Cross-Dataset Assessment of Cathode Thermal Descriptors for Whole-Cell Self-Heating Kinetics in Lithium-Ion Batteries: Onset, Reaction Magnitude, and Limits of Transferability

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Abstract
Component calorimetry is widely used to assess the thermal stability of lithium-ion battery cathode materials, yet it remains unclear which material-scale descriptors retain consistent relationships with whole-cell self-heating kinetics across independent datasets and test protocols. Here, raw accelerating rate calorimetry (ARC) and thermogravimetric/differential scanning calorimetry (TGA/DSC) data for lithium cobalt oxide (LCO), lithium iron phosphate (LFP), and nickel–cobalt–aluminum oxide (NCA) cells were reanalyzed using a physics-guided event framework. Cathode decomposition onset, event-specific apparent exothermic energy, and associated mass loss were compared with the maximum whole-cell self-heating rate. In the Sandia dataset, cathode onset and event-specific exothermic energy showed large matched-state-of-charge correlations with whole-cell self-heating kinetics (r = −0.983 and 0.980, respectively). In an independently generated dataset, the cathode–electrolyte onset relationship was substantially weaker (r = −0.376), whereas cathode–electrolyte reaction enthalpy retained a large association (r = 0.886). Rank-based sensitivity analysis preserved this contrast, whereas leave-one-chemistry-out stress tests were unstable for all three Sandia linear models, indicating that the strong within-dataset associations did not extrapolate reliably to an unseen chemistry. Because the two heat-release metrics were obtained under different sample configurations and calorimetric protocols, the cross-study comparison is interpreted at the descriptor-class level rather than as direct metric equivalence. Across the two conventional lithium-ion datasets examined, cathode-associated exothermic magnitude showed greater cross-dataset consistency than onset temperature alone. However, neither descriptor supported a universal chemistry-independent scaling law, indicating that component-to-cell relationships remain dependent on experimental protocol, electrode interactions, cell architecture, and battery platform.

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