Unconventional correlated systems

This work comprises three different types of unconventional correlated systems.rnChapters 3-5 of this work are about the open shell compounds Rb4O6 and Cs4O6. These mixed valent compounds contain oxygen in two different modifications: the closed-shell peroxide anion is nonmagnetic, whereas the hyperoxide anion contains an unpaired electrons in an antibonding pi*-orbital. Due to this electron magnetic ordering is rendered possible. In contrast to theoretical predictions, which suggested half-metallic ferromagnetism for Rb4O6,rndominating antiferromagnetic interactions were found in the experiment. Besidesrna symmetry reduction due to the mixed valency, strong electronic correlations of this highly molecular system determine its properties; it is a magnetically frustrated insulator. The corresponding Cs4O6 was found to show similar properties.rnChapters 6-9 of this work are about intermetallic Heusler superconductors. rnAll of these superconductors were rationally designed using the van Hove scenario as a working recipe. A saddle point in the energy dispersion curve of a solid leads to a van Hove singularity in the density of states. In the Ni-based and Pd-based Heusler superconductors presented in this work this sort of a valence instability occurs at the high-symmetry L point and coincides or nearly coincides with the Fermi level. The compounds escape the high density of states at the Fermi energy through a transition into the correlated superconducting state.rnChapter 10 of this work is about the tetragonally distorted ferrimagnetic DO22 phase of Mn3Ga. This hard-magnetic modification is technologically useful for spin torque transfer applications. The phase exhibits two different crystallographic sites that are occupied by Mn atoms and can thus be written as Mn2MnGa. The competition between the mainly itinerant moments of the Mn atoms at the Wyckoff position 4d and the localized moments of the Mn atoms at the Wyckoff position 2b leads to magnetic correlations. The antiferromagnetic orientation of these moments determines the compound to exhibit a resulting magnetic moment of approximately 1 µB per formula unit in a partially compensated ferrimagnetic configuration.

Automatic induction of lexical features

This thesis concerns artificially intelligent natural language processing systems that are capable of learning the properties of lexical items (properties like verbal valency or inflectional class membership) autonomously while they are fulfilling their tasks for which they have been deployed in the first place. Many of these tasks require a deep analysis of language input, which can be characterized as a mapping of utterances in a given input C to a set S of linguistically motivated structures with the help of linguistic information encoded in a grammar G and a lexicon L: G + L + C → S (1) The idea that underlies intelligent lexical acquisition systems is to modify this schematic formula in such a way that the system is able to exploit the information encoded in S to create a new, improved version of the lexicon: G + L + S → L' (2) Moreover, the thesis claims that a system can only be considered intelligent if it does not just make maximum usage of the learning opportunities in C, but if it is also able to revise falsely acquired lexical knowledge. So, one of the central elements in this work is the formulation of a couple of criteria for intelligent lexical acquisition systems subsumed under one paradigm: the Learn-Alpha design rule. The thesis describes the design and quality of a prototype for such a system, whose acquisition components have been developed from scratch and built on top of one of the state-of-the-art Head-driven Phrase Structure Grammar (HPSG) processing systems. The quality of this prototype is investigated in a series of experiments, in which the system is fed with extracts of a large English corpus. While the idea of using machine-readable language input to automatically acquire lexical knowledge is not new, we are not aware of a system that fulfills Learn-Alpha and is able to deal with large corpora. To instance four major challenges of constructing such a system, it should be mentioned that a) the high number of possible structural descriptions caused by highly underspeci ed lexical entries demands for a parser with a very effective ambiguity management system, b) the automatic construction of concise lexical entries out of a bulk of observed lexical facts requires a special technique of data alignment, c) the reliability of these entries depends on the system's decision on whether it has seen 'enough' input and d) general properties of language might render some lexical features indeterminable if the system tries to acquire them with a too high precision. The cornerstone of this dissertation is the motivation and development of a general theory of automatic lexical acquisition that is applicable to every language and independent of any particular theory of grammar or lexicon. This work is divided into five chapters. The introductory chapter first contrasts three different and mutually incompatible approaches to (artificial) lexical acquisition: cue-based queries, head-lexicalized probabilistic context free grammars and learning by unification. Then the postulation of the Learn-Alpha design rule is presented. The second chapter outlines the theory that underlies Learn-Alpha and exposes all the related notions and concepts required for a proper understanding of artificial lexical acquisition. Chapter 3 develops the prototyped acquisition method, called ANALYZE-LEARN-REDUCE, a framework which implements Learn-Alpha. The fourth chapter presents the design and results of a bootstrapping experiment conducted on this prototype: lexeme detection, learning of verbal valency, categorization into nominal count/mass classes, selection of prepositions and sentential complements, among others. The thesis concludes with a review of the conclusions and motivation for further improvements as well as proposals for future research on the automatic induction of lexical features.

