机器学习势揭示下地幔中的氢扩散
Hydrogen diffusion in the lower mantle revealed by machine learning potentials
AI总结：
本文利用机器学习势分子动力学模拟研究下地幔布里奇曼石和后钙钛矿中的氢扩散，揭示其受温度、压力及缺陷机制影响，并为通过电导率非均质性推断下地幔水分布提供依据。
摘要：
氢可能以缺陷形式进入名义上无水的矿物，包括布里奇曼石和后钙钛矿，使地球深部地幔成为潜在的重要水储库。氢的扩散及其对下地幔电导率的贡献很少被探索，并且在很大程度上仍未受到约束。本文使用由从头算质量的机器学习势驱动的分子动力学模拟，计算了含水布里奇曼石和后钙钛矿中的氢扩散系数。研究结果表明，氢扩散系数随温度升高和压力降低而显著增加，并且对氢的并入机制相当敏感。在所考察的四种缺陷机制中，(Mg + 2H)$_{\ m Si}$ 和 (Al + H)$_{\ m Si}$ 表现出相似的模式，并产生最高的氢扩散系数。氢扩散通常在后钙钛矿中比在布里奇曼石中更快，并且这两个相表现出不同的扩散各向异性。总体而言，氢扩散在地质时间尺度上是缓慢的，可能导致下地幔中水分布的不均匀性。此外，布里奇曼石中 (Mg + 2H)$_{\ m Si}$ 和 (Al + H)$_{\ m Si}$ 缺陷的质子电导率与下地幔电导率处于同一数量级，这表明下地幔中的水分布可以通过考察电导率的非均质性来推断。
英文摘要：
Hydrogen may be incorporated into nominally anhydrous minerals including bridgmanite and post-perovskite as defects, making the Earth's deep mantle a potentially significant water reservoir. The diffusion of hydrogen and its contribution to the electrical conductivity in the lower mantle are rarely explored and remain largely unconstrained. Here we calculate hydrogen diffusivity in hydrous bridgmanite and post-perovskite, using molecular dynamics simulations driven by machine learning potentials of ab initio quality. Our findings reveal that hydrogen diffusivity significantly increases with increasing temperature and decreasing pressure, and is considerably sensitive to hydrogen incorporation mechanism. Among the four defect mechanisms examined, (Mg + 2H)$_{\rm Si}$ and (Al + H)$_{\rm Si}$ show similar patterns and yield the highest hydrogen diffusivity. Hydrogen diffusion is generally faster in post-perovskite than in bridgmanite, and these two phases exhibit distinct diffusion anisotropies. Overall, hydrogen diffusion is slow on geological time scales and may result in heterogeneous water distribution in the lower mantle. Additionally, the proton conductivity of bridgmanite for (Mg + 2H)$_{\rm Si}$ and (Al + H)$_{\rm Si}$ defects aligns with the same order of magnitude of lower mantle conductivity, suggesting that the water distribution in the lower mantle may be inferred by examining the heterogeneity of electrical conductivity.
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