Calendering of Li(Ni0.33Mn0.33Co0.33)O2‐Based Cathodes: Analyzing the Link Between Process Parameters and Electrode Properties by Advanced Statistics

The optimization of the calendering process represents one of the key tasks for tuning the lithium-ion battery performance. In this study, we present a systematic statistical-based study of the three main calendering parameters (namely, the applied pressure, roll temperature, and line speed) effect on the porosity, electrode mechanical properties and electronic conductivity. Our work main goal is to understand how by changing the calendering parameters, the electrode properties can be tuned and up to which degree they determine the electrode capacity of Li(Ni0.33Mn0.33Co0.33)O-2-based cathodes. The statistical tools used for the analysis were the analysis of the covariance (ANCOVA), the principal components analysis (PCA), and the unsupervised machine learning k-means clustering algorithm. Our results showed that while porosity and the mechanical properties depend mainly on the applied pressure, the electrode's conductivity correlates mainly with the temperature. All of them were found to influence the cathode's capacity (at a rate equal to C), being the best condition applied pressures between 60 and 120 MPa and roll temperatures between 60 and 75 degrees C.