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Ab initio random structure searching for battery cathode materials
Ziheng Lu1, Bonan Zhu2, Benjamin W B Shires1
1Department of Materials Science & Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, United Kingdom.
The Journal of Chemical Physics
|July 9, 2021
Summary
A new computational framework using ab initio random structure searching (AIRSS) efficiently predicts stable and metastable battery cathode materials. This approach explores vast chemical spaces, proposing novel transition-metal oxalates with excellent energy density and stability.
Area of Science:
- Materials Science
- Computational Chemistry
- Electrochemistry
Background:
- Rechargeable battery cathode discovery traditionally relies on time-consuming experimental trial-and-error and limited database searches.
- Existing methods overlook vast chemical spaces, particularly for metastable cathode materials crucial for advanced battery performance.
- The exploration of novel cathode materials is essential for developing next-generation energy storage solutions.
Purpose of the Study:
- To introduce and validate a computational framework for accelerated battery cathode material discovery.
- To demonstrate the efficiency of ab initio random structure searching (AIRSS) in identifying both stable and metastable cathode phases.
- To propose novel cathode materials with enhanced electrochemical properties.
Main Methods:
- Utilized ab initio random structure searching (AIRSS) to explore the potential energy surface and identify new crystal structures.
- Implemented constraints such as chemically aware minimum interatomic separations, cell volumes, and space group symmetries to delimit the search space.
- Validated the AIRSS framework by successfully rediscovering known crystal structures of LiCoO2, LiFePO4, and LixCuyFz.
Main Results:
- The AIRSS framework efficiently predicted thermodynamically stable and metastable cathode materials.
- The study analyzed the impact of various parameters (e.g., minimum separations, symmetries) on sampling efficiency.
- A novel family of transition-metal oxalate-based cathode materials was proposed, exhibiting superior energy density, oxygen-redox stability, and lithium diffusion kinetics.
Conclusions:
- The developed computational framework significantly enhances the efficiency and scope of battery cathode material discovery.
- AIRSS, with appropriate constraints, is a powerful tool for exploring complex materials' phase diagrams.
- The proposed transition-metal oxalates represent promising candidates for high-performance rechargeable batteries.
