly growing population. The fusion process does not result in any harmful waste or green-house gases, since small amounts of helium is the only bi-product that is produced when using the hydrogen isotopes deuterium and tritium as fuel. Moreover, deuterium is abundant in seawater and tritium can be bred from lithium, a common metal in the Earth's crust, rendering the fuel reservoirs practically bottomless. Due to its enormous mass, the Sun has been able to utilize fusion as its main energy source ever since it was born. But here on Earth, we must find other means to achieve the same. Inertial fusion involving powerful lasers and thermonuclear fusion employing extreme temperatures are examples of successful methods. However, these have yet to produce more energy than they consume. In thermonuclear fusion, the fuel is held inside a tokamak, which is a doughnut-shaped chamber with strong magnets wrapped around it. Once the fuel is heated up, it is controlled with the help of these magnets, since the required temperatures (over 100 million degrees C) will separate the electrons from the nuclei, forming a plasma. Once the fusion reactions occur, excess binding energy is released as energetic neutrons, which are absorbed in water in order to produce steam that runs turbines. Keeping the power losses from the plasma low, thus allowing for a high number of reactions, is a challenge. Another challenge is related to the reactor materials, since the confinement of the plasma particles is not perfect, resulting in particle bombardment of the reactor walls and structures. Material erosion and activation as well as plasma contamination are expected. Adding to this, the high energy neutrons will cause radiation damage in the materials, causing, for instance, swelling and embrittlement. In this thesis, the behaviour of a material situated in a fusion reactor was studied using molecular dynamics simulations. Simulations of processes in the next generation fusion reactor ITER include the reactor materials beryllium, carbon and tungsten as well as the plasma hydrogen isotopes. This means that interaction models, {\it i.e. interatomic potentials}, for this complicated quaternary system are needed. The task of finding such potentials is nonetheless nearly at its end, since models for the beryllium-carbon-hydrogen interactions were constructed in this thesis and as a continuation of that work, a beryllium-tungsten model is under development. These potentials are combinable with the earlier tungsten-carbon-hydrogen ones. The potentials were used to explain the chemical sputtering of beryllium due to deuterium plasma exposure. During experiments, a large fraction of the sputtered beryllium atoms were observed to be released as BeD molecules, and the simulations identified the swift chemical sputtering mechanism, previously not believed to be important in metals, as the underlying mechanism. Radiation damage in the reactor structural materials vanadium, iron and iron chromium, as well as in the wall material tungsten and the mixed alloy tungsten carbide, was also studied in this thesis. Interatomic potentials for vanadium, tungsten and iron were modified to be better suited for simulating collision cascades that are formed during particle irradiation, and the potential features affecting the resulting primary damage were identified. Including the often neglected electronic effects in the simulations was also shown to have an impact on the damage. With proper tuning of the electron-phonon interaction strength, experimentally measured quantities related to ion-beam mixing in iron could be reproduced. The damage in tungsten carbide alloys showed elemental asymmetry, as the major part of the damage consisted of carbon defects. On the other hand, modelling the damage in the iron chromium alloy, essentially representing steel, showed that small additions of chromium do not noticeably affect the primary damage in iron. Since a complete assessment of the response of a material in a future full-scale fusion reactor is not achievable using only experimental techniques, molecular dynamics simulations are of vital help. This thesis has not only provided insight into complicated reactor processes and improved current methods, but also offered tools for further simulations. It is therefore an important step towards making fusion energy more than a future goal.

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Hantaviruses, members of the genus Hantavirus in the Bunyaviridae family, are enveloped single-stranded RNA viruses with tri-segmented genome of negative polarity. In humans, hantaviruses cause two diseases, hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS), which vary in severity depending on the causative agent. Each hantavirus is carried by a specific rodent host and is transmitted to humans through excreta of infected rodents. The genome of hantaviruses encodes four structural proteins: the nucleocapsid protein (N), the glycoproteins (Gn and Gc), and the polymerase (L) and also the nonstructural protein (NSs). This thesis deals with the functional characterization of hantavirus N protein with regard to its structure. Structural studies of the N protein have progressed slowly and the crystal structure of the whole protein is still not available, therefore biochemical assays coupled with bioinformatical modeling proved essential for studying N protein structure and functions. Presumably, during RNA encapsidation, the N protein first forms intermediate trimers and then oligomers. First, we investigated the role of N-terminal domain in the N protein oligomerization. The results suggested that the N-terminal region of the N protein forms a coiled-coil, in which two antiparallel alpha helices interact via their hydrophobic seams. Hydrophobic residues L4, I11, L18, L25 and V32 in the first helix and L44, V51, L58 and L65 in the second helix were crucial for stabilizing the structure. The results were consistent with the head-to-head, tail-to-tail model for hantavirus N protein trimerization. We demonstrated that an intact coiled-coil structure of the N terminus is crucial for the oligomerization capacity of the N protein. We also added new details to the head-to-head, tail-to-tail model of trimerization by suggesting that the initial step is based on interaction(s) between intact intra-molecular coiled-coils of the monomers. We further analyzed the importance of charged aa residues located within the coiled-coil for the N protein oligomerization. To predict the interacting surfaces of the monomers we used an upgraded in silico model of the coiled-coil domain that was docked into a trimer. Next the predicted target residues were mutated. The results obtained using the mammalian two-hybrid assay suggested that conserved charged aa residues within the coiled-coil make a substantial contribution to the N protein oligomerization. This contribution probably involves the formation of interacting surfaces of the N monomers and also stabilization of the coiled-coil via intramolecular ionic bridging. We proposed that the tips of the coiled-coils are the first to come into direct contact and thus initiate tight packing of the three monomers into a compact structure. This was in agreement with the previous results showing that an increase in ionic strength abolished the interaction between N protein molecules. We also showed that residues having the strongest effect on the N protein oligomerization are not scattered randomly throughout the coiled-coil 3D model structure, but form clusters. Next we found evidence for the hantaviral N protein interaction with the cytoplasmic tail of the glycoprotein Gn. In order to study this interaction we used the GST pull-down assay in combination with mutagenesis technique. The results demonstrated that intact, properly folded zinc fingers of the Gn protein cytoplasmic tail as well as the middle domain of the N protein (that includes aa residues 80 248 and supposedly carries the RNA-binding domain) are essential for the interaction. Since hantaviruses do not have a matrix protein that mediates the packaging of the viral RNA in other negatve stranded viruses (NSRV), hantaviral RNPs should be involved in a direct interaction with the intraviral domains of the envelope-embedded glycoproteins. By showing the N-Gn interaction we provided the evidence for one of the crucial steps in the virus replication at which RNPs are directed to the site of the virus assembly. Finally we started analysis of the N protein RNA-binding region, which is supposedly located in the middle domain of the N protein molecule. We developed a model for the initial step of RNA-binding by the hantaviral N protein. We hypothesized that the hantaviral N protein possesses two secondary structure elements that initiate the RNA encapsidation. The results suggest that amino acid residues (172-176) presumably act as a hook to catch vRNA and that the positively charged interaction surface (aa residues 144-160) enhances the initial N-RNA interacation. In conclusion, we elucidated new functions of hantavirus N protein. Using in silico modeling we predicted the domain structure of the protein and using experimental techniques showed that each domain is responsible for executing certain function(s). We showed that intact N terminal coiled-coil domain is crucial for oligomerization and charged residues located on its surface form a interaction surface for the N monomers. The middle domain is essential for interaction with the cytoplasmic tail of the Gn protein and RNA binding.

