Ab Initio Atomistic Simulations of Ca‐Perovskite Melting-Reference-Cited by-同舟云学术

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Ab Initio Atomistic Simulations of Ca‐Perovskite Melting

Published:2022-10-25 Issue:20 Volume:49 Page:
ISSN:0094-8276
Container-title:Geophysical Research Letters
language:en
Short-container-title:Geophysical Research Letters

Author:

Hernandez J.‐A.¹²^ORCID,Mohn C. E.¹^ORCID,Guren M. G.¹³^ORCID,Baron M. A.¹⁴^ORCID,Trønnes R. G.¹⁵^ORCID

Affiliation:

1. Centre for Earth Evolution and Dynamics University of Oslo Oslo Norway

2. Now at European Synchrotron Radiation Facility Grenoble France

3. Now at Njord Centre Department of Geoscience University of Oslo Oslo Norway

4. Now at Laboratoire de Chimie de la Matière Condensée de Paris, UMR 7574 Sorbonne Université, CNRS, Collège de France Paris France

5. Natural History Museum University of Oslo Oslo Norway

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021GL097262

Reference59 articles.

1. Melting Curve of MgO from First-Principles Simulations

2. Thermal pressure in the laser-heated diamond-anvil cell: An X-ray diffraction study

3. Stability of the body-centered-tetragonal phase of Fe at high pressure: Ground-state energies, phonon spectra, and molecular dynamics simulations

4. Melting of CaSiO 3 Perovskite at High Pressure

5. Silicate perovskite-melt partitioning of trace elements and geochemical signature of a deep perovskitic reservoir

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1. The thermal equation of state of the magma Ocean;Earth and Planetary Science Letters;2024-07

2. Ab initio constraints on the melting of silica at high pressures up to 500 GPa;Physical Review B;2024-01-18

3. Davemaoite as the mantle mineral with the highest melting temperature;Science Advances;2023-12-08

4. Influence of electronic entropy on Hellmann-Feynman forces in ab initio molecular dynamics with large temperature changes;Physical Review B;2023-10-19

5. Efficient Training of the Machine-Learning Interatomic Potential Based on an Artificial Neural Network for Estimating the Helmholtz Free Energy of Alkali Metals;Journal of the Physical Society of Japan;2023-05-15

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