Mechanistic insight into oxygen vacancy migration in SrFeO3−δ from DFT+U simulations
文献信息
Musa Alaydrus
SrFeO3−δ is known to be an effective oxygen ion conductor and oxygen vacancies are central to its performance. SrFeO3−δ displays four crystallographic structural transitions as it undergoes oxygen reduction over a broad range of operating temperatures. In this work, systematic density functional theory calculations using the Hubbard U correction were performed to understand oxygen vacancy interactions and migration as a function of vacancy concentrations in SrFeO3−δ (δ = 0–0.5). We found strong repulsion between oxygen vacancies at close distance while these oxygen vacancies are stabilized at further distance. We also found that the oxygen migration is highly anisotropic and the calculated effective migration energy for the oxygen migration tends to be high and increases from 0.91 eV to 1.30 eV as δ goes from 0.125 (tetragonal phase) to 0.25 (orthorhombic phase). In the ordered brownmillerite SrFeO2.625, the oxygen migration is restricted in the one-dimensional channel because of the highly anisotropic nature of the crystal structure, resulting in the relatively low effective migration energy of 0.49 eV. This explains the experimental activation energy of 0.55 ± 0.05 eV. These results suggest the importance of regulating the oxygen migration path via the crystal structure design toward development of a SrFeO3−δ based fast oxygen conductor.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.











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