The initial oxidation of transition metal surfaces

Due to their numerous novel technological applications ranging from the example of exhaust catalysts in the automotive industry to the catalytic production of hydro- gen, surface reactions on transition metal substrates have become to be one of the most essential subjects within the surface science community. Although numerous applications exist, there are many details in the different processes that, after many decades of research, remain unknown. There are perhaps as many applications for the corrosion resistant materials such as stainless steels. A thorough knowledge of the details of the simplest reactions occuring on the surfaces, such as oxidation, play a key role in the design of better catalysts, or corrosion resistant materials in the future. This thesis examines the oxidation of metal surfaces from a computational point of view mostly concentrating on copper as a model material. Oxidation is studied from the initial oxidation to the oxygen precovered surface. Important parameters for the initial sticking and dissociation are obtained. The saturation layer is thoroughly studied and the calculated results arecompared with available experimental results. On the saturated surface, some open questions still remain. The present calculations demonstrate, that the saturated part of the surface is excluded from being chemically reactive towards the oxygen molecules. The results suggest, that the reason for the chemical activity of the saturated surface is due to a strain effect occuring between the saturated areas of the surface.

Many valued algebraic structures as measures of comparison

This thesis studies the properties and usability of operators called t-norms, t-conorms, uninorms, as well as many valued implications and equivalences. Into these operators, weights and a generalized mean are embedded for aggregation, and they are used for comparison tasks and for this reason they are referred to as comparison measures. The thesis illustrates how these operators can be weighted with a differential evolution and aggregated with a generalized mean, and the kinds of measures of comparison that can be achieved from this procedure. New operators suitable for comparison measures are suggested. These operators are combination measures based on the use of t-norms and t-conorms, the generalized 3_-uninorm and pseudo equivalence measures based on S-type implications. The empirical part of this thesis demonstrates how these new comparison measures work in the field of classification, for example, in the classification of medical data. The second application area is from the field of sports medicine and it represents an expert system for defining an athlete's aerobic and anaerobic thresholds. The core of this thesis offers definitions for comparison measures and illustrates that there is no actual difference in the results achieved in comparison tasks, by the use of comparison measures based on distance, versus comparison measures based on many valued logical structures. The approach has been highly practical in this thesis and all usage of the measures has been validated mainly by practical testing. In general, many different types of operators suitable for comparison tasks have been presented in fuzzy logic literature and there has been little or no experimental work with these operators.