Computational modeling of surface interactions

Die Wechselwirkung zwischen Proteinen und anorganischen Oberflächen fasziniert sowohl aus angewandter als auch theoretischer Sicht. Sie ist ein wichtiger Aspekt in vielen Anwendungen, unter anderem in chirugischen Implantaten oder Biosensoren. Sie ist außerdem ein Beispiel für theoretische Fragestellungen betreffend die Grenzfläche zwischen harter und weicher Materie. Fest steht, dass Kenntnis der beteiligten Mechanismen erforderlich ist um die Wechselwirkung zwischen Proteinen und Oberflächen zu verstehen, vorherzusagen und zu optimieren. Aktuelle Fortschritte im experimentellen Forschungsbereich ermöglichen die Untersuchung der direkten Peptid-Metall-Bindung. Dadurch ist die Erforschung der theoretischen Grundlagen weiter ins Blickfeld aktueller Forschung gerückt. Eine Möglichkeit die Wechselwirkung zwischen Proteinen und anorganischen Oberflächen zu erforschen ist durch Computersimulationen. Obwohl Simulationen von Metalloberflächen oder Proteinen als Einzelsysteme schon länger verbreitet sind, bringt die Simulation einer Kombination beider Systeme neue Schwierigkeiten mit sich. Diese zu überwinden erfordert ein Mehrskalen-Verfahren: Während Proteine als biologische Systeme ausreichend mit klassischer Molekulardynamik beschrieben werden können, bedarf die Beschreibung delokalisierter Elektronen metallischer Systeme eine quantenmechanische Formulierung. Die wichtigste Voraussetzung eines Mehrskalen-Verfahrens ist eine Übereinstimmung der Simulationen auf den verschiedenen Skalen. In dieser Arbeit wird dies durch die Verknüpfung von Simulationen alternierender Skalen erreicht. Diese Arbeit beginnt mit der Untersuchung der Thermodynamik der Benzol-Hydratation mittels klassischer Molekulardynamik. Dann wird die Wechselwirkung zwischen Wasser und den [111]-Metalloberflächen von Gold und Nickel mittels eines Multiskalen-Verfahrens modelliert. In einem weiteren Schritt wird die Adsorbtion des Benzols an Metalloberflächen in wässriger Umgebung studiert. Abschließend wird die Modellierung erweitert und auch die Aminosäuren Alanin und Phenylalanin einbezogen. Dies eröffnet die Möglichkeit realistische Protein- Metall-Systeme in Computersimulationen zu betrachten und auf theoretischer Basis die Wechselwirkung zwischen Peptiden und Oberflächen für jede Art Peptide und Oberfläche vorauszusagen.

The influence of individual and colony level variation in behavior on colony performance in ants

In my dissertation I investigated the influence of behavioral variation between and within ant colonies on group performance. In particular, I analyzed how evolution shapes behavior in response to ecological conditions, and whether within-group diversity improves productivity as suggested by theory. Our field and laboratory experiments showed that behavioral diverse groups are more productive. Different aggression levels within colonies were beneficial under competitive field situations, whereas diversity in brood care and exploratory behavior were favored in non-competitive laboratory situations. We then examined whether population density and social parasite presence shape aggression through phenotypic plasticity and/or natural selection. The importance of selection was indicated by the absence of density or parasite effects on aggression in a field manipulation. Indeed, more aggressive colonies fared better under high density and during parasite attack. When analyzing the proximate causes of individual behavioral variation, ovarian development was shown to be linked to division of labor and aggressiveness. Finally, our studies show that differences in the collective behavior can be linked to immune defense and productivity. My dissertation demonstrates that behavioral variation should be studied on multiple scales and when possible combined with physiological analyses to better understand the evolution of animal personalities in social groups.rn

