Abstract
Solute atoms segregate and impose a retarding pressure, also known as solute drag pressure, at the grain boundary (GB) leading to reduced GB migration rates. The solute drag pressure depends critically on the segregation energy and the solute diffusivity across the GB. These parameters are, however, typically used as adjustable parameters to describe experimental observations. Here, we present an approach to analyze solute drag based on density functional theory (DFT) calculations. As an example, we apply the proposed approach to available experimental data for migration rates of the 30 ∘<111> GB in Au with Fe and Bi impurities at the ppm level. Based on the DFT calculations, Bi is identified as a strongly segregating element while Fe segregation is weak in comparison. The effective segregation energy for Bi is found to vary from −0.59 eV to −0.72 eV in the experimentally investigated temperature range of 500–610 K. Further, the activation energy for trans−GB diffusion of Bi is calculated with DFT to fall into the range of 0.5–0.6 eV. These DFT based values are consistent with those obtained by the conventional solute drag analysis of the experimental data using the Cahn−Lücke−Stüwe (CLS) model. The proposed approach is discussed in terms of its strengths for trend predictions as well as its quantitative uncertainties.
Originalsprache | Englisch |
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Aufsatznummer | 117473 |
Seitenumfang | 9 |
Fachzeitschrift | Acta materialia |
Jahrgang | 224.2022 |
Ausgabenummer | 1 February |
Frühes Online-Datum | 19 Nov. 2021 |
DOIs | |
Publikationsstatus | Veröffentlicht - 1 Feb. 2022 |
Bibliographische Notiz
Funding Information:The authors gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center ?Integrated Computational Material, Process and Product Engineering (IC-MPPE)? (Project No 859480). This program is supported by the Austrian Federal Ministries for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and for Digital and Economic Affairs (BMDW), represented by the Austrian research funding association (FFG), and the federal states of Styria, Upper Austria and Tyrol. The computational results presented have been achieved using the Vienna Scientific Cluster (VSC).
Funding Information:
The authors gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center “Integrated Computational Material, Process and Product Engineering (IC-MPPE)” (Project No 859480). This program is supported by the Austrian Federal Ministries for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and for Digital and Economic Affairs (BMDW), represented by the Austrian research funding association (FFG), and the federal states of Styria, Upper Austria and Tyrol. The computational results presented have been achieved using the Vienna Scientific Cluster (VSC).
Publisher Copyright:
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