Computer modelling for the prediction and analysis of spectroscopic data: Application to lyotropic aggregates and transition metal centres

Prior, Christopher (2017) Computer modelling for the prediction and analysis of spectroscopic data: Application to lyotropic aggregates and transition metal centres. Doctoral thesis, University of East Anglia.

[thumbnail of 2017PriorCCPPhD.pdf]
Preview
PDF
Download (17MB) | Preview

Abstract

In this thesis Density Functional Theory (DFT) and Molecular Dynamics (MD)
simulations are used to predict, interpret and analyse a range of Electron Paramagnetic
Resonance (EPR) and Nuclear Inelastic Scattering (NIS) spectra of
di�erent molecular systems. By relating theory and experiment, the models are
rigorously tested as well as enabling a clearer interpretation of complex spectra.
Firstly, slow motion EPR spectra of microaggregate, micellar, hexagonal and
lamellar lyotropic liquid crystal aggregations are investigated for two di�erent
surfactant/water systems. Geometric parameters predicted from MD simulations,
such as aggregate radii and eccentricity, are compared with experimental
data and the dynamics investigated through the use of the Model-Free (MF)
approach, allowing for prediction of EPR spectra using the Stochastic Liouville
Equation (SLE) in order to relate dynamics and geometry. For the complex
hexagonal and lamellar lineshapes, the MF-SLE predicted spectra are compared
with those predicted directly and completely from MD. These techniques and
simulation approaches are then expanded to the investigation of the structure
and dynamics of spin labelled DNA. A scheme for rotation about triple bonds in
MD is found to produce good agreement with the spectra observed for acetylene
tethered spin labelled DNA using the new parmbsc1 force�eld.
The geometry and magnetic parameters of two molybdenum complexes are calculated
using DFT. The fast motion EPR spectra are then simulated using these
parameters, thereby con�rming the proposed rearrangement of core geometry in
the catalytic cycle.
Finally, the NIS spectra of a range of iron-sulphur clusters are predicted using
DFT for a series of model compounds and hypothetical structures and compared
with available experimental spectra. This tests both the accuracy of DFT and the
ability of NIS to discriminate between iron sulphur clusters, whilst additionally
con�rming spectral assignments.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Science > School of Chemistry
Depositing User: Stacey Armes
Date Deposited: 23 Mar 2018 16:42
Last Modified: 23 Mar 2018 16:42
URI: https://ueaeprints.uea.ac.uk/id/eprint/66590
DOI:

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item