Analysis of the rate-performance contributions in Li-ion batteries through Chronoamperometry

<jats:p>Battery rate performance, despite its increasing importance, lacks a standardized quantitative framework. This leads to a non-cohesive literature where is hard to establish fair comparisons and understand limitations. In recent years, significant efforts have been directed towards establishing this framework through models based on the master-curve concept. These relates the experimental data with physical parameters through empirical models, providing explainability to the rate behavior. Concurrently, chronoamperometry (CA) has emerged as a faster alternative to traditional galvanostatic cycling for obtaining this rate performance data. It offers richer datasets with high temporal resolution and continuous data. However, the higher amount of information, the presence of contributions poorly understood and the lack of information on how experimental parameters affect the results, has led to its under-utilization by the community. In this study, we systematically evaluated CA within the master-curve framework across four representative chemistries (two cathodes and two anodes). We developed a methodology to directly link impedance data with the master-curve model, which allowed us to give physical interpretation and an analytical derivation to the parameter "n", which until now was a non-physical fitting parameter. Combined, this resulted in the mechanistic description of the processes that occur at high-rates during the CA, and a more robust and physically grounded master-curve model. Additionally, we demonstrated that the selection of the voltage window in the CA, can alter key extracted parameters by up to an order of magnitude, provided a physical interpretation of this dependence, and proposed practical guidelines for the standardized reporting of results. Collectively, these findings enhance the robustness, reproducibility, and comparability of CA-based rate analyses, with direct implications for material evaluation and cell optimization.</jats:p>