Melting Temperature of Iron Under the Earth's Inner Core Condition from Deep Machine Learning
arxiv(2024)
Abstract
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 potential (DP) model for iron that explicitly
incorporates electronic entropy contributions governing thermodynamics under
Earth's core conditions. Extensive benchmarking demonstrates the DP's high
fidelity across relevant iron phases and extreme pressure and temperature
conditions. Through thermodynamic integration and direct solid-liquid
coexistence simulations, the DP predicts melting temperatures for iron at the
inner core boundary, consistent with previous ab initio results. This
resolves the previous discrepancy of iron's melting temperature at ICB between
the DP model and ab initio calculation and suggests the crucial
contribution of electronic entropy. Our work provides insights into machine
learning melting behavior of iron under core conditions and provides the basis
for future development of binary or ternary DP models for iron and other
elements in the core.
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