Finding a Needle in the Haystack: Identification of Functionally Important Minority Phases in an Operating Battery

Area of Science:

• Materials Science
• Electrochemistry
• Data Science

Background:

• Understanding minority phases is crucial for optimizing functional materials like batteries.
• Existing visualization methods need advanced data-mining for identifying minority phase functionalities.

Purpose of the Study:

• To develop and apply data-mining approaches for identifying minority phases in battery electrodes.
• To investigate the role of these phases in battery performance and degradation.

Main Methods:

• Utilized nanoscale X-ray spectromicroscopy on a functional LiCoO2/Li battery pouch cell.
• Applied novel data-mining techniques to analyze over 10 million X-ray absorption spectra.
• Examined more than 100 active cathode particles.

Main Results:

• Identified two cathode particles with unexpected chemical fingerprints.
• Provided direct evidence of undesired side reactions, including cation dissolution and precipitation.
• Linked local overlithiation to subparticle domain deactivation.

Conclusions:

• The developed data-mining approach effectively identifies critical minority phases in complex materials.
• Gained valuable insights into battery degradation mechanisms.
• The methodology is broadly applicable to heterogeneous systems where minority phases impact performance.