Precessional Dynamics of Octahedra in CsPbBr3
Lucas Martin Farigliano1,2, Marcio S Gomes-Filho3, Alexandre Reily Rocha4
1Departamento de Física dos Materiais e Mecânica, Instituto de Física, Universidade de São Paulo, São Paulo, São Paulo 05508-090, Brazil.
Machine learning potentials enable large-scale simulations of halide perovskite dynamics. Octahedral rotations in CsPbBr3 primarily involve complex precession-nutation, not simple tilting sequences, revealing new insights into structural behavior.
Area of Science:
- Materials Science
- Solid-State Physics
- Computational Chemistry
Background:
- ABX3 halide perovskites feature corner-sharing BX6 octahedra crucial for their phases.
- These materials exhibit significant octahedral dynamics due to their soft mechanical nature and shallow energy landscape.
- Understanding these dynamics is key to their structural transitions and physical properties, but experimental and computational methods face limitations.
Purpose of the Study:
- To develop a machine-learning potential for accurate, large-scale molecular dynamics simulations of halide perovskites.
- To investigate the rotational dynamics of individual octahedra in CsPbBr3.
- To elucidate the dominant mechanisms of octahedral motion and challenge existing models.
Main Methods:
- Development of a novel machine-learning potential for simulating perovskite structures.
- Execution of large-scale molecular dynamics simulations with near-density functional theory (DFT) accuracy.
- Analysis of the temporal evolution and rotational behavior of individual BX6 octahedra in CsPbBr3.
Main Results:
- The study successfully simulated large-scale molecular dynamics of CsPbBr3 with high accuracy.
- Contrary to common assumptions, the typical a+ ⇒ a0 ⇒ a- tilting sequence was rarely observed.
- The dominant octahedral motion was identified as a complex precession-nutation process involving continuous reorientation and oscillations.
Conclusions:
- The findings reveal that halide perovskite octahedra exhibit complex rotational dynamics beyond simple tilting.
- These complex motions are likely prevalent across various halide perovskites, impacting their structural behavior.
- The developed machine-learning approach provides a powerful tool for future investigations and guides experimental efforts to detect these dynamics.
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