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Thin films are the basis of much of recent technological advance, ranging from coatings with mechanical or optical benefits to platforms for nanoscale electronics. In the latter, semiconductors have been the norm ever since silicon became the main construction material for a multitude of electronical components. The array of characteristics of silicon-based systems can be widened by manipulating the structure of the thin films at the nanoscale - for instance, by making them porous. The different characteristics of different films can then to some extent be combined by simple superposition. Thin films can be manufactured using many different methods. One emerging field is cluster beam deposition, where aggregates of hundreds or thousands of atoms are deposited one by one to form a layer, the characteristics of which depend on the parameters of deposition. One critical parameter is deposition energy, which dictates how porous, if at all, the layer becomes. Other parameters, such as sputtering rate and aggregation conditions, have an effect on the size and consistency of the individual clusters. Understanding nanoscale processes, which cannot be observed experimentally, is fundamental to optimizing experimental techniques and inventing new possibilities for advances at this scale. Atomistic computer simulations offer a window to the world of nanometers and nanoseconds in a way unparalleled by the most accurate of microscopes. Transmission electron microscope image simulations can then bridge this gap by providing a tangible link between the simulated and the experimental. In this thesis, the entire process of cluster beam deposition is explored using molecular dynamics and image simulations. The process begins with the formation of the clusters, which is investigated for Si/Ge in an Ar atmosphere. The structure of the clusters is optimized to bring it as close to the experimental ideal as possible. Then, clusters are deposited, one by one, onto a substrate, until a sufficiently thick layer has been produced. Finally, the concept is expanded by further deposition with different parameters, resulting in multiple superimposed layers of different porosities. This work demonstrates how the aggregation of clusters is not entirely understood within the scope of the approximations used in the simulations; yet, it is also shown how the continued deposition of clusters with a varying deposition energy can lead to a novel kind of nanostructured thin film: a multielemental porous multilayer. According to theory, these new structures have characteristics that can be tailored for a variety of applications, with precision heretofore unseen in conventional multilayer manufacture.

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Superfluidity is perhaps one of the most remarkable observed macroscopic quantum effect. Superfluidity appears when a macroscopic number of particles occupies a single quantum state. Using modern experimental techniques one dark solitons) and vortices. There is a large literature on theoretical work studying the properties of such solitons using semiclassical methods. This thesis describes an alternative method for the study of superfluid solitons. The method used here is a holographic duality between a class of quantum field theories and gravitational theories. The classical limit of the gravitational system maps into a strong coupling limit of the quantum field theory. We use a holographic model of superfluidity to study solitons in these systems. One particularly appealing feature of this technique is that it allows us to take into account finite temperature effects in a large range of temperatures.

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Close to one half of the LHC events are expected to be due to elastic or inelastic diffractive scattering. Still, predictions based on extrapolations of experimental data at lower energies differ by large factors in estimating the relative rate of diffractive event categories at the LHC energies. By identifying diffractive events, detailed studies on proton structure can be carried out. The combined forward physics objects: rapidity gaps, forward multiplicity and transverse energy flows can be used to efficiently classify proton-proton collisions. Data samples recorded by the forward detectors, with a simple extension, will allow first estimates of the single diffractive (SD), double diffractive (DD), central diffractive (CD), and non-diffractive (ND) cross sections. The approach, which uses the measurement of inelastic activity in forward and central detector systems, is complementary to the detection and measurement of leading beam-like protons. In this investigation, three different multivariate analysis approaches are assessed in classifying forward physics processes at the LHC. It is shown that with gene expression programming, neural networks and support vector machines, diffraction can be efficiently identified within a large sample of simulated proton-proton scattering events. The event characteristics are visualized by using the self-organizing map algorithm.