Computational chemistry employs mathematical algorithms, statistics, and large databases to integrate chemical theory with experimental observations. Computational modeling allows us to make predictions concerning molecular properties and reactivity that ultimately lead to accurate assessment of the most important fundamental properties of chemical systems. Advances in theoretical techniques and computer power have dramatically increased the usefulness and importance of computational chemistry as a complement to experimental studies. This is especially relevant to catalytic reactions of industrial importance as well as the analysis of structural properties and the resulting spectroscopic phenomena in what are often otherwise counterintuitive models. This dissertation is a representation of the research I performed during my years as a graduate student in the Chemistry Department at the University of North Texas. My research has examined novel carbenes as efficient organocatalysts, structure-based design and optimization of small molecule drugs, and surveying methods to accurately describe structure and bonding and catalytic abilities of inorganic and organometallic systems. The works presented herein have been published or are awaiting submission to peer-reviewed scientific journals. A variety of computational techniques were employed in studying metal-mediated catalysis and organocatalysis as well as the structural and photophysical properties of systems containing closed-shell transition metal ions.

The Abraham solvation model (ABSM) is an experimentally derived predictive model used to help predict various solute properties. This work covers various uses for the ABSM including predicting molar enthalpies of vaporization, predicting solvent coefficients for two new solvents (2,2,5,5-tetramethyloxolane and diethyl carbonate), predicting values for multiple new ionic liquids (ILs). This work also introduces a novel method for updating IL ABSM parameters by updating cation- and anion-specific values using linear algebra and binary matrices.