Probing Surface Degradation Pathways of Charged Nickel-Oxide Cathode Materials Using Machine-Learning Interatomic...

Area of Science:

• Materials Science
• Electrochemistry
• Computational Chemistry

Background:

• Nickel-based layered oxides are promising cathode materials for lithium-ion batteries due to high energy density.
• Instability of these cathodes upon full delithiation (charging) limits their practical application.
• The atomic-scale mechanisms of charged cathode degradation remain poorly understood.

Purpose of the Study:

• To elucidate the atomic-scale structural degradation mechanisms of fully delithiated lithium nickel oxide (LiNiO2) surfaces.
• To identify stable surface reconstructions and degradation pathways.
• To understand the role of oxygen loss and cation migration in cathode instability.

Main Methods:

• High-level ab initio calculations were employed to study surface energetics.
• Machine-learning interatomic potentials were developed for molecular dynamics simulations.
• Molecular dynamics simulations were used to explore ion migration and surface evolution.

Main Results:

• A previously unreported, stable reconstruction of the LiNiO2 (012) facet was identified.
• This reconstruction exhibits a lower oxygen vacancy formation energy compared to pristine surfaces.
• Nickel (Ni) ion migration into alkali-layer sites was observed as a kinetically plausible degradation initiation step.

Conclusions:

• The identified surface reconstruction and facile oxygen loss contribute to the instability of charged nickel-based cathodes.
• Nickel ion migration is a critical early step in the surface degradation process.
• These findings provide atomic-scale insights into cathode material decomposition, guiding future material design.