Accelerating Battery Manufacturing Through Modeling and AI

Bridging the gap between laboratory breakthroughs and industrial-scale battery production remains one of the most critical bottlenecks in meeting the global demand for energy storage. This challenge is highly relevant for both industry engineers and academic researchers who must scale next-generation batteries efficiently without relying on costly, resource-intensive trial-and-error methods. To overcome this hurdle, digital modeling and simulation offers a powerful, predictive pathway to understand and optimize production at scale.

In this webinar, Dr. Franco of the Université de Picardie Jules Verne will introduce a comprehensive digital platform, ARTISTIC, that Franco and his team started developing over 13 years ago. ARTISTIC integrates multiscale physics-based simulations with artificial intelligence to digitalize battery manufacturing. Specifically, Franco will showcase how the team leveraged the COMSOL Multiphysics^® software to perform key electrochemical simulations within integrated workflows, demonstrating how it seamlessly connects with the team's manufacturing process simulations and machine learning. Franco will explore how these computational models decode the complex multiphysics interactions occurring across key manufacturing steps, from traditional wet processing (e.g., slurry mixing, drying, calendering, and electrolyte infiltration) to emerging dry manufacturing techniques.

The core value of this simulation framework lies in its ability to be rigorously validated against real-world data from the laboratory's in-house pilot line, providing actionable insights that accelerate process optimization and reduce waste. Finally, Franco will demonstrate how he and his team are bringing these computational tools directly to the factory floor using virtual and mixed reality. The audience will walk away with a clear understanding of how integrating physical manufacturing models, advanced electrochemical simulations via COMSOL^®, AI, and immersive technology can streamline decision-making, effectively train operators, and ultimately accelerate the deployment of intelligent battery production lines.