



Solid-state batteries (SSB) are expected to outperform standard lithium-ion technology in terms of energy density and safety, with application in electric vehicles or stationary energy storage. Manufacturing of these new battery technologies can rely on existing infrastructure (solvent-based electrode slurry mixing and coating) or need new processing methods. In this context, twin-screw extrusion process exhibits several advantages when applied to SSB, particularly with polymer-based electrolytes.
To speed up the implementation of polymer-based SSB, a better understanding of extrusion process applied to positive electrode manufacturing is needed. The objective of this thesis is to develop new electrode formulations using hot-melt extrusion and understand the impact of process parameters on final performances. It should finally give a clear picture about the advantages and limitations of extrusion compared to standard wet casting.
This PhD project will be part of a collaboration between CEA and Stellantis on the development of new solid-state batteries. The study will focus on the development of extrusion-processed composite electrodes to be used in polymer-based SSB. First, materials will be selected and characterized for a preliminary screening of formulations using lab-scale extrusion. Then, a systematic evaluation of the impact of input materials and operational conditions during extrusion process will be undertaken to highlight the relationships between process, electrode microstructures and performances. Finally, the best performing electrode formulations will be integrated in a fully-extruded prototype and characterized by electrical tests as well as post-mortem analysis.
The PhD candidate will benefit from CEA-LITEN's multidisciplinary environment (Grenoble campus) and Stellantis industrial know-how. Battery Prototyping Platform will be used for extrusion trials and cell assembly, whereas access to advanced characterization equipment (SEM, XPS, rheometers, electrochemical methods, etc.) will guarantee deep understanding of underlying mechanisms.

