KAIST researchers identified a pathway to help electric-vehicle batteries charge faster without significant performance or lifespan losses by using a three-dimensional digital twin of a real graphite anode. The approach models how microscopic electrode variations can trigger lithium plating, uneven protective-film growth, mechanical stress, and degradation. By observing these failure precursors inside the digital representation, the team aimed to create design rules that reduce plating risk during high-rate charging. The study emphasizes digital simulation as a lever to move beyond slower, trial-and-error electrode optimization. For EV battery developers, the reported digital-twin workflow could support faster iteration cycles and more targeted materials and process changes aimed at improving charging durability. As charging-speed competition intensifies, modeling that predicts degradation pathways can become an increasingly valuable component of qualification and R&D planning.