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No description available.

No description available.

The interfacial structure of Co/Cu multilayers deposited under energetic ion bombardment has been investigated using X-ray reflectivity techniques. An ionassisted deposition system, based on unbalanced magnetron sputtering principles, has been developed in order to provide a method for the independent control of ion flux and energy. Using this system ion current densities measured at the substrate could be varied from ~30 µAcm2 to ~100 µAcm2 and average ion energies of ~50-200 eV could be selected. It was therefore possible to prepare Co/Cu multilayers under a variety of ion bombardment conditions and thus study the effect of this energetic particle bombardment on the evolution of interface structure. Samples were characterised by measuring the specular and diffuse X-ray reflectivity, using anomalous scattering effects to enhance the contrast between the cobalt and copper layers. Quantitative analysis of the specular reflection revealed the existence of variations of the interface roughness in multilayers deposited under ~200 eV ion bombardment, such that the interfaces became smoother towards the free surface. Films deposited with the highest available levels of ion flux were found to display the greatest interface smoothing effect. However, no such variation was observed when ion energies of ~50 eV were applied, although differences in the large lateral scale correlated roughness were observed between ~50 eV ion-assisted and non ion-assisted samples. The sensitivity of the interface structure to energetic bombardment during growth is thus demonstrated and the results are discussed in terms of resputtering and ion bombardment induced reordering of the growing surface. It is shown that these effects can be exploited to obtain multilayers with atomically smooth interfaces.

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In this thesis, we are interested in using the Padé approximants and asymptotic series to approximate the density functions of the stable distributions. The paper specifically discusses the selection of the optimal degree and central point of Padé approximants as well as how to connect the Padé approximants and asymptotic series as a piecewise function. Based on such approximation, a computational algorithm is developed to estimate the maximum likelihood estimator with confidence interval of the parameters, using quasi-Newton method. Simulations are conducted to evaluate the performance of this algorithm, and comparisons are made to Nolan's integral method to show that the method introduced in the thesis is fast and reliable in approximation and estimation.

Placement of a sufficient volume of acid in all desired zones is critical for a successful acid stimulation treatment. Particularly in thick, highly heterogeneous carbonate formations, the acid distribution is crucial for optimal stimulation results. A variety of diversion methods are applied in acidizing treatments to evenly place acid along the well, but the effectiveness of these diversion methods is generally only inferred from the rate and pressure behavior during the treatment, and is not known with any certainty. Recently, distributed temperature sensing technology has enabled us to observe dynamic temperature profiles along the wellbore during and immediately following an acid treatment. This technology allows us to monitor and evaluate treatments and diversion methods in real-time and to capture a sequence of temperature profiles at different times during and after acid injection. We developed a transient thermal model for reservoir, coupled with a wormhole penetration model. Then the reservoir model is combined with a vertical well temperature model as the forward model, which can predict the temperature behavior inside formation and wellbore during and after a treatment. We applied the forward model in a synthetic two-layer example, and it shows that the temperature increase caused by the reaction between acid and carbonate rock indicates the acid distribution. An inversion model was also developed to analyze the temperature data measured after treatments to obtain the acid flow profile for a vertical well. The inversion method applied in this work is Markov chain Monte Carlo (MCMC) method, which is a stochastic method to search globally for possible results. We discuss the approach to realize the inversion procedure and to make the inversion more efficient. We also applied the comprehensive thermal model for hypothetical cases and field cases. The results from the inverse model give us quantitative understanding of acid distribution, which helps us to confirm the success of the acid treatment and diversion methods.

Typescript. / Bibliography: leaves 142-149. / Microfiche. / xi, 149 leaves ill

The objective of the current study was to analyse the effect of landscape structure (habitat size and exposure to farmland) on the occurrence and abundance of Lobaria pulmonaria, a foliose cyanolichen. Since the agrarian revolution during the 19th century the agricultural landscape has become increasingly fragmented resulting in isolated meadows and wood-pastures surrounded by farmland. Lobaria pulmonaria is one of the species being affected by this habitat change, much due to their dispersal limitations, specific habitat demands and susceptibility to air pollution. 36 localities of two different size classes (< 1.5 ha and > 4.5 ha) and two different exposure classes (exposed or unexposed to farmland) were studied. The occurrence, size of lichen thallus and height of lichen patches on tree trunks were significantly positively affected by habitat size and negatively affected by habitat exposure. The implications of these findings for strategies to manage and conserve L. pulmonaria in a fragmented landscape are discussed.