|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||Funded by the Leverhulme Trust|
|Placed On:||24th July 2023|
|Closes:||1st March 2024|
Supervisor: Prof. Reinhard J. Maurer, Department of Chemistry & Department of Physics, University of Warwick
Funding: Home, EU, Overseas
Deadline: 01.03.2024, but applications will be considered on a rolling basis, please post for 90 days on FindAPhD or until the deadline (on jobs.ac.uk)
A fully funded 4-year PhD project in “Computational design of topological defects in graphene” is available with a flexible 2023-2024 start date. The project is open to candidates with a science Bachelor/Master’s degree (Physics, Chemistry, Materials Science) and includes a 4-year stipend with tuition fees. Successful candidates will become members of the interdisciplinary Computational Surface Science group (www.warwick.ac.uk/maurergroup) led by Prof. Reinhard Maurer based in the Departments of Physics and Chemistry at the University of Warwick, UK.
The nanomaterial graphene is ultrathin, ultra-strong and highly conductive. However, to find new real-world applications it must be tailored to a given function, e.g. to be more adhesive or to sense gases. Idealised graphene is a two-dimensional sheet of pure carbon. Its topology is defined by linked hexagonal rings of carbon; each hexagon perfectly identical to the next. By topologically designing defects to build graphene block by block with non-hexagonal rings, non-carbon atoms, or missing carbon atoms, we can controllably introduce new functionality to graphene that will enhance its applicability to support metal catalysts, to sense molecules, and to be used as components in nanoelectronic devices.
The goal of this PhD project is to develop and employ computational simulation and electronic structure theory approaches to identify how certain local defects can be created in two-dimensional graphene networks. The simulations will be done in close collaboration with experiment, in fact, they will directly inform which experiments will be conducted. We will aim to identify general design principles of local topological defect formation to identify which defects can be preserved in networks and which ones cannot. The project will also involve method and software development to enable large-scale simulations on high performance computing architectures such as the UK national supercomputer. Where surface superstructure models become too large for direct quantum mechanical calculations, acceleration techniques based on machine-learning methods will be employed. Upon successful completion of the computational screening and characterisation of defective graphene networks, we will study the ability of the grown networks to support new types of metal catalyst materials and nanostructured magnetic materials.
The studentship is part of a collaborative project funded by the Leverhulme Trust and will feature close collaboration with experimental project partners who synthesize organic molecular precursors and who perform surface synthesis and characterization of defective graphene. The student will work closely with experimental team members to directly inform which experiments will be conducted and to provide computational simulation support for the characterization of the structure and spectroscopic properties of experimentally fabricated two-dimensional networks.
Successful candidates will join a large, interdisciplinary research group that provides a collaborative and supportive environment. The PhD student will be trained in state-of-the-art electronic structure theory, molecular simulation methods, and machine learning methods, all of which are well established in the host group. The student will acquire important transferable skills such as software development (Python) and project management and present their research at international and national conferences.
Interested candidates should contact Prof. Reinhard Maurer (email@example.com).
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