Advancing All-Solid-State Battery Design via Stochastic Microstructure Modeling and Digital Twins in the DELFIN Project

Designing the microstructure of all-solid-state batteries (ASSB) is critical to achieve efficient solid-solid contact between active materials and solid electrolytes for ASSB functionality, yet experimental characterization remains highly challenging due to the extreme air and moisture sensitivity and toxicity of the used materials such as the widely used sulfur-based solid electrolyte LPSCl. To address this, the DELFIN project aims to accelerate the optimization of all-solid-state batteries by using digital microstructure design of ASSB cathodes and by developing a validated microstructure model for the performance of ASSB electrode microstructures. By integrating structure generators and AI-supported algorithms within the GeoDict environment, we are establishing "digital twins" that enable the prediction of electrochemical performance based on 3D structural parameters.

Recent developments have focused on enhancing the automated generation of complex microstructures, specifically implementing workflows for transforming 2D cross-sectional images into realistic 3D ASSB microstructures. Furthermore, we have advanced the implementation of electrochemical performance simulations to establish robust microstructure-property relationships. This allows a streamlined design pipeline consisting of gray image segmentation, statistical reconstruction, and performance prediction validation, aiming to reduce reliance on costly experimental trial-and-error approaches and facilitate the rapid deployment of next-generation solid state battery storage technologies.