Development and application of effective quantum chemical strategies

Within the field of computational chemistry, one of the greatest challenges is predicting thermodynamic properties such as enthalpies of formation and interaction energies to understand chemical phenomena throughout the periodic table. To predict these properties at a quantitative level, high-level electronic structure methods, primarily ab initio methods, are used. These methods are not utilized as often when increasing molecule size due to the significant computational resources (disk space, memory, CPU time) required. Therefore, effective quantum chemical schemes that take advantage of numerous cost-effective methods are needed and this dissertation showcases their development and application towards main group and transition metal thermochemistry.In this dissertation, the pKa of late transition metal hydrides, which are important intermediates in catalytic reactions, were predicted with electronic structure methods including density functional theory (DFT) and ab initio methods. Insight into the thermochemistry and binding behavior of these hydrides is key to understanding metal-ligand behavior for inorganic and organometallic complexes.To utilize ab initio methods for high accuracy thermochemistry and circumvent their high computational cost, ab initio composite strategies, such as the correlation consistent Composite Approach (ccCA), were developed. In an effort to expand the size limitations of composite methodologies, ccCA was combined with the domain-based local pair natural orbital (DLPNO) methods. Denoted as DLPNO-ccCA, this method was developed for main group thermochemistry and targeted one of the largest molecules examined with composite methodologies. This methodology was expanded to key reaction types in organometallic chemistry, such as olefin insertion in hydroformylation, the largest volume homogeneous chemical reaction in chemical industry for chemical production, and metal-ligand dissociation. To investigate the vibrational behavior of chemical systems found in the interstellar medium, ccCA was used to generate potential energy surfaces (PESs) characterizing vibrational motion to predict anharmonic frequencies in tandem with vibrational self-consistent field (VSCF) and post-VSCF theory so that there is a reduction in the computational cost associated with generating accurate PESs for anharmonic mode-mode couplings as well as calculating contributions from anharmonic corrections to the potential.While ab initio methods are critical for attaining quality thermochemical predictions, addressing polyatomic molecules of increasing size and complexity, electronic structure methods like DFT are utilized due to the relative computational cost of DFT compared to ab initio methods. Applications in this dissertation include the modeling of the frontier orbitals of zinc porphyrin-fullerene supramolecular dyads with DFT to exhibit intramolecular charge transfer and the prediction of the binding energies for several drug-like molecules to polymer-based host compounds that display a binding pocket, which models protein-drug binding interactions, as part of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) blind prediction competition.