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A battery is a galvanic cell that is used as a source of electrical power for specific applications. Modern batteries exist in a multitude of forms to accommodate various applications, from tiny button batteries such as those that power wristwatches to the very large batteries used to supply backup energy to municipal power grids. Some batteries are designed for single-use applications and cannot be recharged (primary cells), while others are based on conveniently reversible cell reactions that...
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Related Experiment Video

Updated: Oct 29, 2025

Characterization of Electrode Materials for Lithium Ion and Sodium Ion Batteries Using Synchrotron Radiation Techniques
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Characterization of Electrode Materials for Lithium Ion and Sodium Ion Batteries Using Synchrotron Radiation Techniques

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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
PubMed
Summary
This summary is machine-generated.

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.

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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.