Cation Disorder of Mg2SiO4 in Super‐Earth Mantles

Abstract Understanding the mineralogy of exoplanets is essential for unraveling their interior structures, dynamics, and evolution. For large super‐Earths, the post‐post spinel , one of the major mantle phases, may undergo the order‐disorder transition (ODT) at high temperatures. However, the ODT phase boundary of has not been rigorously constrained. Additionally, fundamental thermodynamic properties of the disordered remain poorly investigated. Here, we develop a unified machine learning potential (MLP) for of ab initio accuracy under super‐Earth mantle conditions. With the efficient MLP, we extensively calculate the free energy of post‐post spinel via the thermodynamic integration method. The results are used to constrain the ODT phase boundary. Furthermore, we report the P‐V‐T equation of state and Grüneisen parameters for post‐post spinel across various degrees of disorder. These thermodynamic properties are further applied to update the adiabatic thermal profiles and the mass‐radius relation of super‐Earths.

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Publication Details

Journal
Geophysical Research Letters
Published
2025-12-17
DOI
https://doi.org/10.1029/2025gl118419
Primary Topic
High-pressure geophysics and materials
Type
article
Field-Weighted Citation Impact
0.00

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article

Cation Disorder of Mg2SiO4 in Super‐Earth Mantles

Yihang Peng, Jie Deng, Rushi Gong, Yifan Li et al.
Geophysical Research Letters
High-pressure geophysics and materials
article

Cation Disorder of Mg2SiO4 in Super‐Earth Mantles

Yihang Peng, Jie Deng, Rushi Gong, Yifan Li, Zi‐Kui Liu, Dongyu Zheng
article en

Abstract

Abstract Understanding the mineralogy of exoplanets is essential for unraveling their interior structures, dynamics, and evolution. For large super‐Earths, the post‐post spinel , one of the major mantle phases, may undergo the order‐disorder transition (ODT) at high temperatures. However, the ODT phase boundary of has not been rigorously constrained. Additionally, fundamental thermodynamic properties of the disordered remain poorly investigated. Here, we develop a unified machine learning potential (MLP) for of ab initio accuracy under super‐Earth mantle conditions. With the efficient MLP, we extensively calculate the free energy of post‐post spinel via the thermodynamic integration method. The results are used to constrain the ODT phase boundary. Furthermore, we report the P‐V‐T equation of state and Grüneisen parameters for post‐post spinel across various degrees of disorder. These thermodynamic properties are further applied to update the adiabatic thermal profiles and the mass‐radius relation of super‐Earths.

Geophysical Research LettersVol. 52(24)
Pennsylvania State University (US), Princeton University (US)
National Science Foundation, U.S. Department of Energy
Openalex Percentile: Top 57%
High-pressure geophysics and materials
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