Multiscale insights enable rational design of solvent-free dry electrode processing for advanced battery electrode fabrication

High-performance electrodes can be fabricated using environmentally friendly dry processes instead of wet processes. A key material in dry processing is polytetrafluoroethylene (PTFE), which fibrillates under shear stress and forms a robust fibrous network essential for electrode integrity. However, the precise control of PTFE fibrillation is challenging owing to the complex transfer of shear forces from macroscale equipment to microscale particle dynamics. To address this, we present a multiscale optimization framework integrating finite element method simulations, Gaussian process regression, and Bayesian optimization to engineer PTFE fibrillation. Our model identifies the optimal particle size and particle-loaded pressure. It demonstrates that a 10 + 5 µm bimodal system with 14 MPa of particle-loaded pressure yields the most effective fibrillation. Electrodes are inversely designed using 10 + 5 µm particles, and enhanced electrochemical properties are experimentally validated. The proposed optimized dry electrode fabrication bridges microscale particle dynamics with large-scale processing. PTFE is a key material for the dry fabrication of battery electrodes, and controlling its fibrillation is key. Here, a computational framework for PTFE fibrillation identifies optimal particle size and particle-loaded pressure, validated by electrode fabrication.