Heteronuclear recoupling methods in solid-state NMR

This thesis is focused on the development of heteronuclear correlation methods in solid-state NMR spectroscopy, where the spatial dependence of the dipolar coupling is exploited to obtain structural and dynamical information in solids. Quantitative results on dipolar coupling constants are extracted by means of spinning sideband analysis in the indirect dimension of the two-dimensional experiments. The principles of sideband analysis were established and are currently widely used in the group of Prof. Spiess for the special case of homonuclear 1H double-quantum spectroscopy. The generalization of these principles to the heteronuclear case is presented, with special emphasis on naturally abundant 13C-1H systems. For proton spectroscopy in the solid state, line-narrowing is of particular importance, and is here achieved by very-fast sample rotation at the magic angle (MAS), with frequencies up to 35 kHz. Therefore, the heteronuclear dipolar couplings are suppressed and have to be recoupled in order to achieve an efficient excitation of the observed multiple-quantum modes. Heteronuclear recoupling is most straightforwardly accomplished by performing the known REDOR experiment, where pi-pulses are applied every half rotor period. This experiment was modified by the insertion of an additional spectroscopic dimension, such that heteronuclear multiple-quantum experiments can be carried out, which, as shown experimentally and theoretically, closely resemble homonuclear double-quantum experiments. Variants are presented which are well-suited for the recording of high-resolution 13C-1H shift correlation and spinning-sideband spectra, by means of which spatial proximities and quantitative dipolar coupling constants, respectively, of heteronuclear spin pairs can be determined. Spectral editing of 13C spectra is shown to be feasible with these techniques. Moreover, order phenomena and dynamics in columnar mesophases with 13C in natural abundance were investigated. Two further modifications of the REDOR concept allow the correlation of 13C with quadrupolar nuclei, such as 2H. The spectroscopic handling of these nuclei is challenging in that they cover large frequency ranges, and with the new experiments it is shown how the excitation problem can be tackled or circumvented altogether, respectively. As an example, one of the techniques is used for the identification of a yet unknown motional process of the H-bonded protons in the crystalline parts of poly(vinyl alcohol).

Novel simulation methods for Coulomb and hydrodynamic interactions

This thesis presents new methods to simulate systems with hydrodynamic and electrostatic interactions. Part 1 is devoted to computer simulations of Brownian particles with hydrodynamic interactions. The main influence of the solvent on the dynamics of Brownian particles is that it mediates hydrodynamic interactions. In the method, this is simulated by numerical solution of the Navier--Stokes equation on a lattice. To this end, the Lattice--Boltzmann method is used, namely its D3Q19 version. This model is capable to simulate compressible flow. It gives us the advantage to treat dense systems, in particular away from thermal equilibrium. The Lattice--Boltzmann equation is coupled to the particles via a friction force. In addition to this force, acting on {it point} particles, we construct another coupling force, which comes from the pressure tensor. The coupling is purely local, i.~e. the algorithm scales linearly with the total number of particles. In order to be able to map the physical properties of the Lattice--Boltzmann fluid onto a Molecular Dynamics (MD) fluid, the case of an almost incompressible flow is considered. The Fluctuation--Dissipation theorem for the hybrid coupling is analyzed, and a geometric interpretation of the friction coefficient in terms of a Stokes radius is given. Part 2 is devoted to the simulation of charged particles. We present a novel method for obtaining Coulomb interactions as the potential of mean force between charges which are dynamically coupled to a local electromagnetic field. This algorithm scales linearly, too. We focus on the Molecular Dynamics version of the method and show that it is intimately related to the Car--Parrinello approach, while being equivalent to solving Maxwell's equations with freely adjustable speed of light. The Lagrangian formulation of the coupled particles--fields system is derived. The quasi--Hamiltonian dynamics of the system is studied in great detail. For implementation on the computer, the equations of motion are discretized with respect to both space and time. The discretization of the electromagnetic fields on a lattice, as well as the interpolation of the particle charges on the lattice is given. The algorithm is as local as possible: Only nearest neighbors sites of the lattice are interacting with a charged particle. Unphysical self--energies arise as a result of the lattice interpolation of charges, and are corrected by a subtraction scheme based on the exact lattice Green's function. The method allows easy parallelization using standard domain decomposition. Some benchmarking results of the algorithm are presented and discussed.

Use of computer algebra in the calculation of Feynman diagrams

The increasing precision of current and future experiments in high-energy physics requires a likewise increase in the accuracy of the calculation of theoretical predictions, in order to find evidence for possible deviations of the generally accepted Standard Model of elementary particles and interactions. Calculating the experimentally measurable cross sections of scattering and decay processes to a higher accuracy directly translates into including higher order radiative corrections in the calculation. The large number of particles and interactions in the full Standard Model results in an exponentially growing number of Feynman diagrams contributing to any given process in higher orders. Additionally, the appearance of multiple independent mass scales makes even the calculation of single diagrams non-trivial. For over two decades now, the only way to cope with these issues has been to rely on the assistance of computers. The aim of the xloops project is to provide the necessary tools to automate the calculation procedures as far as possible, including the generation of the contributing diagrams and the evaluation of the resulting Feynman integrals. The latter is based on the techniques developed in Mainz for solving one- and two-loop diagrams in a general and systematic way using parallel/orthogonal space methods. These techniques involve a considerable amount of symbolic computations. During the development of xloops it was found that conventional computer algebra systems were not a suitable implementation environment. For this reason, a new system called GiNaC has been created, which allows the development of large-scale symbolic applications in an object-oriented fashion within the C++ programming language. This system, which is now also in use for other projects besides xloops, is the main focus of this thesis. The implementation of GiNaC as a C++ library sets it apart from other algebraic systems. Our results prove that a highly efficient symbolic manipulator can be designed in an object-oriented way, and that having a very fine granularity of objects is also feasible. The xloops-related parts of this work consist of a new implementation, based on GiNaC, of functions for calculating one-loop Feynman integrals that already existed in the original xloops program, as well as the addition of supplementary modules belonging to the interface between the library of integral functions and the diagram generator.

