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The occurrence of earthquakes is characterized by a high degree of spatiotemporal complexity. Although numerous patterns, e.g. fore- and aftershock sequences, are well-known, the underlying mechanisms are not observable and thus not understood. Because the recurrence times of large earthquakes are usually decades or centuries, the number of such events in corresponding data sets is too small to draw conclusions with reasonable statistical significance. Therefore, the present study combines both, numerical modeling and analysis of real data in order to unveil the relationships between physical mechanisms and observational quantities. The key hypothesis is the validity of the so-called "critical point concept" for earthquakes, which assumes large earthquakes to occur as phase transitions in a spatially extended many-particle system, similar to percolation models. New concepts are developed to detect critical states in simulated and in natural data sets. The results indicate that important features of seismicity like the frequency-size distribution and the temporal clustering of earthquakes depend on frictional and structural fault parameters. In particular, the degree of quenched spatial disorder (the "roughness") of a fault zone determines whether large earthquakes occur quasiperiodically or more clustered. This illustrates the power of numerical models in order to identify regions in parameter space, which are relevant for natural seismicity. The critical point concept is verified for both, synthetic and natural seismicity, in terms of a critical state which precedes a large earthquake: a gradual roughening of the (unobservable) stress field leads to a scale-free (observable) frequency-size distribution. Furthermore, the growth of the spatial correlation length and the acceleration of the seismic energy release prior to large events is found. The predictive power of these precursors is, however, limited. Instead of forecasting time, location, and magnitude of individual events, a contribution to a broad multiparameter approach is encouraging.
It has been known for several years that under certain conditions electrons can be confined within thin layers even if these layers consist of metal and are supported by a metal substrate. In photoelectron spectra, these layers show characteristic discrete energy levels and it has turned out that these lead to large effects like the oscillatory magnetic coupling technically exploited in modern hard disk reading heads. The current work asks in how far the concepts underlying quantization in two-dimensional films can be transferred to lower dimensionality. This problem is approached by a stepwise transition from two-dimensional layers to one-dimensional nanostructures. On the one hand, these nanostructures are represented by terraces on atomically stepped surfaces, on the other hand by atom chains which are deposited onto these terraces up to complete coverage by atomically thin nanostripes. Furthermore, self organization effects are used in order to arrive at perfectly one-dimensional atomic arrangements at surfaces. Angle-resolved photoemission is particularly suited as method of investigation because is reveals the behavior of the electrons in these nanostructures in dependence of the spacial direction which distinguishes it from, e. g., scanning tunneling microscopy. With this method intense and at times surprisingly large effects of one-dimensional quantization are observed for various exemplary systems, partly for the first time. The essential role of bandgaps in the substrate known from two-dimensional systems is confirmed for nanostructures. In addition, we reveal an ambiguity without precedent in two-dimensional layers between spacial confinement of electrons on the one side and superlattice effects on the other side as well as between effects caused by the sample and by the measurement process. The latter effects are huge and can dominate the photoelectron spectra. Finally, the effects of reduced dimensionality are studied in particular for the d electrons of manganese which are additionally affected by strong correlation effects. Surprising results are also obtained here. ---------------------------- Die Links zur jeweiligen Source der im Appendix beigefügten Veröffentlichungen befinden sich auf Seite 83 des Volltextes.
In this work, the basic principles of self-organization of diblock copolymers having the in¬herent property of selective or specific non-covalent binding were examined. By the introduction of electrostatic, dipole–dipole, or hydrogen bonding interactions, it was hoped to add complexity to the self-assembled mesostructures and to extend the level of ordering from the nanometer to a larger length scale. This work may be seen in the framework of biomimetics, as it combines features of synthetic polymer and colloid chemistry with basic concepts of structure formation applying in supramolecular and biological systems. The copolymer systems under study were (i) block ionomers, (ii) block copolymers with acetoacetoxy chelating units, and (iii) polypeptide block copolymers.