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Improving accessible Li-ion cathode capacity through morphological control

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  • Full or part time
    Dr R Boston
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

The next generation of Li-ion batteries will not only require superior performance, cycle-life and power, but will need to be manufactured in an efficient and sustainable way. This project will seek to address some of the challenges still faced by current and future Li-ion cathode materials through the control of crystallite size and shape using reduced temperature synthesis methods.

This project will use a range of different synthesis methods including biotemplating, which uses biologically derived long-chain polymers to control crystallisation during calcination, and small molecule organic solvent synthesis. These techniques have been successfully use to create nano- and micron-scale structures in a wide variety of oxides, controlling particle shape whilst reducing the energy required for production, including in Na-ion cathode materials which are similar in structure to materials used in Li-ion.

This project will seek to improve specific capacity and mechanical stability through targeted control of crystallite morphology in NMC811 and related materials using biotemplating and similar techniques. Specific shapes e.g. nanowires (using e.g. seaweed derivatives) or hollow polycrystalline spheres will be synthesised and characterised. These will be fully characterised in-house using the world-class facilities available at Sheffield, including state-of-the art operando X-ray diffraction, high resolution transmission electron microscopy and battery testing, and where appropriate, at central facilities such as the Diamond Light Source. As such the successful candidate will be a self-motivated individual with a passion for improving energy storage at the interface of science and engineering.

The University of Sheffield is committed to building a motivated and diverse University community, where staff and students demand the highest standards from each other and work together to maximise the benefits of difference. We aim to create a corporate culture that is inclusive at all levels and in every system and process. Through our Equality and Diversity Strategy and Action Plans - Excellence Through Inclusion - we will work with and listen to people from across the University and beyond, to hear and help them tell the positive stories about what we have achieved already through inclusion and what we should be doing in the future.

Applicants should have (or expect to obtain) at least the equivalent of a 2.1 honours masters level degree in a relevant subject (e.g. engineering discipline, physics, (electro-)chemistry or equivalent). Experience with research, batteries, scanning electron microscopy and machine learning is desirable.

Recipients will have access to multiple networking opportunities, industry visits, mentorship, internships, as well as quality experiences that will further develop knowledge, skills, and aspirations

In order to apply for a Faraday Institution PhD position, you need to do both of the following:
1. Complete a Faraday Institution expression of interest form
2. Follow the university application process as per advert

Early application is strongly encouraged as if a suitable candidate is found then the advert may close before the end date.

Funding Notes

This position is fully funded for 48 months by the Faraday Institution and Department of Materials Science & Engineering.

Funding covers home tuition fees and annual maintenance payments of at least the Research Council minimum for eligible UK and EU applicants. EU nationals must have lived in the UK for 3 years prior to the start of the programme to be eligible for a full award (fees and stipend).

How good is research at University of Sheffield in Electrical and Electronic Engineering, Metallurgy and Materials?
Materials Science and Engineering

FTE Category A staff submitted: 34.80

Research output data provided by the Research Excellence Framework (REF)

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