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Title: Path integral Monte Carlo and density functional molecular dynamics simulations of warm dense MgSiO 3

Abstract

In order to provide a comprehensive theoretical description of MgSiO 3 at extreme conditions, we combine results from path integral Monte Carlo and density functional molecular dynamics simulations and generate a consistent equation of state for this material. We consider a wide range of temperature and density conditions from 10 4 to 10 8 K and from 0.321 to 64.2 g/cm -3 (0.1- to 20-fold the ambient density). We study how the L and K shell electrons are ionized with increasing temperature and pressure. We derive the shock Hugoniot curve and compare with experimental results. Our Hugoniot curve is in good agreement with the experiments, and we predict a broad compression maximum that is dominated by the K shell ionization of all three nuclei while the peak compression ratio of 4.70 is obtained when the Si and Mg nuclei are ionized. To conclude, we analyze the heat capacity and structural properties of the liquid.

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1];  [1]
  1. Univ. of California, Berkeley, CA (United States)
  2. Univ. of California, Berkeley, CA (United States); Univ. Claude Bernard, Lyon (France)
Publication Date:
Research Org.:
Univ. of California, Berkeley, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); National Science Foundation (NSF)
OSTI Identifier:
1593521
Grant/Contract Number:  
SC0016248; NA0003842; LFR-17-449059; 74160058; NSF ACI 1640776
Resource Type:
Accepted Manuscript
Journal Name:
Physical Review B
Additional Journal Information:
Journal Volume: 101; Journal Issue: 2; Related Information: https://journals.aps.org/prb/abstract/10.1103/PhysRevB.101.024107#supplemental; Journal ID: ISSN 2469-9950
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; statistical physics; plasma physics; fluid dynamics; condensed matter & materials physics

Citation Formats

González-Cataldo, Felipe, Soubiran, François, Peterson, Henry, and Militzer, Burkhard. Path integral Monte Carlo and density functional molecular dynamics simulations of warm dense MgSiO3. United States: N. p., 2020. Web. doi:10.1103/PhysRevB.101.024107.
González-Cataldo, Felipe, Soubiran, François, Peterson, Henry, & Militzer, Burkhard. Path integral Monte Carlo and density functional molecular dynamics simulations of warm dense MgSiO3. United States. doi:10.1103/PhysRevB.101.024107.
González-Cataldo, Felipe, Soubiran, François, Peterson, Henry, and Militzer, Burkhard. Tue . "Path integral Monte Carlo and density functional molecular dynamics simulations of warm dense MgSiO3". United States. doi:10.1103/PhysRevB.101.024107.
@article{osti_1593521,
title = {Path integral Monte Carlo and density functional molecular dynamics simulations of warm dense MgSiO3},
author = {González-Cataldo, Felipe and Soubiran, François and Peterson, Henry and Militzer, Burkhard},
abstractNote = {In order to provide a comprehensive theoretical description of MgSiO3 at extreme conditions, we combine results from path integral Monte Carlo and density functional molecular dynamics simulations and generate a consistent equation of state for this material. We consider a wide range of temperature and density conditions from 104 to 108 K and from 0.321 to 64.2 g/cm-3 (0.1- to 20-fold the ambient density). We study how the L and K shell electrons are ionized with increasing temperature and pressure. We derive the shock Hugoniot curve and compare with experimental results. Our Hugoniot curve is in good agreement with the experiments, and we predict a broad compression maximum that is dominated by the K shell ionization of all three nuclei while the peak compression ratio of 4.70 is obtained when the Si and Mg nuclei are ionized. To conclude, we analyze the heat capacity and structural properties of the liquid.},
doi = {10.1103/PhysRevB.101.024107},
journal = {Physical Review B},
number = 2,
volume = 101,
place = {United States},
year = {2020},
month = {1}
}

Journal Article:
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