Gas-phase electron diffraction (GED) is the method of choice for determining the structures of molecules containing between two and 100 atoms, free from intermolecular interaction. However, for many molecules it becomes necessary to augment the experimental GED data with information from other sources. The SARACEN method, used routinely at Edinburgh when determining structures, allows computed parameters from ab initio and density functional theory (DFT) calculations to be used as extra data in the GED refinement process. This thesis describes the determinations of the gas-phase structures of molecules that contain heavy p-block elements, including examples from Groups 13, 14, 15 and 16. Each of the compounds studied was solid at room temperature, requiring heating to produce a suitable vapour pressure and vaporisation rate and testing the existing electron diffraction apparatus to its limits. Use was made of a new heated reservoir, recently developed in Edinburgh by a previous PhD student, which has allowed compounds to be studied that were previously inaccessible. The molecules that were studied during the course of this degree are: In(P3C2But2), In(P2C3But3), Sn(P2C2But2), Sb2(C6F6)3, Bi2(C6F6)3, Se(SCH3)2 and Te(SCH3)2. While determining the structures of these molecules, accurate theoretical geometries have been obtained using both ab initio and DFT methods. As a result a better understanding has been achieved of which methods are suitable for use in calculating the structures of molecules with heavy p-block elements. The use of pseudopotentials as opposed to all-electron basis sets proved necessary when performing calculations on such large molecules with heavy atoms. The extent to which these pseudopotentials, especially ones that consider very few electrons to be in the valence shell of an atom, can affect the calculated geometries has been shown to be considerable. In addition, methods being developed to compute vibrational corrections for gas-phase structure determination have been extended to the crystalline phase. Molecular dynamics simulations have been used to derive the effects of vibrations on average nuclear positions, relative to equilibrium positions. The differences, when applied to coordinates obtained experimentally by neutron diffraction yield experimental equilibrium structures.

The effect of varying substituents on structure and energies of bisketenes was studied using ab initio methods. Effect of substituents on ring closing reaction of bisketenes to the corresponding cyclobutenediones was also studied using ab initio methods. One or two of the following substituents were used to study the effect of varying substituents: BH2, CH3, NH2, OH, F, AlH2, SiH3, PH2, SH, Cl. Studies were done at the Hartree-Fock (HF), Møller-Plesset (MP2), and Density Functional Theory (B3LYP) levels of theory using the 6-31G* basis set.

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Protein structure prediction is concerned with the prediction of a protein's three dimensional structure from its amino acid sequence. Such predictions are commonly performed by searching the possible structures and evaluating each structure by using some scoring function. If it is assumed that the target protein structure resembles the structure of a known protein, the search space can be significantly reduced. Such an approach is referred to as comparative structure prediction. When such an assumption is not made, the approach is known as ab initio structure prediction. There are several difficulties in devising efficient searches or in computing the scoring function. Many of these problems have ready solutions from known mathematical methods. However, the problems that are yet unsolved have hindered structure prediction methods from more ideal predictions. The objective of this study is to present a complete framework for ab initio protein structure prediction. To achieve this, a new search strategy is proposed, and better techniques are devised for computing the known scoring functions. Some of the remaining problems in protein structure prediction are revisited. Several of them are shown to be intractable. In many of these cases, approximation methods are suggested as alternative solutions. The primary issues addressed in this thesis are concerned with local structures prediction, structure assembly or sampling, side chain packing, model comparison, and structural alignment. For brevity, we do not elaborate on these problems here; a concise introduction is given in the first section of this thesis. Results from these studies prompted the development of several programs, forming a utility suite for ab initio protein structure prediction. Due to the general usefulness of these programs, some of them are released with open source licenses to benefit the community.

Protein structure prediction is concerned with the prediction of a protein's three dimensional structure from its amino acid sequence. Such predictions are commonly performed by searching the possible structures and evaluating each structure by using some scoring function. If it is assumed that the target protein structure resembles the structure of a known protein, the search space can be significantly reduced. Such an approach is referred to as comparative structure prediction. When such an assumption is not made, the approach is known as ab initio structure prediction. There are several difficulties in devising efficient searches or in computing the scoring function. Many of these problems have ready solutions from known mathematical methods. However, the problems that are yet unsolved have hindered structure prediction methods from more ideal predictions. The objective of this study is to present a complete framework for ab initio protein structure prediction. To achieve this, a new search strategy is proposed, and better techniques are devised for computing the known scoring functions. Some of the remaining problems in protein structure prediction are revisited. Several of them are shown to be intractable. In many of these cases, approximation methods are suggested as alternative solutions. The primary issues addressed in this thesis are concerned with local structures prediction, structure assembly or sampling, side chain packing, model comparison, and structural alignment. For brevity, we do not elaborate on these problems here; a concise introduction is given in the first section of this thesis. Results from these studies prompted the development of several programs, forming a utility suite for ab initio protein structure prediction. Due to the general usefulness of these programs, some of them are released with open source licenses to benefit the community.

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The electron transport characteristics of Oligoaniline molecular junctions terminated with thiol-ends are analyzed with the density functional theory and the Green's function approach. The molecular junction consists of an Oligoaniline molecule attached to metal electrodes at each end. By applying an electric field, the molecule conducts a current that depends on either the molecular conformation or the ionization state. Ab initio optimization methods are performed on various Oligoaniline systems to analyze how different conformational changes are associated with different conductivities. The density functional theory and Green's function are used to calculate the density of states, transmission probability functions, and current-voltage calculations for each Oligoaniline system to complement the results from the molecular analysis. An inelastic tunneling spectrum analysis is also performed through frequency calculations to examine the different characteristics of each conducting state. Molecular orbits of each conformation was used to investigate further the relation between structure and electrical properties of the molecular junction. The combined results from the different calculations provided insight into the possible mechanisms for electron transfer throughout the junction.

This work focuses on an examination of the high-accuracy extrapoloated ab initio thermochemistry (HEAT) protocol of determining molecular atomization energies. The HEAT protocol does not utilize experimental data or empirical scaling effects. The accuracy of the approach is tested via comparison to ATcT data, and all molecules fall within 1 kcal/mol of accepted values. There are several important points to note about this treatment: namely, that we have used atomic natural orbital (ANO) basis sets for the calculation of the zero point energy and that we have made determinations for larger molecules than previously done with HEAT. The molecules in this paper were chosen to provide benchmark numbers for the homodesmotic reaction heirarchy as described by Wheeler et al.[3] The relative accuracy of the approach is considered, as well as a discussion of possible remaining sources of error. / text

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