Copper-catalysed asymmetric sulfide oxidation

The focus of this thesis is the preparation of enantiopure sulfoxides by means of copper-catalysed asymmetric sulfoxidation, with particular emphasis on the synthesis of aryl benzyl and aryl alkyl sulfoxides. Chapter 1 contains a review of the methods employed for the asymmetric synthesis of sulfoxides, compounds with many applications in stereoselective synthesis and in some cases with pharmaceutical application. Chapter 1 describes asymmetric oxidation, including metal-catalysed, non metal-catalysed and enzyme-catalysed, in addition to synthetic approaches via nucleophilic substitution of appropriately substituted precursors. Kinetic resolution in oxidation of sulfoxides to the analogous sulfones is also discussed; in certain cases, access to enantioenriched sulfoxides can be achieved via a combination of asymmetric sulfoxidation and complementary kinetic resolution. The design and synthesis of a series of sulfides to enable exploration of the substituent effects of the copper-mediated oxidation was undertaken, and oxidation to the racemic sulfoxides and sulfones to provide reference samples was conducted. Oxidation of the sulfides using copper-Schiff base catalysis was undertaken leading to enantioenriched sulfoxides. The procedure employed is clean, inexpensive, not air-sensitive and utilises aqueous hydrogen peroxide as oxidant. Extensive investigation of the influence of the reaction conditions such as solvent, temperature, copper salt and ligand was undertaken to lead to the optimised conditions. While the direct attachment of one aryl substituent to the sulfide is essential for efficient enantiocontrol, in the case of the second substituent the enantiocontol is dependent on the steric rather than electronic features of the substituent. Significantly, use of naphthyl-substituted sulfides results in excellent enantiocontrol; notably 97% ee, obtained in the oxidation of 2-naphthyl benzyl sulfide, represents the highest enantioselectivity reported to date for a copper-mediated sulfur oxidation. Some insight into the mechanistic features of the copper-mediated sulfur oxidation has been developed based on this work, although further investigation is required to establish the precise nature of the catalytic species responsible for asymmetric sulfur oxidation. Full experimental details, describing the synthesis and structural characterisation, and determination of enantiopurity are included in chapter 3.

Precursor chemistry for oxide related materials

This thesis describes modelling, synthesis, spectroscopic and physical characterisation, as well as application of Magnesium, Calcium and Copper β-diketonate, β-ketoiminate, β-diiminate, Schiff base, amide and fluorenyl compounds. The selected compounds could potentially find application in materials deposition using Atomic Layer Deposition (ALD), MOCVD, CVD and Sol-Gel techniques. Quantum chemical modelling was used as a tool to perform the comprehensive and rapid study of magnesium and calcium precursor molecules in order to predict which of them would be more successful in ALD of metal oxides. Precursor chemistry plays a key role in ALD, since precursors must be volatile, thermally stable, chemisorb on the surface and react rapidly with existing surface groups. This Thesis describes one aspect of this, surface reactivity between ligands and hydroxyl groups, via a gas-phase model with energetics computed at the level of Density Functional Theory (DFT). A number of different synthetic strategies, both aerobic and anaerobic, were investigated for the synthesis of the described metal complexes. These included the use of different metal starting reagents such as, anhydrous and hydrated inorganic metal salts, metal alkyls and Grignard reagents. Some of previously unreported metal complexes of homoleptic and heteroleptic magnesium, calcium and copper β-diketonates, β-ketoiminates, β-diiminates, amides and Schiff base type were synthesised and characterised: [Mg(hfpd)2(DipPa)], [Mg(hfpd)2(MapH)2], [Mg(hf-ebp)(THF)2], [Mg(tf-Pap)Cl(THF)2], [Ca(PhNacnac)2], [Cu(tf-Pap)2], [Cu(PhNacnac)2], [Cu(hf-ebp)], [Cu(DipPa)] and [Cu(DipPa)2(4,4’-bypy)]. A comprehensive study on the thermal properties of magnesium, calcium and copper β-diketonates, β-ketoiminates, β-diiminates, Schiff base, amide and fluorenyl complexes was performed using TGA and sublimation of selected compounds. Atomic Layer Deposition of MgO using magnesium β-ketoiminate – [bis{(4-N-phenyl)-2-pentonato} magnesium] and β-diketonate - [bis(1,1,1,5,5,5-hexafluoropentane-2,4-dionato)(THF)magnesium hydrate] was performed on Si(100) substrates at 180°C and 0.2 Torr using O2 plasma.

Combining and choosing case base maintenance algorithms

Case-Based Reasoning (CBR) uses past experiences to solve new problems. The quality of the past experiences, which are stored as cases in a case base, is a big factor in the performance of a CBR system. The system's competence may be improved by adding problems to the case base after they have been solved and their solutions verified to be correct. However, from time to time, the case base may have to be refined to reduce redundancy and to get rid of any noisy cases that may have been introduced. Many case base maintenance algorithms have been developed to delete noisy and redundant cases. However, different algorithms work well in different situations and it may be difficult for a knowledge engineer to know which one is the best to use for a particular case base. In this thesis, we investigate ways to combine algorithms to produce better deletion decisions than the decisions made by individual algorithms, and ways to choose which algorithm is best for a given case base at a given time. We analyse five of the most commonly-used maintenance algorithms in detail and show how the different algorithms perform better on different datasets. This motivates us to develop a new approach: maintenance by a committee of experts (MACE). MACE allows us to combine maintenance algorithms to produce a composite algorithm which exploits the merits of each of the algorithms that it contains. By combining different algorithms in different ways we can also define algorithms that have different trade-offs between accuracy and deletion. While MACE allows us to define an infinite number of new composite algorithms, we still face the problem of choosing which algorithm to use. To make this choice, we need to be able to identify properties of a case base that are predictive of which maintenance algorithm is best. We examine a number of measures of dataset complexity for this purpose. These provide a numerical way to describe a case base at a given time. We use the numerical description to develop a meta-case-based classification system. This system uses previous experience about which maintenance algorithm was best to use for other case bases to predict which algorithm to use for a new case base. Finally, we give the knowledge engineer more control over the deletion process by creating incremental versions of the maintenance algorithms. These incremental algorithms suggest one case at a time for deletion rather than a group of cases, which allows the knowledge engineer to decide whether or not each case in turn should be deleted or kept. We also develop incremental versions of the complexity measures, allowing us to create an incremental version of our meta-case-based classification system. Since the case base changes after each deletion, the best algorithm to use may also change. The incremental system allows us to choose which algorithm is the best to use at each point in the deletion process.