MRS 2024 Invited Talk

Estimated time to read: 2 minutes

I was recently invited to speak on data-driven battery design and manufacturing at the Material Research Societies (MRS) Spring Meeting. This conference is held annually and is one of the largest for the materials field, so needless to say I was excited to attend. This year the conference was held in Seattle, which was the icing on the cake as it's an amazing city with, among other things, brilliant coffee shops.

As previously discussed on this website, my current research agenda is based around the parameterisation and optimisation of battery models. These models can have physics-based architectures as well as data-driven, black-box style formulations, both of which offer interesting solutions in materials design. In this talk I discussed the open source Python framework I've been developing with collaborators, PyBOP. This work aims to develop a unified library for battery model parameterisation, leading to parameter optimisation for design-based objective functions, i.e. which parameters and corresponding values result in the best electrochemical performance for a given operating condition. Below I've included the presentation I gave in my given thirty minute session.