基于神经网络势函数计算地球内核条件下的铁-硫合金黏度OA
Viscosity of Iron-Sulfur Alloy under the Conditions of the Earth Inner Core Calculated Based on the Neural Network Potential
地球内核的密度较纯铁低,表明其中存在轻元素.碳、氢、氧、硫、硅被认为是最可能存在于内核的轻元素.黏度是反映地球内核动力学和演化历史的关键物理量,对于地球内核波速各向异性的成因具有重要影响.前人已对内核条件下纯铁的六方密堆积(hexagonal close-packed,HCP)相和体心立方(body-centered cubic,BCC)相的黏度进行了模拟计算.然而,目前仍然缺乏针对地球内核中轻元素对地球内核黏度影响的系统性研究.为此,构建了内核条件下铁-硫合金的神经网络势函数,利用该方法实现了对铁-硫体系的大规模分子动力学模拟,研究了空位浓度低至0.01%时对该合金离子输运性质的影响.利用晶格中铁的自扩散系数研究了内核铁-硫合金的蠕变机制和黏度,将地球内核条件下铁-硫合金的黏度限定为1×1014～2×1016 Pa·s,与自由核章动以及地震波观测结果一致.
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.
XU Yunfan;HE Yu;ZHANG Wei;LI Heping
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,ChinaState 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,ChinaSchool of Karst Science,Guizhou Normal University,Guiyang 550025,Guizhou,ChinaState 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
数理科学
神经网络势函数地球内核自扩散系数黏度分子动力学
neural network potentialEarth's inner coreself-diffusion coefficientviscositymolecular dynamics
《高压物理学报》 2026 (1)
77-89,13
国家自然科学基金(42350002,42074104)中国科学院青年交叉团队项目(JCTD-2022-1)中国科学院青年创新促进会项目(2020394)贵州省2020年科技专项补助项目(NGZ2020SIG)
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