4.7 Article

An integrated experimental and computational study of diffusion and atomic mobility of the aluminum-magnesium system

Journal

ACTA MATERIALIA
Volume 189, Issue -, Pages 214-231

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.actamat.2019.12.054

Keywords

Magnesium alloys; Diffusion coefficients; Atomic mobility; Density functional theory (DFT); Diffusion multiples

Funding

  1. Vehicle Technology Program of the Office of Energy Efficiency and Renewable Energy (EERE) of the U.S. Department of Energy [DE-EE0006450]
  2. U.S. Department of Energy, Office of Science, Basic Energy Sciences [DE-SC0012481]
  3. U.S. Department of Energy (DOE) [DE-SC0012481] Funding Source: U.S. Department of Energy (DOE)

Ask authors/readers for more resources

Diffusion between Al and Mg was investigated comprehensively using both high-throughput experiments and density functional theory (DFT) calculations. Experimental diffusion coefficients in fcc Al, hcp Mg, beta-Mg17Al3 and epsilon-Mg23Al30 phases were collected by combining diffusion multiples with forward-simulation analysis together with a critical review of the experimental studies in the literature. The best settings to compute the dilute (impurity) diffusion coefficients of Al and Mg using DFT were tested by comparing the computed data using various DFT settings with the critically assessed experimental diffusion coefficients in stable phases (fcc Al and hcp Mg). The optimal DFT settings were employed to calculate the dilute diffusion coefficients of Al and Mg in metastable (hypothetical) phases (hcp Al and fcc Mg) where experimental measurements were impossible. The atomic mobilities of Al and Mg in the Al-Mg binary system across the entire composition range were then reliably optimized for both the fcc and hcp phases based on the comprehensive diffusion data obtained from both experimental measurements for the stable phases and DFT calculations for the metastable phases. This study demonstrates an efficient and reliable way to develop fundamental mobility databases using integrated experimental and computational methods. (C) 2020 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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