PhD Studentship: Multiscale Modelling for Energy Storage Devices with Smart Shapes and Intelligent Functions

University of Birmingham - School of Chemical Engineering

Supervisor: Dr Adriano Sciacovelli

Funding:   University Scholarship covering tuition fees and stipend at EPSRC rates (£14,340 per annum) for UK or EU students only.

This is a unique research opportunity for a motivated student to undertake research that spans across the disciplines of energy engineering and computational sciences. The successful candidate will join the Birmingham Centre for Energy Storage (School of Chemical Engineering, University of Birmingham). The Centre has a strong record in fundamental and applied research in energy storage, conversion, transportation, renewable energy systems and next generation technologies for energy demand reduction.

Energy storage, both thermal and electrical, will transform the way we produce, convert and use energy in the future. It is however crucial to design storage devices capable to deliver optimal functions such as fast charging and discharging, high power density and manufacturability (e.g. 3d printing). Traditional modelling and optimization tools often fail to appropriately predict multiphysics coupled phenomena (thermal, electrical and mechanical) and to capture the necessary links between properties, structure and performance, leading to thermal/electrical batteries without the desired performance, reliability and functions.

In this project we aim to develop and connect computational methods (e.g. CFD, computational heat&mass transfer, computational chemistry, etc.) with advanced optimization methods (e.g. shape/topology optimization) to develop and test innovative configuration performance of energy storage devices (thermal and/or flow batteries) with smarter and more intelligent performances. The primary aims of the project are:

  1. Develop and apply multiscale computational and optimization methods for energy storage devices
  2. Design energy storage devices with advanced functionality and smart behavior
  3. Validate the computational methods and the corresponding benefits

The ultimate goal is to develop and validate a modelling&optimization techniques which will transform the way we design and manufacture energy storage devices.

This PhD is linked to an academic project funded by the UK research council and in collaboration with Renishaw – a world leading company in 3d printing. The successful candidate will have therefore the opportunity to work closely with both academics and industrial experts.

Phd candidate specification:

We are looking for creative and motivated applicants with First or Upper Second degree (or equivalent) in energy/mechanical engineering, computational engineering or a related subject with a strong component in modelling (e.g. physics, computer science, mathematics). Candidates with previous experience in modelling (for example Comsol, OpenFoam, etc) and programming (for example Matlab, C++, Fortran, etc) are encouraged to apply.

If you wish to discuss any details of the project informally, please contact Dr Adriano Sciacovelli (Email: ).

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Midlands of England