Accurate and Reliable Prediction of Energetic and Spectroscopic Properties Via Electronic Structure Methods
Description: Computational chemistry has led to the greater understanding of the molecular world, from the interaction of molecules, to the composition of molecular species and materials. Of the families of computational chemistry approaches available, the main families of electronic structure methods that are capable of accurate and/or reliable predictions of energetic, structural, and spectroscopic properties are ab initio methods and density functional theory (DFT). The focus of this dissertation is to improve the accuracy of predictions and computational efficiency (with respect to memory, disk space, and computer processing time) of some computational chemistry methods, which, in turn, can extend the size of molecule that can be addressed, and, for other methods, DFT, in particular, gain greater insight into which DFT methods are more reliable than others. Much, though not all, of the focus of this dissertation is upon transition metal species – species for which much less method development has been targeted or insight about method performance has been well established. The ab initio approach that has been targeted in this work is the correlation consistent composite approach (ccCA), which has proven to be a robust, ab initio computational method for main group and first row transition metal-containing molecules yielding, on average, accurate thermodynamic properties, i.e., within 1 kcal/mol of experiment for main group species and within 3 kcal/mol of experiment for first row transition metal molecules. In order to make ccCA applicable to systems containing any element from the periodic table, development of the method for second row transition metals and heavier elements, including lower p-block (5p and 6p) elements was pursued. The resulting method, the relativistic pseudopotential variant of ccCA (rp-ccCA), and its application are detailed for second row transition metals and lower p-block elements. Because of the computational cost of ab initio methods, DFT is a popular choice ...
Date: August 2013
Creator: Laury, Marie L.