In recent years, chemical instrumentation has become much more sophisticated. Most analytical equipment now incorporates a microprocessor or is interfaced to a microcomputer. As a result, chemists can collect an immense amount of data on a single sample in a short period of time. While there may be an advantage to gathering such a great deal of information, problems can arise from too much information. Today, analysts commonly are faced with the dual problems of storing and analyzing the resulting flood of information. The goal of this research has been to address the problems of data storage and data analysis. Specifically, data compression techniques and spectral search and match algorithms have been developed. The data compression techniques developed utilize the Hadamard Transform and the modified zero-crossing clipping algorithm. The spectral search technique utilizes the unique format of the compressed and clipped data to greatly accelerate spectrum identification. To demonstrate the feasibility of this technique, three-dimensional fluorescence spectra of polynuclear aromatic compounds have been used. The results indicate data compression techniques and the application of these techniques to a library search system for three-dimensional fluorescence spectroscopy were both successful. / Ph. D.

The development of the correlation consistent basis sets, cc-pVnZ (where n = D, T, Q, etc.) have allowed for the systematic elucidation of the intrinsic accuracy of ab initio quantum chemical methods. In density functional theory (DFT), where the cc-pVnZ basis sets are not necessarily optimal in their current form, the elucidation of the intrinsic accuracy of DFT methods cannot always be accomplished. This dissertation outlines investigations into the basis set requirements for DFT and how the intrinsic accuracy of DFT methods may be determined with a prescription involving recontraction of the cc-pVnZ basis sets for specific density functionals. Next, the development and benchmarks of a set of cc-pVnZ basis sets designed for the s-block atoms lithium, beryllium, sodium, and magnesium are presented. Computed atomic and molecular properties agree well with reliable experimental data, demonstrating the accuracy of these new s-block basis sets. In addition to the development of cc-pVnZ basis sets, the development of a new, efficient formulism of the correlation consistent Composite Approach (ccCA) using the resolution of the identity (RI) approximation is employed. The new formulism, denoted 'RI-ccCA,' has marked efficiency in terms of computational time and storage, compared with the ccCA formulism, without the introduction of significant error. Finally, this dissertation reports three separate investigations of the properties of FOOF-like, germanium arsenide, and silicon hydride/halide molecules using high accuracy ab initio methods and the cc-pVnZ basis sets.

Solubility prediction usually refers to prediction of the intrinsic aqueous solubility, which is the concentration of an unionised molecule in a saturated aqueous solution at thermodynamic equilibrium at a given temperature. Solubility is determined by structural and energetic components emanating from solid-phase structure and packing interactions, solute–solvent interactions, and structural reorganisation in solution. An overview of the most commonly used methods for solubility prediction is given in Chapter 1. In this thesis, we investigate various approaches to solubility prediction and solvation model development, based on informatics and incorporation of empirical and experimental data. These are of a knowledge-based nature, and specifically incorporate information from the Cambridge Structural Database (CSD). A common problem for solubility prediction is the computational cost associated with accurate models. This issue is usually addressed by use of machine learning and regression models, such as the General Solubility Equation (GSE). These types of models are investigated and discussed in Chapter 3, where we evaluate the reliability of the GSE for a set of structures covering a large area of chemical space. We find that molecular descriptors relating to specific atom or functional group counts in the solute molecule almost always appear in improved regression models. In accordance with the findings of Chapter 3, in Chapter 4 we investigate whether radial distribution functions (RDFs) calculated for atoms (defined according to their immediate chemical environment) with water from organic hydrate crystal structures may give a good indication of interactions applicable to the solution phase, and justify this by comparison of our own RDFs to neutron diffraction data for water and ice. We then apply our RDFs to the theory of the Reference Interaction Site Model (RISM) in Chapter 5, and produce novel models for the calculation of Hydration Free Energies (HFEs).

Indiana University-Purdue University Indianapolis (IUPUI) / The multi-protein complex of F0F1 ATP synthase has been of great interest in the fields of microbiology and biochemistry, due to the ubiquitous use of ATP as a biological energy source. Efforts to better understand this complex have been made through structural determination of segments based on NMR and crystallographic data. Some experiments have provided useful data, while others have brought up more questions, especially when structures and functions are compared between bacteria and species with chloroplasts or mitochondria. The epsilon subunit is thought to play a signi cant role in the regulation of ATP synthesis and hydrolysis, yet the exact pathway is unknown due to the experimental difficulty in obtaining data along the transition pathway. Given starting and end point protein crystal structures, the transition pathway of the epsilon subunit was examined through computer simulation.The purpose of this investigation is to determine the likelihood of one such proposed mechanism for the involvement of the epsilon subunit in ATP regulation in bacterial species such as E. coli.