Computational modelling of two-dimensional graphene-based materials

About the Project

Graphene is a novel material with outstanding electronic and mechanical properties. Chemical modification of graphene gives rise to new materials, such as graphene oxide and reduced graphene oxide, with properties very distinct from graphene and with possible applications in photocatalysis and batteries. However, determining their exact structure and structure-properties relationship remains challenging. Moreover, graphene can be combined with other two-dimensional materials, such as semiconducting phosphorene or insulating boron nitride, into multi-layer heterostructures. Because of these combinations of electronic properties, these two-dimensional heterostructures have great potential for use in electronics. Insight from computational modelling is needed to determine these materials’ chemical structure and its effect on their properties.

This project will use theoretical modelling (density-functional theory and Monte Carlo calculations) to investigate the structures of functionalised graphene-based materials, such as graphene oxide and reduced graphene oxide, in order to identify stable structures and predict their electronic properties. We will also study multilayers composed of graphene and other two-dimensional layered materials, such as phosphorene or transition metal dichalcogenides, to investigate how the properties of such multilayers are influenced by their interlayer interactions. The aim is to determine the structure-properties relationship, with a view to evaluate these materials’ suitability as sensors or as anodes in batteries.

Our group’s research is in computational modelling of materials, in particular for applications in solar energy, sensors and nanomaterials. We collaborate with experimental groups both at the University of Sheffield and in other universities. We are always looking to work with talented and motivated scientists.

Funding Notes

This project is for Self-funded students or students with external funding.