Cross-sectional analysis of lithium ion electrodes using spatial autocorrelation techniques

Area of Science:

• Materials Science
• Electrochemistry
• Spatial Analysis

Background:

• Understanding material distribution is crucial for battery performance.
• Spatial autocorrelation analysis offers quantitative insights into material heterogeneity.

Purpose of the Study:

• To quantify the clustering and gradients of carbon, fluorine, and sodium in anode and cathode coatings.
• To correlate material distribution with experimental design parameters.

Main Methods:

• Employed join counting, a spatial autocorrelation technique.
• Utilized Energy-Dispersive X-ray Spectroscopy (EDS) mapping on cross-sectioned battery samples.
• Applied Design of Experiments (DoE) for systematic variation of coating parameters.

Main Results:

• Identified two primary types of heterogeneity: gradients and clustering.
• Observed greater clustering of carbon compared to fluorine in cathode samples.
• Correlated material distribution with input parameters like coating blade gap and speed, and output parameters like coat weight and electrochemical resistance.

Conclusions:

• Join counting is an effective method for characterizing material distribution in battery coatings.
• Uneven distribution of conductive carbon in cathodes may affect performance.
• Material heterogeneity is linked to specific coating process parameters.