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Atomistic Simulation Informs Interface Engineering of Nanoscale LiCoO2
Spencer Dahl1, Toshihiro Aoki2, Amitava Banerjee3
1Department of Materials Science and Engineering, University of California, Davis, California 95616, United States.
Chemistry of Materials : a Publication of the American Chemical Society
|September 19, 2022
Summary
Atomistic simulations predict dopant behavior in lithium-ion battery cathodes. Computational modeling and experimental validation show dopant segregation at interfaces enhances cathode stability and performance.
Area of Science:
- Materials Science
- Electrochemistry
- Computational Chemistry
Background:
- Lithium-ion batteries are vital for energy storage, with cathode interface stability crucial for performance.
- Interfacial engineering via chemical modification can mitigate cathode degradation mechanisms.
- Understanding dopant behavior at cathode surfaces and grain boundaries is key for improved battery design.
Purpose of the Study:
- To computationally evaluate dopant interfacial segregation trends in LiCoO2 cathodes.
- To assess the predictive capability of atomistic simulations for cathode design.
- To investigate the segregation potential and stabilization effects of various dopants on LiCoO2 interfaces.
Main Methods:
- Atomistic simulations were used to study dopant segregation on LiCoO2 surfaces ({001}, {104}) and grain boundaries (Σ3, Σ5).
- A range of isovalent and aliovalent dopants (e.g., Mg2+, La3+, Ti4+, V5+) were computationally substituted into Co3+ sites.
- Scanning transmission electron microscopy-electron energy loss spectroscopy (STEM-EELS) was employed for experimental validation.
Main Results:
- Dopant segregation energy correlated linearly with ionic radius for different dopant valencies across surfaces and grain boundaries.
- Segregation potential varied with surface chemistry and grain boundary structure, with higher energies observed for the Σ5 grain boundary and {104} surface.
- Experimental validation confirmed predicted lanthanum enrichment at grain boundaries and surfaces in synthesized nanoparticles.
Conclusions:
- Atomistic simulations are effective predictive tools for understanding dopant interfacial segregation in cathode materials.
- Dopant selection based on ionic size and interface type can optimize cathode stability and battery performance.
- Experimental validation confirms the reliability of computational predictions for guiding cathode material design.
