Order–disorder in grossly non-stoichiometric SrFeO2.50 — a simulation study

Literature Information

Publication Date 2003-02-17
DOI 10.1039/B300137G
Impact Factor 3.676
Authors

Egil Bakken, Neil L. Allan, T. Hugh K. Barron, Chris E. Mohn, Ilian T. Todorov, Svein Stølen


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Abstract

Configurational lattice energy techniques are used to investigate oxygen vacancy ordering and the order–disorder transition in SrFeO2.50. Vacancy disorder is shown to present many new challenges, largely due to the extensive relaxation in such grossly non-stoichiometric systems. With large supercells it is not feasible to optimise each individual configuration. Efficient methods for choosing a small number of representative configurations are discussed. Oxygen vacancy–vacancy interactions are considerable in SrFeO2.50 and lead to the formation of preferred local structural entities. While the low-temperature structure consists of an ordered arrangement of octahedra and tetrahedra, the disordered high-temperature structure may be described as a mixture of tetrahedra, square pyramids and octahedra. Fe atoms with coordination numbers lower than four are negligible. The assumption of an ideal solution of oxygen vacancies in such systems, commonly made in standard thermodynamic treatments, is questionable.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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