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  • 标题:High-throughput ab-initio dilute solute diffusion database
  • 本地全文:下载
  • 作者:Henry Wu ; Tam Mayeshiba ; Dane Morgan
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2016
  • 卷号:3
  • DOI:10.1038/sdata.2016.54
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:We demonstrate automated generation of diffusion databases from high-throughput density functional theory (DFT) calculations. A total of more than 230 dilute solute diffusion systems in Mg, Al, Cu, Ni, Pd, and Pt host lattices have been determined using multi-frequency diffusion models. We apply a correction method for solute diffusion in alloys using experimental and simulated values of host self-diffusivity. We find good agreement with experimental solute diffusion data, obtaining a weighted activation barrier RMS error of 0.176 eV when excluding magnetic solutes in non-magnetic alloys. The compiled database is the largest collection of consistently calculated ab-initio solute diffusion data in the world.
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