The aim of the work presented in this thesis is to explore computational approaches to the modelling and discovery of spin crossover (SCO) transition metal complexes. Both ‘ab initio’ methods, based mainly on density functional theory, and empirical force fields based on ligand field molecular mechanics (LFMM) have been considered. It is shown that whilst a user can choose a functional and basis set combination through validation to experimental data which will yield accurate results for a series of related systems this combination is not necessarily transferable to other metal-ligand combinations. The ability of density functional approaches to model remote substituent effects is explored. Using the iron(II) R,R’pytacn complexes2 as a case study it is shown that whilst density functional approaches predict the correct trend for these substituted pyridine complexes there are occasional outliers. Traditional quantum approaches to the study of SCO, whilst accurate, are too time-consuming for the discovery of new complexes. Several LFMM parameter sets are optimised within this work. It is shown that this approach can accurately reproduce spin state energetics and geometries of iron(II) and cobalt(II) amines. A mixed donor type iron(II) amine/pyridine force field is also proposed. Through the utilisation of the drug discovery tools of the Molecular Operating Environment high throughput screening of cobalt(II) tetramine complexes is carried out. It is shown that ligands derived from macrocyclic rings display the most promise. These complexes, which are predicted to adopt a sawhorse geometry, show promise as SCO candidates are proposed as potential synthetic targets. This work illustrates the many exciting possibilities LFMM provides in the field transition metal computational chemistry allowing for theory to lead experiment rather than follow.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:667658 |
| Date | January 2015 |
| Creators | Houghton, Benjamin J. |
| Publisher | University of Warwick |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://wrap.warwick.ac.uk/72837/ |
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