Computer Modelling of SnO2-based sensor materials

Project ID: 2228cd1354 (You will need this ID for your application)

UCL Lead department: Chemistry

Lead Supervisor: Rob Bell

Project Summary:

Gas sensors play a crucial role in many applications, from ensuring air quality in indoor environments to monitoring toxic gases in industrial settings. SnO2 sensors have gained significant attention due to their high sensitivity, stability, and effectiveness in detecting various gases. The working principle of tin dioxide sensors relies on a change in electrical conductivity when exposed to different gases. The mechanism is known to be facilitated by the presence of oxygen vacancies at the SnO2 surface(s), but there are aspects of the chemistry which remain poorly understood. Computational modelling studies1 on these materials have tended to focus on local surface structure and defect chemistry. In order to examine aspects such as temperature-dependent behaviours, competitive adsorption from the bulk gas phase, and a broad range of defect concentrations, larger scale simulations are required.
In this PhD project we will use large-scale molecular dynamics simulations to study the surfaces of SnO2 (cassiterite), and related structures, interacting with gas phase mixtures. This will enable the introduction of variables not accessible in electronic structure calculations, e.g. (1) concentrations of bulk gas phase components; (2) variable temperature; (3) nature, location and concentration of defects; (4) nanostructuring. The goal will be to develop in-depth models for the diffusion and adsorption of molecules such as CO, O2, and methanol. These could then also be used to inform DFT calculations. The student will receive training in both state-of-the-art molecular dynamics simulations and DFT, as well as exposure to the field of gas sensor technology. The project will be under the supervision of Dr Rob Bell, an expert in simulation of materials, collaborating with Prof Chris Blackman, whose experimental research programme is in the field of gas sensor materials. The successful applicant will have a good masters degree in chemistry, physics or materials science.