Crescimento de filmes nanométricos monocristalinos de Fe/MgO(100) por "SPUTTERING" DC

The research behind this master dissertation started with the installation of a DC sputtering system, from its first stage, the adaptation of a refrigerating system, passing by the introduction of a heating system for the chamber using a thermal belt, until the deposition of a series of Fe/MgO(100) single crystal nanometric film samples. The deposition rates of some materials such as Fe, Py and Cu were investigated through an Atomic Force Microscope (AFM). For the single crystal samples, five of them have the same growth parameters and a thickness of 250Å, except for the temperature, which varies from fifty degrees from one to another, from 100ºC to 300ºC. Three other samples also have the same deposition parameters and a temperature of 300ºC, but with thickness of 62,5Å, 150Å, and 250Å. Magneto-optical Kerr Effect (MOKE) of the magnetic curves measurements and Ferromagnetic Resonance (FMR) were made to in order to study the influence of the temperature and thickness on the sample s magnetic properties. In the present dissertation we discuss such techniques, and the experimental results are interpreted using phenomenological models, by simulation, and discussed from a physical point of view, taking into account the system s free magnetic energy terms. The results show the growth of the cubic anisotropy field (Hac) as the sample s deposition temperature increases, presenting an asymptotic behavior, similar to the characteristic charging curve of a capacitor in a RC circuit. A similar behavior was also observed for the Hac due to the increase in the samples thicknesses. The 250˚A sample, growth at 300°C, presented a Hac field close to the Fe bulk value

Ergodicidade em cadeias de Markov não-homogêneas e cadeias de Markov com transições raras

The central objective of a study Non-Homogeneous Markov Chains is the concept of weak and strong ergodicity. A chain is weak ergodic if the dependence on the initial distribution vanishes with time, and it is strong ergodic if it is weak ergodic and converges in distribution. Most theoretical results on strong ergodicity assume some knowledge of the limit behavior of the stationary distributions. In this work, we collect some general results on weak and strong ergodicity for chains with space enumerable states, and also study the asymptotic behavior of the stationary distributions of a particular type of Markov Chains with finite state space, called Markov Chains with Rare Transitions