Calendering of Li(Ni _0.33 Mn _0.33 Co _0.33 )O ₂ ‐Based Cathodes: Analyzing the Link Between Process Parameters and Electrode Properties by Advanced Statistics

The optimization of the calendering process represents one key tasks for tuning lithium-ion battery performance. In this study, we present a systematic statistical-based study three main parameters (namely, applied pressure, roll temperature, and line speed) effect on porosity, electrode mechanical properties electronic conductivity. Our work goal is to understand how by changing parameters, can be tuned up which degree they determine capacity Li(Ni0.33Mn0.33Co0.33)O2-based cathodes. statistical tools used analysis were covariance (ANCOVA), principal components (PCA), unsupervised machine learning k-means clustering algorithm. results showed that while porosity depend mainly electrode's conductivity correlates with temperature. All them found influence cathode's (at rate equal C), being best condition pressures between 60 120 MPa temperatures 75 °C.