Multilayer thin films by layer-by-layer (LBL) assembly of functional polyelectrolytes

Nanoscience aims at manipulating atoms, molecules and nano-size particles in a precise and controlled manner. Nano-scale control of the thin film structures of organic/polymeric materials is a prerequisite to the fabrication of sophisticated functional devices. The work presented in this thesis is a compilation of various polymer thin films with newly synthesized functional polymers. Cationic and anionic LC amphotropic polymers, p-type and n-type semiconducting polymers with triarylamine, oxadiazole, thiadiazole and triazine moieties are suitable materials to fabricate multilayers by layer-by-layer (LBL) self-assembly with a well defined internal structure. The LBL assembly is the ideal processing technique to prepare thin polymer film composites with fine control over morphology and composition at nano-scale thickness, which may have applications in photo-detectors, light-emitting diodes (LEDs), displays and sensors, as well as in solar cells. The multilayer build-up was investigated with amphotropic LC polymers individually by solution-dipping and spin-coating methods; they showed different internal orders with respect to layering and orientation of the mesogens, as a result of the liquid crystalline phase. The synthesized p-type and n-type semiconducting polymers were examined optically and electrochemically, suggesting that they are favorably promising as hole-(p-type) or electron-(n-type) transport materials in electronic and optoelectronic devices. In addition, we report a successful film deposition of polymers by the vacuum deposition method. The vapor deposition method provides a clean environment; it is solvent free and well suited to sequential depositions in hetero-structured multilayer system. As the potential applications, the fabricated polymer thin films were used as simple electrochromic films and also used as hole transporting layers in LEDs. Electrochemical and electrochromic characterizations of assembled films reveal that the newly synthesized polymers give rise to high contrast ratio and fast switching electrochromic films. The LEDs with vacuum deposited films show dramatic improvements in device characteristics, indicating that the films are promising as hole transporting layers. These are the result of not only the thin nano-scale film structures but also the combination with the high charge carrier mobility of synthesized semiconducting polymers.

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.