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Probing Particle-Carbon/Binder Degradation Behavior in Fatigued Layered Cathode Materials through Machine Learning
Weibo Hua1,2,3, Jinniu Chen1, Dario Ferreira Sanchez4
1School of Chemical Engineering and Technology, Xi'an Jiaotong University, No.28, West Xianning Road, Xi'an, Shaanxi, 710049, China.
Angewandte Chemie (International Ed. in English)
|May 3, 2024
Summary
Investigating cathode materials in lithium-ion batteries (LIBs) reveals distinct degradation patterns. Machine learning and μ-XRD tomography pinpointed how particle size and cycling affect NCM622 and LLNMO performance.
Area of Science:
- Materials Science
- Electrochemistry
- Battery Technology
Background:
- Understanding reaction heterogeneity in cathode materials is crucial for optimizing lithium-ion battery (LIB) performance.
- Experimental verification of these complex reactions within LIBs remains a significant challenge.
Purpose of the Study:
- To investigate the impact of reaction heterogeneity on the electrochemical performance of Ni-rich layered LiNi0.6Co0.2Mn0.2O2 (NCM622) and Li-rich layered Li[Li0.2Ni0.2Mn0.6]O2 (LLNMO) cathode materials.
- To spatially map crystalline structure and microstrain evolution during cycling using advanced imaging and machine learning techniques.
Main Methods:
- Employed scanning μ-XRD computed tomography to analyze NCM622 and LLNMO cathode materials.
- Utilized machine learning (ML) to analyze a large dataset of μ-XRD patterns, identifying spatial distributions of crystal structure and microstrain.
- Correlated structural changes with particle size and location within the electrode composite.
Main Results:
- NCM622 demonstrated structural degradation and lattice strain dependent on secondary particle size, with smaller particles and particle surfaces experiencing greater fatigue.
- LLNMO exhibited severe strain-induced degradation in both surface and bulk regions during high-voltage cycling, leading to substantial voltage decay and capacity fade.
- Distinct degradation mechanisms were identified for NCM622 and LLNMO, influenced by particle morphology and cycling conditions.
Conclusions:
- The study highlights the critical role of microstructural characteristics and spatial heterogeneity in determining cathode material performance and degradation pathways in LIBs.
- Findings provide insights for designing advanced layered cathode materials with improved stability and longevity.
- The combined approach of μ-XRD tomography and ML offers a powerful tool for understanding and mitigating degradation in battery materials.
