Accurate and Efficient Modelling of X-ray Spectra for the Nuclear Fuel Cycle

Leading nations are transitioning to renewable energy and reducing carbon emissions with a major focus on increasing resource efficiency and sustainability. Nuclear power is an inevitable component of the solution; nuclear fuel is energy dense, has zero direct carbon emissions and has a small footprint in comparison to other zero-emission energy sources.

However, actinide chemistry is complex, and metal ions with different oxidation states can present vastly different reactivities, hence there is need to identify, quantify and characterise the atomic-scale nature of actinide species within the nuclear fuel cycle.

X-ray spectroscopies are frequently employed in chemical characterisation to provide information on local environment, oxidation state, and the nature of bonding in molecules and materials, making it a perfect technique for studying materials in the nuclear fuel cycle. However, heavy metal-containing systems often exhibit a rich spectrum due to multiplet splitting, and these complicated spectra are prone to misinterpretation. Multiconfigurational relativistic methods have been developed specifically to handle such difficulties and hence these methods are the state-of-the-art in computational modelling of X-ray spectra and can explain experimental data where other methods fail The focus of this project is to develop efficient, scalable, and accurate computational approaches for modelling X-ray spectra of actinide-containing molecules and materials to ultimately provide atomistic-level insight to the electronic structure and behaviour of these species within the nuclear fuel cycle.

The PhD student will develop computational approaches to model X-ray spectra of actinide complexes and materials relevant to the nuclear fuel cycle. A major focus of the PhD studentship will be the inclusion of extended environmental effects to model solid-state and solution actinide chemistry with several computational chemistry techniques (multiconfigurational methods with dynamic correlation corrections, periodic density functional theory, molecular dynamics).

Eligibility

2.1 honours degree in Chemistry, Physics, or a related discipline. 

Funding

At Manchester we offer a range of scholarships, studentships and awards at university, faculty and department level, to support both UK and overseas postgraduate researchers.

For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for.

Before you apply

We strongly recommend that you contact the supervisor(s) for this project before you apply.

How to apply

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