Doctoral Dissertations
Date of Award
5-2004
Degree Type
Dissertation
Degree Name
Doctor of Philosophy
Major
Chemistry
Major Professor
Jeff Kovac
Abstract
This dissertation contains the results of two different computational studies of adsorbed species. The dissertation is composed of two parts. In the first part we present research aimed at understanding the structural and dynamical properties of a single, partially adsorbed, model polymer chain. In the second part, we present research aimed at determining the minimum energy configuration of a single methane molecule adsorbed on the (100) face of MgO. These two studies are independent of each other, but both contribute to the general understanding of molecules adsorbed on surfaces. Here we provide a brief overview for each study. In the polymer study we simulated the dynamics of a single polymer chain partially adsorbed on an impenetrable surface using a Monte Carlo method. Two sets of simulations were performed. In one set we used the Local Jump (LJ) algorithm to simulate the motion of the polymer chain and in the other we used the Bond Fluctuation (BF) algorithm to simulate the chain’s motion. The objectives of this research were three-fold: (1) to determine the structural and dynamical scaling exponents for a partially adsorbed polymer chain; (2) to determine if the Rouse normal coordinates are the appropriate normal coordinates for a partially adsorbed chain; (3) to determine if the LJ and BF algorithms provide similar descriptions of the dynamics of the partially adsorbed polymer chain. The results of our polymer research show that the scaling exponents for the mean square end-to-end distance, the mean square radius of gyration and the diffusion constant are nearly the same for chains simulated using the LJ and BF algorithms. The scaling exponents for the relaxation times of the Rouse modes indicate the internal dynamics of a chain is different for the chains simulated using the LJ and BF algorithms. Using both algorithms we determined that the Rouse normal coordinates are not the appropriate normal coordinates for a partially adsorbed polymer chain. In the methane-MgO(100) study we used the electronic structure methods and empirical potential energy functions to investigate the minimum energy configurations of a single methane molecule adsorbed on a model MgO(100) surface. The primary goal of this research was to understand why the minimum energy configuration obtained using the electronic structure methods is different than the minimum energy configuration obtained using empirical potential energy functions. The results of our electronic structure calculations indicate that the electronic energy of the edge-down (C2v axis perpendicular to the MgO(100) surface) configuration of methane is significantly lower than that of the face-down (C3v axis perpendicular to the MgO(100) surface) configuration. Furthermore, our electronic structure results indicate that a single methane molecule in the near-surface electric field of MgO experiences significant polarization effects. Using the electronic structure results as our standard we assessed the accuracy of three empirical potential energy functions. We have shown that an empirical potential which treats the electrostatic component of the potential energy using a point charge model cannot accurately describe the electrostatic energy of both the edge-down and the face-down geometries using the same set of point charges. If we extend this approach by including the polarization of the methane adsorbate due to the electric field and field gradients of the MgO surface, we are still unable to account for all of the electrostatic and induction contributions obtained from the electronic structure calculations. Additionally, we show the charge equilibration method of Rappé and Goddard does not reproduce the induction effects indicated by the electronic structure calculations.
Recommended Citation
Stimac, Phil J., "Computational Studies of Molecules Adsorbed on Surfaces. " PhD diss., University of Tennessee, 2004.
https://trace.tennessee.edu/utk_graddiss/6857