Atomic-scale characterization of diamond surfaces and fullerene self-assembly

In this thesis, elemental research towards the implantation of a diamond-based molecular quantum computer is presented. The approach followed requires linear alignment of endohedral fullerenes on the diamond C(100) surface in the vicinity of subsurface NV-centers. From this, four fundamental experimental challenges arise: 1) The well-controlled deposition of endohedral fullerenes on a diamond surface. 2) The creation of NV-centers in diamond close to the surface. 3) Preparation and characterization of atomically-flat diamondsurfaces. 4) Assembly of linear chains of endohedral fullerenes. First steps to overcome all these challenges were taken in the framework of this thesis. Therefore, a so-called “pulse injection” technique was implemented and tested in a UHV chamber that was custom-designed for this and further tasks. Pulse injection in principle allows for the deposition of molecules from solution onto a substrate and can therefore be used to deposit molecular species that are not stable to sublimation under UHV conditions, such as the endohedral fullerenes needed for a quantum register. Regarding the targeted creation of NV-centers, FIB experiments were carried out in cooperation with the group of Prof. Schmidt-Kaler (AG Quantum, Physics Department, Johannes Gutenberg-Universität Mainz). As an entry into this challenging task, argon cations were implanted into (111) surface-oriented CaF2 crystals. The resulting implantation spots on the surface were imaged and characterized using AFM. In this context, general relations between the impact of the ions on the surface and their valency or kinetic energy, respectively, could be established. The main part of this thesis, however, is constituted by NCAFM studies on both, bare and hydrogen-terminated diamond C(100) surfaces. In cooperation with the group of Prof. Dujardin (Molecular Nanoscience Group, ISMO, Université de Paris XI), clean and atomically-flat diamond surfaces were prepared by exposure of the substrate to a microwave hydrogen plasma. Subsequently, both surface modifications were imaged in high resolution with NC-AFM. In the process, both hydrogen atoms in the unit cell of the hydrogenated surface were resolved individually, which was not achieved in previous STM studies of this surface. The NC-AFM images also reveal, for the first time, atomic-resolution contrast on the clean, insulating diamond surface and provide real-space experimental evidence for a (2×1) surface reconstruction. With regard to the quantum computing concept, high-resolution NC-AFM imaging was also used to study the adsorption and self-assembly potential of two different kinds of fullerenes (C60 and C60F48) on aforementioned diamond surfaces. In case of the hydrogenated surface, particular attention was paid to the influence of charge transfer doping on the fullerene-substrate interaction and the morphology emerging from self-assembly. Finally, self-assembled C60 islands on the hydrogen-terminated diamond surface were subject to active manipulation by an NC-AFM tip. Two different kinds of tip-induced island growth modes have been induced and were presented. In conclusion, the results obtained provide fundamental informations mandatory for the realization of a molecular quantum computer. In the process it was shown that NC-AFM is, under proper circumstances, a very capable tool for imaging diamond surfaces with highest resolution, surpassing even what has been achieved with STM up to now. Particular attention was paid to the influence of transfer doping on the morphology of fullerenes on the hydrogenated diamond surface, revealing new possibilities for tailoring the self-assembly of molecules that have a high electron affinity.