Predicting the Hydration Free Energy of Small Alkanes and Alcohols from Custom, Electronic Structure-Based Force Fields
Mathematical theories reveal the fundamental physics involved in experimentalphenomena. Computer models of such theories are routinely used to corroborate or explain experiments and predict properties of chemical systems. Therefore, an important effort in computational chemistry is the development of more accurate and efficient chemical models. Current-generation models are only beginning to approach experimental-quality predictions of hydration free energies (HFEs).Using computations of quantum mechanical (QM) forces and classical simulations based on these forces, I investigate models to predict several properties of solutes and solutions. This dissertation is a collection of projects exemplifying methods used to gain insight into chemical systems. Simulations of bulk, supercooled, liquid water using a model based solely on QM data predict an exponential rise in the surface tension with increased supercooling, supporting the existence of a highly debated second phase of liquid water. A new method for computing static charges of atomic nuclei is derived, which offers a simple and physically sound method that can be used to investigate charge transfer in model systems and generate atomic charges for use in simulations. Formulae used to calculate HFEs and the assumptions under which they may be equated are investigated, demonstrating that, under physical conditions that validate ideal gas assumptions, theoretical and experimental HFE measurements should be directly comparable. This project also shows how to resolve disagreement between experimental and computational measurements made outside ideal conditions. Methods for developing custom, QM-based force fields (FFs) by Adaptive Force Matching are described, including specific details for FFs of aqueous methane, ethane, methanol, and ethanol. These FFs are used to predict HFEs and other properties in good agreement with experiments. These projects demonstrate the capability of computational methods to enhance scientific knowledge when carefully developed from sound theory. Using simple models constructed to reproduce the underlying QM characteristics of a system, classical simulations are able to accurately predict HFEs. Supplemental attachments to the dissertation include the first users’ manual for the CRYOFF software and a tutorial for using CRYOFF in Adaptive Force Matching.
computational chemistry, force fields, free energy, molecular modeling, simulations, solvation, thermodynamics, Other Chemistry, Physical Chemistry, Statistical, Nonlinear, and Soft Matter Physics
Networked Digital Library of Theses and Dissertations