Guy Olivier Ngongang Ndjawa

The rapid expansion of electric vehicle (EV) adoption, particularly in alignment with Saudi Vision 2030's sustainable energy diversification goals, demands advanced battery technologies that ensure both safety and performance at scale. Lithium-metal anodes in high-capacity EV batteries are susceptible to filamentary dendrite growth at the anode/electrolyte interface, significantly impacting battery performance, safety, and the viability of mass EV deployment. In this study, we introduce a modelling framework to achieve dendrite-free electro-deposition by applying constraints to the phase-field evolution, directly addressing key technological barriers to EV battery reliability and longevity. Specifically, dendrite formation is mitigated by constraining the system evolution through a cost function consistent with dendrite-free morphologies essential for safe, long-lasting EV applications. We develop a coupled phase-field model comprising a non-conserved Allen–Cahn equation describing the metal–electrolyte interface dynamics, a reaction–diffusion model capturing ionic transport, and electrostatic charge conservation. We present a comprehensive mathematical formulation amenable to machine learning models, including governing equations, boundary conditions, and energy-based constraints. Leveraging a variational approach to estimate the free-energy functional, we derive a modified phase-field state equation that systematically steers electro-deposition away from dendrite-forming pathways, thereby enhancing battery safety and cycle life crucial for EV market penetration and supporting sustainable transportation goals.