Up to 90% of chemical products require a catalytic step somewhere in their preparation. The catalysts that the manufacturing sector relies on to enable these transformations are often based on precious and depleting transition metals. Here, a new family of sustainable redox-active bismuth catalysts are targeted. These catalysts will be applied in halogen atom transfer processes (XAT) to build otherwise difficult C–C and C–N bonds that are of great importance to pharmaceutical and materials science. This project involves skills in organic and inorganic synthesis, spectroscopy, and computation chemistry.

Methods for the formation of fluorine-containing molecules that avoid the intermediacy of HF are highly sought after. Repurposing existing F-containing ‘waste’ streams can by envisaged by developing metal-mediated processes for F abstraction and re- delivery. This project targets the direct conversion of metal hydrides to metal fluorides using F-containing waste, and the use of the derived M-F systems in nucleophilic fluoride delivery.

High-quality medical imaging is critical for non-invasive diagnosis of, for example, malignant tumours, but is limited by the performance of the detectors currently available. We recently demonstrated BiOI single crystals to be 250 times more sensitive to X-rays than commercial a-Se detectors, opening up new opportunities to make medical imaging safer and faster. The key limiting factor is charge-carriers coupling to optical phonons, and in this project you will design and test new semiconducting materials in order to tune the structure, bond polarity and rigidity to further enhance performance and push the boundaries of ultra-sensitive radiation detectors.

Predicting new materials with large-scale computations and machine learning is a thriving research field. In this project, we will develop chemical ML models for structurally and compositionally complex inorganic materials – in particular, new glassy electrolytes for solid-state batteries – to be predicted and synthesised in the laboratory.

Electrocatalytic CO₂ reduction in aqueous medium requires a proper balance of protons, hydroxyls, carbonate ions and alkali-metal ions at the cathode and anode. By using Cu based catalysts, we have recently reported a pure-water-fed membrane–electrode– assembly system for CO₂ reduction to ethylene by integrating an anion-exchange membrane and a proton-exchange membrane, respectively, under forward bias with excellent stability at high Faradaic efficiency and current density towards ethylene. Here we propose to systematically investigate the support effects for the Cu phase to optimise best catalytic selectivity, activity and lifetime under neutral pH and gain controls in catalytic performance.

Amine-groups are widespread in pharmaceuticals, agrochemicals and many other important chemicals. An important route to their synthesis is via reduction of nitro groups, but available nitro reduction methods suffer from limited selectivity, rare-metal catalysts or use of heavy metals. This project builds on demonstrations of nitro group reductions at carbon, either via electrocatalysis or hydrogenation catalysis, and uses a combination of experimental methods (electrochemistry, GC, NMR, IR spectroelectrochemistry) to feed into a computational study of mechanism (via density functional theory and kinetic Monte Carlo) aiming at elucidating means of tuning selectivity to the amine product.

This project will be at the forefront of exploring new catalysts for the photocatalytic conversion of CO₂ to green chemicals. In particular, layered oxide chalcogenide and perovskite chalcogenide compounds with strong light absorption in the visible region of the solar spectrum will be targeted using solid-state synthesis (Clarke group) and studied in photocatalytic reactions (Steier group) with a focus on building an understanding of the chemical structure and catalytic properties including energy conversion efficiency, product selectivity and catalyst activity over time. You will be exposed to a wide range of techniques for bulk and thin-film synthesis, structural characterisation, spectroscopy and catalytic characterisation and hence develop a thorough understanding of how to tune structural, chemical and optical properties to enhance photocatalysis.

Plasma-assisted catalysis provides a way of ‘gaming’ the thermodynamic landscape, making new chemical pathways available and/or lowering barriers to existing pathways, without the required increase in temperature. This project seeks to elucidate key parameters in the important plasma regions - sensitive end-point chemistry, active gas-phase species and surface and gas phase properties - with a view to optimising catalyst materials and reactor design for the depolymerisation of olefins into hydrocarbons, hydrogen and other nitrogen-containing small molecules by atmospheric nitrogen plasma.

Sol-gel Electrospinning of ceramic fibers offers the possibility to manufacture ceramics with tuneable macroscopic shape, volume, density, and porosity (Grobert) enabling advanced SOEC design. Different choices of surfactants further open the possibility of designing the crystal facets with the best catalytic and stability properties as well as designing the texture and interface population in densified ceramics. Such choices will be informed by modeling (Wilson). This is a unique possibility to enable the synthesis of preferential interface populations (Marquardt) in SOEC for enhanced hydrogen production.

Biocatalysis is increasingly important in the manufacture of fine chemicals, including pharmaceuticals, aromas and flavours. This project focuses on cytochrome P450 monooxygenase enzymes which catalyse a vast array of oxygen-atom insertions. The project sets out to develop smarter routes to delivery of reducing equivalents to these enzymes based on interfacing hydrogenase with carefully selected carbon-based supports.

New catalysts and polymers using carbon dioxide and bio-derived heterocycles (e.g. epoxides, lactones, cyclic carbonates, anhydrides) are developed to produce engineering thermoplastics. These polymers are targeted for uses in electronics and automotive sectors, so understanding structure-performance-recycling behaviours is critical; experimental work is underpinned by machine learning to predict polymer properties using PolyAGM, an in-house database and software tool.

In recent work, we have demonstrated that fluorochemicals can be prepared from Fluorspar without the necessity to produce highly hazardous hydrogen fluoride. With global challenges in mind, this project will investigate the chemistry of fluoroapatite, the most abundant fluorine-containing mineral on earth, for the direct production of fluorinated materials.