Hydrogen Diffusion in the Lower Mantle Revealed by Machine Learning Potentials.

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)Si and (Al + H)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)Si and (Al + H)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. Plain Language Summary: Water or hydrogen may be trapped in the Earth's deep mantle, affecting the state and evolution of our planet. However, the mobility of hydrogen in the lower mantle remains poorly understood. By using advanced machine learning‐driven simulations, we find that hydrogen in lower‐mantle silicates diffuses faster at higher temperatures and lower pressures, and how hydrogen is incorporated into the silicates greatly influences this mobility. Two specific ways of hydrogen incorporation were found to allow hydrogen to move very efficiently. On a geological scale, the transport of hydrogen is slow, suggesting that water may be unevenly distributed in the Earth's lower mantle. The electrical conductivity associated with the movement of hydrogen aligns with previous observations of the Earth's mantle. Variations in electrical conductivity in the lower mantle may inform where water is located in the Earth's deep interior. Key Points: A machine learning potential of ab initio quality has been developed for hydrous MgSiO3 systemHydrogen diffusion is sluggish in both bridgmanite and post‐perovskite, leading to heterogeneous water distribution in the lower mantleProton diffusion may be associated with the variation of electrical conductivity in the deep mantle [ABSTRACT FROM AUTHOR]