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.

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    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:

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