Student for thesis Characterisation of Battery Anodes for P2D Models

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Job-ID: MER0003XLT

P2D models are ideal for predictions of electrochemical behaviours of cells for electric vehicle application since they strike the right balance between complexity and predictive power. Solid-state diffusion is a process within the electrode that critically influences the rate capabilities during charging and discharging. In P2D models, this process is not fully understood especially in anodes such as graphite. Currently existing methods of modelling and characterisation, generally implemented in cathodes, does not fully work on graphite due to additional effects such as occurrence of phase transitions which necessitates alternative methodologies. The cell modelling lab focuses on the development of such methodologies. The focus of the work is to characterize solid-state diffusion through experiments and implement it in a P2D model.

Contents of the Master's Thesis

• Building graphite half cells (EL cells) of different electrode variations such as very thin electrodes, thickness variations and particle size variations
• Perform C-Rate tests at different temperatures
• Obtaining diffusion coefficients through fitting
• Use the obtained results to capture the behaviours of all electrode variations

The final topic determination takes place in consultation with the university, you and us.

The activity can begin from April 2026.

• Study: Engineering/Natural Sciences or anything comparable
• Basics of electrochemistry or electrical engineering
• Laboratory experience
• Interest to work on cell assembly and testing in the laboratory
• Basic levels of programming and basic familiarity with MATLAB

Additional Information:

We look forward to receiving your online application, including a resume, cover letter, certificates, current certificate of enrollment stating your semester, and proof of the standard period of study. Please remember to mark your documents as "relevant for this application" in the online form and observe the maximum file size of 5 MB.

You can find further information on the hiring criteria here.

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