Experimental design of diagnostics currently lacks a systematic approach, based on the physical information that could derived from the data. Moreover, information is typically extracted by fitting lumped parameters that are only qualitatively connected with degradation mechanisms, such as the loss of active material, loss of lithium inventory, or increasing area-specific impedance . While such results from diagnostic tests provide valuable insights, they are difficult to connect unambiguously with root causes of degradation . These observed "symptoms" do not offer a direct mapping to specific mechanisms that can be rigorously captured in physical models, such as film resistance and electrolyte concentration loss .