PhD Studentship: Building Better Batteries: Modelling and Optimisation of Electrode Filling

Supervisors:  Dr. Ferran Brosa Planella, Dr. Radu Cimpeanu, Prof. Louis Piper

Summary:

Manufacturing not only has a significant impact on battery performance and lifetime, but also on cost and environmental impact. A key process (yet not a well-studied one) is the so-called filling, in which a liquid electrolyte is incorporated into the battery, occupying the pores in the electrodes. It requires keeping the battery at high temperatures for days, becoming a very expensive process both in terms of time and energy usage. In this project, you will have the opportunity to build exciting new capabilities for modelling and optimisation of electrode filling, with a potential to energise our understanding of battery manufacturing.

Manufacturing not only has a significant impact on battery performance and lifetime, but also on its cost and environmental impact. A key process (yet not a well-studied one) is the electrolyte filling, in which the liquid electrolyte is incorporated to the battery and let to fill the pores in the electrodes. This process requires keeping the battery at high temperatures for several days, becoming a very expensive step in battery manufacturing (both in terms of energy and time). In addition, if the electrodes are not fully wetted, the performance of the battery diminishes drastically. Understanding and optimising electrode wetting is key to improve battery performance and reduce the manufacturing cost, but this has mainly been addressed from the experimental side.

The focus of this project is on developing new models for electrode wetting, which can be used to understand and optimise this manufacturing process. We will start with standard models for flow in porous media and adapt them to the particularities of electrode wetting. Such models can later be extended to describe more complex phenomena, such as solvent penetration during the recycling process, or gas formation and metal dissolution during the battery operation.

For the success of this project, a combination of analytical (e.g. asymptotic analysis) and numerical approaches (e.g. finite volume methods) will be required to implement and validate the wetting models. It will be fundamental to deploy the implementations of the models so other researchers and industry can use them, thus the models will be built upon established packages such as PyBaMM and Basilisk. Along with the models, parameterisation tools will be developed and will incorporate uncertainty quantification, which is necessary given the stochasticity of the porous electrode materials.

About the CDT:

HetSys recruits enthusiastic students from across physical sciences, mathematics and engineering who enjoy using their mathematical skills and thinking flexibly to solve complex problems. By developing these skills HetSys trains people to challenge current state-of-the-art in computational modelling of heterogeneous, ‘real world’ systems across a range of research themes such as nanoscale devices, new catalysts, superalloys, smart fluids, space plasmas etc. They have recently been awarded £11m to train PhD cohorts in computation modelling.

Built around a closely knit, highly collaborative team of academics from five science departments at Warwick with a strong track record in leading large projects. With its project partners HetSys develops talented PhD students to push boundaries in this exciting field. The students have the potential to inspire new ideas, approaches & innovation & become future leaders in developing new technologies. HetSys builds on Warwick's cross-departmental scientific computing research community & the Warwick Centre for Predictive Modelling.

https://warwick.ac.uk/fac/sci/hetsys/themes/projectopportunities/

Previous applicants need not apply.

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