From the 1 of 70 linked papers with an AI index.
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70 papers
Melting Temperature of Iron Under the Earth's Inner Core Condition from Deep Machine Learning
Fulun Wu, Cai-Zhuang Wang, Kai-Ming Ho +3
Constraining the melting temperature of iron under Earth's inner core conditions is crucial for understanding core dynamics and planetary evolution. Here, we develop a deep potenti…
Deep-learning-based prediction of the tetragonalcubic transition in davemaoite
Fulun Wu, Yang Sun, Tianqi Wan +2
Davemaoite, i.e., perovskite (CaPv), is the third most abundant phase in the lower mantle and exhibits a tetragonal-cubic phase transition at high pressures and temperatu…
Ab initio study on the stability and elasticity of brucite
Hongjin Wang, Chenxing Luo, Renata M. Wentzcovitch
Brucite (Mg(OH)) is a mineral of great interest owing to its various applications and roles in geological processes. Its structure, behavior under different conditions, and uni…
Unveiling the effect of Ni on the formation and structure of Earth's inner core
Yang Sun, Mikhail I. Mendelev, Feng Zhang +5
Ni is the second most abundant element in the Earth's core. Yet, its effects on the inner core's structure and formation process are usually disregarded because of its electronic a…
Probing the state of hydrogen in -AlOOH at mantle conditions with machine learning potential
Chenxing Luo, Yang Sun, Renata M. Wentzcovitch
Hydrous and nominally anhydrous minerals (NAMs) are a fundamental class of solids of enormous significance to geophysics. They are the water carriers in the deep geological water c…
Thermoelastic properties of bridgmanite using Deep Potential Molecular Dynamics
Tianqi Wan, Chenxing Luo, Yang Sun +1
MgSiO_3-perovskite (MgPv) plays a crucial role in the Earth's lower mantle. This study combines deep-learning potential (DP) with density functional theory (DFT) to investigate the…