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Multi-scale modelling of shear transformations in advanced materials for nuclear fusion

UCL - Mechanical Engineering

Qualification Type: PhD
Location: London
Funding for: UK Students, EU Students, International Students
Funding amount: Full tuition fees and maintenance stipend (currently £19,668/year)
Hours: Full Time
Placed On: 25th November 2022
Closes: 25th January 2023

Key information Lead supervisors: Dr Enrique Galindo-Nava
Application deadline: ongoing
Project start date: 25 September 2023
Project duration: 3.5 years
Eligibility: UK Students, EU Students, International Students
Studentship funding: full tuition fees and maintenance stipend (currently £19,668/year)

PhD project description

The realisation of nuclear fusion is seen as ultimate solution for sustainable energy production. Significant international efforts are in place to deliver a prototype power plant by 2040, being UK’s Tokamak the leading contender, but to achieve this several Material-related challenges must be addressed. A key issue in structural components is that no candidate steel has met the targets for high-temperature mechanical stability. Candidate steels mainly use shear transformations, primarily martensite and bainite, to tailor their nanostructure and final properties. Shear transformations are solid-state transitions that involve rapid and coordinated atomic displacements -resulting in a complicated nanostructure- and provide unique properties such as very high strength and the shape memory effect. There is however no first principles understanding of how the nanostructure forms and as consequence current material design strategies have not been able to tackle existing alloy limitations. Atomistic methods like Molecular Dynamics offer the possibility to deliver new understanding of nanostructure evolution but further work is required to link relevant transformation mechanisms across length- and time-scales.

This project will consist in developing new computational models to describe across the scales how the nanostructure forms during shear transformations and use this understanding to develop new alloys with improved mechanical performance. Main activities in the project shall include:

  • Develop new Machine Learning-based interatomic potentials describing equilibrium and non-equilibrium configurations of shear transformations in iron.
  • Combine the potentials with Molecular Dynamics and coarse-graining studies (based on kinetic Monte Carlo) to predict key atomic-scale processes over long time periods and suggest relevant features to optimise.
  • Mean field modelling to link the predicted transformation mechanisms with nanostructure evolution and design new steel structures with better mechanical and thermal stability.

We offer a unique opportunity to collaborate with a highly interdisciplinary team of academics and industrialists using state-of-the-art techniques on computational modelling and material characterisation. The project will likely involve interacting with colleagues at other institutions to expand and exploit the outcomes of the work. The successful candidate will be encouraged to attend international conferences and publish high-impact papers to disseminate the outcomes of the project.

Person specification

Applicants should have (or expect to be awarded) an upper second or first class UK honours degree at the level of MSci or MEng (or overseas equivalents) in a relevant Physics, Engineering or Science subject, including Materials Science, Engineering, Physics, Chemistry, Applied Mathematics or related disciplines. 

Fluency and clarity in spoken English as well as good written English in accordance with UCL English requirements (TOEFL>92 or IELTS>6.5) is required.

Eligibility

The position is open to UK, EU and International students.

Please refer to the following website for full eligibility criteria: Mechanical Engineering MPhil/PhD

How to apply

Eligible applicants should first contact Dr Enrique Galindo-Nava (e.galindo-nava@ucl.ac.uk). Please enclose:

  • A one-page statement outlining suitability for the project
  • A two pages CV (including contact details of two referees)

After discussing the project with Dr Galindo-Nava, eligible applicants should also submit a formal PhD application via the UCL website.

The supervisory team will arrange interviews for short-listed candidates.

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