Related Experiment Video
Updated: Jun 24, 2025
11:54
Growth and Electrostatic/chemical Properties of Metal/LaAlO3/SrTiO3 Heterostructures
Published on: February 8, 2018
10.3K
Local Ordering, Distortion, and Redox Activity in (La0.75Sr0.25)(Mn0.25Fe0.25Co0.25Al0.25)O3 Investigated by a
Boyuan Xu1, Jiyun Park2, Dawei Zhang3
1Department of Physics, Brown University, Providence, Rhode Island 02912, United States.
Chemistry of Materials : a Publication of the American Chemical Society
|June 3, 2024
Summary
Density functional theory combined with Metropolis Monte Carlo efficiently predicts cation ordering and thermodynamic properties in complex perovskite oxides for solar thermochemical hydrogen applications.
Area of Science:
- Materials Science
- Computational Chemistry
- Renewable Energy
Background:
- Mixing multiple cations in perovskite oxides creates configurational entropy and vast tunability.
- Compositionally complex perovskite oxides (CCPOs) are promising for solar thermochemical hydrogen (STCH) generation.
- Computational challenges exist in predicting cation configurations and properties of CCPOs.
Purpose of the Study:
- To demonstrate the efficiency of DFT-MC for sampling cation configurations in CCPOs.
- To investigate the effect of oxygen vacancies on cation ordering.
- To predict thermodynamic properties of CCPOs for STCH applications.
Main Methods:
- Density functional theory (DFT) combined with Metropolis Monte Carlo (MC) simulations.
- Analysis of cation site preference and short-range ordering in the presence of oxygen vacancies.
- Development of a statistical model for oxygen nonstoichiometry prediction.
Main Results:
- DFT-MC efficiently samples cation configurations in CCPOs, exemplified by (La0.75Sr0.25)(Mn0.25Fe0.25Co0.25Al0.25)O3.
- Oxygen vacancies significantly increase local cation site preference (short-range ordering).
- Cobalt (Co) identified as redox-active, with vacancies preferentially forming near Co due to stretched Co-O bonds.
- A clear definition of vacancy formation energy (Evf) for CCPOs is proposed.
- Predicted oxygen nonstoichiometry (δ) aligns with experimental van't Hoff analysis for enthalpy and entropy of reduction.
Conclusions:
- The DFT-MC workflow enables prediction of local ordering, redox activity, and thermodynamic properties of CCPOs.
- This computational approach facilitates the screening and design of CCPO materials for STCH applications.
- Accurate prediction of oxygen nonstoichiometry and thermodynamic parameters is crucial for material optimization.
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