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Updated: May 12, 2026
08:55
Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses
Published on: June 7, 2018
Covalent magnetism and magnetic impurities.
C Gruber1, P O Bedolla, P Mohn
1Center for Computational Materials Science, Vienna University of Technology, Gußhausstraße 25/134, A-1040 Vienna, Austria.
Summary
We introduce a covalent magnetism model for insulating materials, like carbon-doped barium titanate. This model explains magnetic order formation by favoring singly occupied orbitals, offering an alternative to the Stoner mechanism.
Area of Science:
- Condensed Matter Physics
- Materials Science
- Quantum Chemistry
Background:
- The Stoner mechanism, typically used for metals, is insufficient for explaining magnetism in insulators.
- Barium titanate (BaTiO3) doped with carbon presents a unique case for studying magnetic properties in insulating compounds.
Purpose of the Study:
- To adapt and apply the covalent magnetism model to insulating carbon-doped BaTiO3.
- To investigate the formation of magnetic order driven by singly occupied orbitals in this material.
- To develop a modified criterion for magnetic ordering applicable to insulators.
Main Methods:
- Utilizing the covalent magnetism model within a molecular orbital framework.
- Determining electron occupation numbers for spin-up and spin-down states.
- Performing ab initio calculations to simulate energy (E) as a function of magnetization (ℳ).
Main Results:
- A new criterion, analogous to the Stoner criterion but suitable for insulators, was formulated.
- The molecular orbital picture successfully described the covalent magnetism model.
- Simulated results from the model showed excellent agreement with ab initio calculations for E(ℳ).
Conclusions:
- The covalent magnetism model provides a viable explanation for magnetic ordering in insulating carbon-doped BaTiO3.
- The developed criterion offers a new tool for predicting magnetic properties in insulating systems.
- The study validates the model's accuracy through comparison with sophisticated ab initio calculations.
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