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Publishing Language: Chinese | Open Access

Viscosity of Iron-Sulfur Alloy under the Conditions of the Earth Inner Core Calculated Based on the Neural Network Potential

Yunfan XU1,2,3Yu HE1,2,3( )Wei ZHANG4Heping LI1,2
State Key Laboratory of Critical Mineral Research and Exploration, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, Guizhou, China
Key Laboratory of High-Temperature and High-Pressure Study of the Earth’s Interior, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, Guizhou, China
University of Chinese Academy of Sciences, Beijing 100049, China
School of Karst Science, Guizhou Normal University, Guiyang 550025, Guizhou, China
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Abstract

The density of the Earth’s inner core is lower than that of pure iron, indicating the presence of light elements. Among the candidate elements, carbon, hydrogen, oxygen, sulfur, and silicon are considered the most likely. Viscosity is a key physical property controlling the dynamics and evolutionary history of the inner core, and it has significant implications for the origin of seismic anisotropy. Previous studies have investigated the viscosity of pure iron in its hexagonal close-packed (HCP) and body-centered cubic (BCC) phases under inner-core conditions through computational simulations. However, the influence of light elements on the viscosity of the inner core remains insufficiently constrained. In this study, we constructed a neural network potential (NNP) for Fe-S alloy under inner-core conditions and employed it to perform large-scale molecular dynamics simulations. We systematically examined the impact of vacancy concentrations as low as 0.01% on the ionic transport properties of Fe-S alloy. Based on the self-diffusion coefficients of Fe in the lattice, we further explored the creep mechanisms and viscosity of Fe-S alloy under core conditions. Our results indicate that dislocation creep dominates the rheological behavior, yielding viscosities of 1×1014–2×1016 Pa·s, consistent with constraints from free-core nutation and seismic observations.

CLC number: O521.2 Document code: A

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Chinese Journal of High Pressure Physics

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Cite this article:
XU Y, HE Y, ZHANG W, et al. Viscosity of Iron-Sulfur Alloy under the Conditions of the Earth Inner Core Calculated Based on the Neural Network Potential. Chinese Journal of High Pressure Physics, 2026, 40(1). https://doi.org/10.11858/gywlxb.20251221

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Received: 09 October 2025
Revised: 11 December 2025
Published: 05 January 2026
© 2026 Editorial Office of Chinese Journal of High Pressure Physics

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc/4.0/)