X-ray photoelectron spectroscopy (XPS) has been used to probe the influence of cation structure on fundamental interactions within Ionic Liquid (IL) systems. A series of guanidinium-based ILs have been investigated and cation-anion interactions have been studied to determine the effect of a highly charge delocalised cationic core on the electronic environment of the anion. These and sulfur-based cations were developed, and 13C-NMR comparisons addressed, along with the influence of sulfur functionalisation upon the electronic environments of the cationic component. These materials were then used to probe the composition and structural orientation of ions of the IL surface with resource to angle-resolved XPS (ARXPS) and particularly, energy-resolved XPS (ERXPS). Appropriate methodologies for both techniques were developed and fully verified, and the position of the anion ([NTf2]-) relative to cation (imidazolium, guanidinium and thioimidazolium) was found to support previous findings in the literature using other spectroscopic techniques. Additionally, ERXPS allowed for relative depth profiles not only of the anionic component, but also of the sulfur in the cationic component for the thioimidazolium bis(trifluoromethanesulfonyl)imide IL series.

Two reaction classes have been studied computationally including the pyrolysis of various components of airplane fuels, such as decane, dodecane, butylbenzene isomers, and JP-10 (exo-tetrahydrodicyclopentadiene), and oxidation of a group of molecules belonging to the class of Polycyclic Aromatic Hydrocarbons (PAHs). Investigation of both reaction classes have been performed using ab initio quantum chemistry methods with the Gaussian 09 and MOLPRO programs at various levels of theory. Initially, Potential Energy Surfaces (PES) were generated at the G3(MP2,CC)/B3LYP/6-311G** level of theory for various radicals involved in the reactions as reactants, intermediates, transition states, and products. The next step was to perform RiceRamsperger-Kassel-Marcus (RRKM) / Master Equation calculations in order to calculate rate constants and branching ratios of different products at various temperatures and pressures characteristic for combustion flames. All calculations were then compared with previous works on similar systems available in the literature. The results of these simulations along with previous data were then used to formulate guidelines for the pyrolysis and oxidation patterns of larger and more complex systems, in order to achieve a better understanding of the pathways to the end products in airplane jet engines.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 189-196).

<p>Membrane proteins are of broad interest since they constitute a large fraction of the proteome in all organisms, up to 20-30%. They play a crucial role in many cellular processes mediating information flow and molecular transport across otherwise nearly impermeable membranes. Traditional three-dimensional structural analyses of membrane proteins are difficult to perform, which makes studies of other structural aspects important. The topology of an α-helical membrane protein is a two-dimensional description of how the protein is embedded in the membrane and gives valuable information on both structure and function.</p><p>This thesis is focused on predicting the topology of α-helical membrane proteins and on assessing and improving the prediction accuracy. Reliability scores have been derived for a number of prediction methods, and have been integrated into the widely used TMHMM predictor. The reliability score makes it possible to estimate the trustworthiness of a prediction.</p><p>Mapping the full topology of a membrane protein experimentally is time-consuming and cannot be done on a genome-wide scale. However, determination of the location of one part of a membrane protein relative to the membrane is feasible. We have analyzed the impact of incorporating such experimental information <i>a priori </i>into TMHMM predictions and show that the accuracy increases significantly. We further show that the C-terminal location of a membrane protein (inside or outside) is the optimal information to use as a constraint in the predictions.</p><p>By combining experimental techniques for determining the C-terminal location of membrane proteins with topology predictions, we have produced reliable topology models for the majority of all membrane proteins in the model organisms <i>E. coli </i>and <i>S. cerevisiae</i>. The results were further expanded to ~15,000 homologous proteins in 38 fully sequenced eukaryotic genomes. This large set of reliable topology models should be useful, in particular as the structural data for eukaryotic membrane proteins is very limited.</p>

<p>For the vast majority of proteins no experimental information about the three-dimensional structure is known, but only its sequence. Therefore, the easiest way to obtain some understanding of the structure and function of these proteins is by relating them to well studied proteins. This can be done by searching for homologous proteins. It is easy to identify a homologous sequence if the sequence identity is above 30%. However, if the sequence identity drops below 30% then more sophisticated methods have to be used. These methods often use evolutionary information about the sequences, which makes it possible to identify homologous sequences with a low sequence identity.</p><p>In order to build a three--dimensional model from the sequence based on a protein structure the two sequences have to be aligned. Here the aligned residues serve as a first approximation of the structure.</p><p>This thesis focuses on the development of fold recognition and alignment methods based on evolutionary information. The use of evolutionary information for both query and target proteins was shown to improve both recognition and alignments. In a benchmark of profile--profile methods it was shown that the probabilistic methods were best, although the difference between several of the methods was quite small once optimal gap-penalties were used. An artificial neural network based alignment method ProfNet was shown to be at least as good as the best profile--profile method, and by adding information from a self-organising map and predicted secondary structure we were able to further improve ProfNet.</p>

For the vast majority of proteins no experimental information about the three-dimensional structure is known, but only its sequence. Therefore, the easiest way to obtain some understanding of the structure and function of these proteins is by relating them to well studied proteins. This can be done by searching for homologous proteins. It is easy to identify a homologous sequence if the sequence identity is above 30%. However, if the sequence identity drops below 30% then more sophisticated methods have to be used. These methods often use evolutionary information about the sequences, which makes it possible to identify homologous sequences with a low sequence identity. In order to build a three--dimensional model from the sequence based on a protein structure the two sequences have to be aligned. Here the aligned residues serve as a first approximation of the structure. This thesis focuses on the development of fold recognition and alignment methods based on evolutionary information. The use of evolutionary information for both query and target proteins was shown to improve both recognition and alignments. In a benchmark of profile--profile methods it was shown that the probabilistic methods were best, although the difference between several of the methods was quite small once optimal gap-penalties were used. An artificial neural network based alignment method ProfNet was shown to be at least as good as the best profile--profile method, and by adding information from a self-organising map and predicted secondary structure we were able to further improve ProfNet.

