Time for already our 12th Open Access Publication from project PULSELiON. What an achievement by the team! And there is more coming soon.
As 12th Open Access Publication from PULSELiON, we proudly present the journal article “A hybrid modelling approach coupling physics-based simulation and deep learning for battery electrode manufacturing simulations”, which has been published in the Journal for Energy Storage Materials, Volume 75, in February 2025.
Manufacturing of an optimized electrode can incur high production costs such as high energy consumption, high scrap rates and emissions. This is due to the process that consists of a series of manufacturing steps presenting a complex interrelationship, thus limiting the understanding of performance as a function of manufacturing parameters. By leveraging Deep Learning (DL), we can enhance our understanding of the complex manufacturing processes and accelerate its optimization.
In this article we report a new chemistry agnostic methodology, combining physics based simulations and deep learning, to simulate electrode slurries.
We are proud of this achievement within project PULSELiON, thanks to the authors from project partner CNRS: Utkarsh Vijay, Diego E. Galvez-Aranda, Franco M. Zanotto, Tan Le-Dinh, Mohammed Alabdali, Mark Asch and Alejandro A. Franco.
Feel free to download and read the work