Characterisation of supramolecular structures by novel recoupling methods in solid-state NMR

In this work, solid-state NMR methods suitable for the investigation of supramolecular systems were developed and improved. In this context, special interest was focussed on non-covalent interactions responsible for the formation of supramolecular structures, such as pi-pi interacions and hydrogen-bonds. In the first part of this work, solid-state NMR methods were presented that provide information on molecular structure and motion via the investigation of anisotropic interactions, namely quadrupole and dipole-dipole couplings, under magic-angle spinning conditions. A two-dimensional 2H double quantum experiment was developed, which is performed under off magic-angle conditions and correlates 2H isotropic chemical shifts with quasistatic DQ-filtered line shapes. From the latter, the quadrupole coupling parameters of samples deuterated at multiple sites can be extracted in a site-selective fashion. Furthermore, 7Li quadrupole parameters of lithium intercalated into TiO2 were determined by NMR experiments performed under static and MAS conditions, and could provide information on the crystal geometry. For the determination of 7Li-7Li dipole-dipole couplings, multiple-quantum NMR experiments were performed. The 1H-13C REREDOR experiment was found to be capable of determining strong proton-carbon dipole-dipole couplings with an accuracy of 500~Hz, corresponding to a determination of proton-carbon chemical-bond lengths with picometer accuracy In the second part of this work, solid-state NMR experiments were combined with quantum-chemical calculations in order to aid and optimise the interpretation of experimental results. The investigations on Calix[4]hydroquinone nanotubes have shown that this combined approach can provide information on the presence of disordered and/or mobile species in supramolecular structures. As a second example, C3-symmetric discs arranging in helical columnar stacks were investigated. In these systems, 1H chemical shifts experience large pi-shifts due to packing effects, which were found to be long-ranged. Moreover, quantum-chemical calculations revealed that helicity in these systems is induced by the propeller-like conformation of the core of the molecules.

Coarse-graining methods and polymer dynamics

This thesis studies molecular dynamics simulations on two levels of resolution: the detailed level of atomistic simulations, where the motion of explicit atoms in a many-particle system is considered, and the coarse-grained level, where the motion of superatoms composed of up to 10 atoms is modeled. While atomistic models are capable of describing material specific effects on small scales, the time and length scales they can cover are limited due to their computational costs. Polymer systems are typically characterized by effects on a broad range of length and time scales. Therefore it is often impossible to atomistically simulate processes, which determine macroscopic properties in polymer systems. Coarse-grained (CG) simulations extend the range of accessible time and length scales by three to four orders of magnitude. However, no standardized coarse-graining procedure has been established yet. Following the ideas of structure-based coarse-graining, a coarse-grained model for polystyrene is presented. Structure-based methods parameterize CG models to reproduce static properties of atomistic melts such as radial distribution functions between superatoms or other probability distributions for coarse-grained degrees of freedom. Two enhancements of the coarse-graining methodology are suggested. Correlations between local degrees of freedom are implicitly taken into account by additional potentials acting between neighboring superatoms in the polymer chain. This improves the reproduction of local chain conformations and allows the study of different tacticities of polystyrene. It also gives better control of the chain stiffness, which agrees perfectly with the atomistic model, and leads to a reproduction of experimental results for overall chain dimensions, such as the characteristic ratio, for all different tacticities. The second new aspect is the computationally cheap development of nonbonded CG potentials based on the sampling of pairs of oligomers in vacuum. Static properties of polymer melts are obtained as predictions of the CG model in contrast to other structure-based CG models, which are iteratively refined to reproduce reference melt structures. The dynamics of simulations at the two levels of resolution are compared. The time scales of dynamical processes in atomistic and coarse-grained simulations can be connected by a time scaling factor, which depends on several specific system properties as molecular weight, density, temperature, and other components in mixtures. In this thesis the influence of molecular weight in systems of oligomers and the situation in two-component mixtures is studied. For a system of small additives in a melt of long polymer chains the temperature dependence of the additive diffusion is predicted and compared to experiments.