ARCANA was so far demonstrated to generalize well across battery formats, electrolyte formulations, cathode chemistries and cycling procedures for LIBs. The ultimate generalization would be achieved if the model could also be deployed to Na-ion batteries. Since the underlying degradation mechanism of Na-ion batteries is very different, we performed fine-tuning to test whether M (B) and M (P ) are capable of achieving "true chemistry agnosticism" . These fine-tuned models are denoted M (B) N a and M (P ) N a , and are trained on Na-ion cycling data with CC-CV and pulse discharge settings. Details on the fine-tuning parameters are available in SI.