Thermoelastic properties of bridgmanite using deep-potential molecular dynamics

Tianqi Wan, Chenxing Luo, Yang Sun, and Renata M. Wentzcovitch
Phys. Rev. B 109, 094101 – Published 4 March 2024

Abstract

The high-pressure Pbnm-perovskite polymorph of MgSiO3, i.e., bridgmanite (Bm), plays a crucial role in the Earth's lower mantle. It is likely responsible for ∼75 vol. % of this region and its properties dominate the properties of this region, especially its elastic properties that are challenging to measure at ambient conditions. This study combines deep-learning potential (DP) with density-functional theory (DFT) to investigate the structural and elastic properties of Bm under lower-mantle conditions. To simulate this system, we developed a series of potentials capable of faithfully reproducing DFT calculations using different functionals, i.e., local density approximation (LDA), Perdew-Burke-Ernzerhof parametrization (PBE), revised PBE for solids (PBEsol), and strongly constrained and appropriately normed (SCAN) meta–generalized-gradient approximation functionals. Our predictions with DP-SCAN exhibit a remarkable agreement with experimental measurements of high-temperature equations of states and elastic properties and highlight its superior performance, closely followed by DP-LDA in accurately predicting. This hybrid computational approach offers a solution to the accuracy-efficiency dilemma in obtaining precise elastic properties at high pressure and temperature conditions for minerals like Bm, opening a way to study the Earth material's thermodynamic properties and related phenomena.

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  • Received 13 July 2023
  • Revised 19 January 2024
  • Accepted 23 January 2024

DOI:https://doi.org/10.1103/PhysRevB.109.094101

©2024 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Tianqi Wan1,2, Chenxing Luo1, Yang Sun2,3,*, and Renata M. Wentzcovitch1,4,5,6,7,†

  • 1Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, USA
  • 2Department of Physics, Xiamen University, Xiamen 361005, China
  • 3Department of Physics, Iowa State University, Ames, Iowa 50011, USA
  • 4Department of Earth and Environmental Sciences, Columbia University, New York, New York 10027, USA
  • 5Lamont–Doherty Earth Observatory, Columbia University, Palisades, New York 10964, USA
  • 6Data Science Institute, Columbia University, New York, New York 10027, USA
  • 7Center for Computational Quantum Physics, Flatiron Institute, New York, New York 10010, USA

  • *yangsun@xmu.edu.cn
  • rmw2150@columbia.edu

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Issue

Vol. 109, Iss. 9 — 1 March 2024

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