COMPUTATIONAL STUDIES OF MAIN GROUP CLUSTERS AS CATALYSTS IN ORGANIC SYNTHESIS

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The industrial production of chemicals accounts for £34 Bn within the UK manufacturing sector, and up to 90% of chemical products require the use of a catalyst at some point in their preparation. These catalysts are often based on expensive precious metals such as palladium, platinum and rhodium, but excessive mining of these non renewable resources has exacerbated environmental and geopolitical issues associated with their use, as well as the costs. Developing alternatives based on earth abundant main group elements, such as phosphorus, is increasingly urgent and has garnered global attention.Industry favours heterogeneous catalysts because of their greater stability and recyclability, and lower separation/purification costs compared with homogeneous catalysts. One attractive and inexpensive heterogeneous material is red phosphorus, but its catalytic applications are in their infancy. Mechanistic investigations are essential to developing better catalysts, but heterogeneous materials can be difficult to study. Molecular clusters occupy an important middle ground between molecules and bulk solids, allowing them to act as stepping stones. For example, [P7] Zintl clusters can be viewed as a fragment of red phosphorus. Thus, improved understanding of the reactivity patterns of [P7] should inform the corresponding reactions with red phosphorus. It is therefore exciting that the Mehta group has recently found the first application of these clusters in the metal-free catalytic reduction of C=O bonds.[P7] clusters represent a new family of metal-free catalysts. Since discovering that they can mediate the reduction of C=O bonds, the Mehta group has also found that they are competent catalysts for the hydroboration of imines, nitriles and pyridines, and are expected to facilitate many other organic transformations. However, better mechanistic understanding is necessary in order to optimize existing transformations and to uncover new ones. Such understanding can be furnished in exquisite detail by computational quantum chemistry at the density functional theory (DFT) level, which can work in conjunction with experiment to optimise protocols and guide experiment to improved catalysts.This computational PhD project involves three work packages (WPs):WP1: Mechanism of imine, nitrile and pyridine reductions. This WP will establish the mechanism of the catalytic hydroboration of C-N multiple bonds and pyridines. As these catalytic transformations have already been established experimentally, the computational student will begin by working on well-characterized systems, thereby mitigating risk.WP2: New hydrofunctionalization catalytic transformations. WP2 will study how the energy profiles of the catalytic transformations change when the organic substrate is altered from C-N multiply bonded species to more ambitious non-polar multiple bonds, such as alkenes and alkynes. The reductant will also be tuned from hydroboranes to hydrosilanes, hydroamines and H2 gas. Computational predictions will be tested experimentally in the Mehta group, exploring these new catalytic reactions and identifying computed intermediates. Computationally-located transition states, and hence activation energies, will link with experimentally determined kinetic parameters.WP3: Improved catalyst design. The first generation transition metal free Zintl catalysts are based on phosphorus clusters with boron functional groups. WP3 will study how the energy profiles of the catalytic transformations change upon replacing the boron group by aluminium or indium moieties. In addition, the cluster component will be tuned from [P7] to [As7]; the latter feature weaker Group15-Group13 bonds which may alter catalytic behaviour. A number of such catalyst variants have already been synthesized in the Mehta group; optimization of these, and new variants, based on DFT predictions will also be explored experimentally.