Melting temperature of iron under the Earth's inner core condition from deep machine learning

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外文摘要：Constraining the melting temperature of iron under Earth's inner core conditions is crucial for under-standing 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 temper-ature at 1CB between the DP model and ab initio calculation and suggests the crucial contribution of elec-tronic 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.

外文关键词：

Inner core boundaryMelting temperatureMachine learningSolid-liquid coexistenceFree energy calculationMolecular dynamics simulation

作者：

Fulun Wu、Shunqing Wu、Cai-Zhuang Wang、Kai-Ming Ho、Renata M.Wentzcovitch、Yang Sun

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作者单位：

Department of Physics,Xiamen University,Xiamen 361005,China

Department of Physics,Iowa State University,Ames,IA 50011,USA

Department of Applied Physics and Applied Mathematics,Columbia University,New York,NY 10027,USA

Department of Earth and Environmental Sciences,Columbia University,New York,NY 10027,USA

Lamont-Doherty Earth Observatory,Columbia University,Palisades,NY 10964,USA

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出版年：

2024

DOI：

10.1016/j.gsf.2024.101925

地学前缘(英文版)

中国地质大学（北京）北京大学

地学前缘(英文版)

CSTPCD

影响因子：0.576

ISSN：1674-9871

年,卷(期)：2024.15(6)