Membrane proteins are of broad interest since they constitute a large fraction of the proteome in all organisms, up to 20-30%. They play a crucial role in many cellular processes mediating information flow and molecular transport across otherwise nearly impermeable membranes. Traditional three-dimensional structural analyses of membrane proteins are difficult to perform, which makes studies of other structural aspects important. The topology of an α-helical membrane protein is a two-dimensional description of how the protein is embedded in the membrane and gives valuable information on both structure and function. This thesis is focused on predicting the topology of α-helical membrane proteins and on assessing and improving the prediction accuracy. Reliability scores have been derived for a number of prediction methods, and have been integrated into the widely used TMHMM predictor. The reliability score makes it possible to estimate the trustworthiness of a prediction. Mapping the full topology of a membrane protein experimentally is time-consuming and cannot be done on a genome-wide scale. However, determination of the location of one part of a membrane protein relative to the membrane is feasible. We have analyzed the impact of incorporating such experimental information a priori into TMHMM predictions and show that the accuracy increases significantly. We further show that the C-terminal location of a membrane protein (inside or outside) is the optimal information to use as a constraint in the predictions. By combining experimental techniques for determining the C-terminal location of membrane proteins with topology predictions, we have produced reliable topology models for the majority of all membrane proteins in the model organisms E. coli and S. cerevisiae. The results were further expanded to ~15,000 homologous proteins in 38 fully sequenced eukaryotic genomes. This large set of reliable topology models should be useful, in particular as the structural data for eukaryotic membrane proteins is very limited.

This thesis presents quantum chemical calculations, applications of the response function formalism recently implemented within the framework of density functional theory by our research group. The purpose of the calculations is to assess the performance of this perturbative approach to determining heavy atom effects on magnetic resonance parameters. Relativistic corrections can be generated by spin-orbit interactions or by scalar relativistic effects due to high velocity electrons in the atomic core region of heavy atoms. In this work, the evaluation of nuclear magnetic resonance parameters is considered, the nuclear shielding tensor and the indirect nuclear spin-spin coupling tensor. For series of homologous compounds, it is found that both types of corrections to these parameters are increasing in size upon substitution of a constituent atom by a heavier element, but that their relative importance is system dependent. The obtained results are compatible with the ones provided by electron correlated ab initio methods, and a qualitative agreement with experimentally determined parameters is overall achieved. The methodology presented in this thesis aims to be a practical approach which can be applied in the study of molecular properties of large systems. This thesis also addresses the calculation of hyperfine coupling constants, and evaluates a novel approach to the treatment of spin-polarization in spin restricted calculations without the spin contamination associated with spin unrestricted calculations / QC 20100811

<p>The presented thesis is devoted to the field of organic light emitting</p><p>diodes (OLEDs). Time-dependent Kohn-Sham density functional theory</p><p>(TDDFT) is applied</p><p>in order to eludicate optical properties such as fluorescence and</p><p>phosphorescence for some of the most important materials. The</p><p>accuracy of TDDFT is evaluated with respect to the calculated absorption</p><p>and emission spectra for commonly used light emitting polymers.</p><p>A continuation of this work is devoted to Polyfluorene as this polymer</p><p>has proven to be very promising. In this study the chain</p><p>length dependence of its singlet and triplet excited states is</p><p>analyzed as well as the excited state structures.</p><p>Understanding the phosphorescence mechanism of tris(2-phenylpyridine)Iridium is</p><p>of importance in order to interpret the high efficiency of OLEDs</p><p>containing these specimens. The mechanism is analyzed by calculating</p><p>the electric transition dipole moments by means of TDDFT using</p><p>quadratic response functions.</p><p>As not only the optical properties are essential for effective</p><p>devices, electron transfer properties are addressed. The electron</p><p>transfer capability of the sulfur and nitrogen analogues of Oxadiazole</p><p>is evaluated through their internal reorganization energy.</p>

<p>Density Functional Theory is used in order to shed light on the reaction mechanisms and the origins of stereoselectivity in enantioselective organocatalytic reactions. The reactions investigated are the dipeptide-catalyzed aldol reaction, the cinchona thiourea-catalyzed nitroaldol reaction and the prolinol derivative-catalyzed hydrophosphination reaction. We can justify the stereoselectivity in the reactions from the energies arising from different interactions in the transition states. The major contributions to the energy differences are found to be hydrogen bond-type attractions and steric repulsions. This knowledge will be useful in the design of improved catalysts as well as general understanding of the basis of selection in other reactions</p>