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Theory of spontaneous grain boundary roughening in high entropy alloys

Carolina Baruffi1, William Curtin1,2*

1 Laboratory for Multiscale Mechanics Modeling, École Polytechnique Fédérale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland

2 Faculty of Engineering, Brown University, Providence, RI 02912, USA

* Corresponding authors emails: William_Curtin@brown.edu
DOI10.24435/materialscloud:e7-77 [version v1]

Publication date: Nov 03, 2022

How to cite this record

Carolina Baruffi, William Curtin, Theory of spontaneous grain boundary roughening in high entropy alloys, Materials Cloud Archive 2022.134 (2022), doi: 10.24435/materialscloud:e7-77.

Description

High Entropy Alloys (HEAs) are a new broad class of near-random solid solution alloys that can possess some impressive mechanical and physical properties including high stability against grain growth (i.e. low grain boundary (GB) mobility). Here, it is shown that an initially flat GB in an HEA can become spontaneously rough, driven by natural local compositional fluctuations. Roughening lowers the total GB energy and thus can inhibit migration. A parameter-free theoretical framework is developed to demonstrate the energetics and size scales of the roughening in terms of solute/GB interaction energies and GB disconnection energies. Above a critical level of solute/GB interactions, a planar GB is predicted to roughen down to the scale of the GB periodic unit. A similar theory for 1D GBs (minimum periodic length in one direction) is also developed since such geometries are common in atomistic simulations. Specific predictions are made for the symmetric tilt boundaries Σ17 [100] (530) and Σ5 [100] (310) in a model CoCuFeNi alloy and atomistic simulations demonstrate roughening consistent with the theory. Analysis of the stresses needed to drive migration shows how migration can be inhibited or enhanced, rationalizing variations in mobility of GBs in HEAs.

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Keywords

High entropy alloys Grain boundaries Spontaneous roughening Pinning

Version history:

2022.134 (version v1) [This version] Nov 03, 2022 DOI10.24435/materialscloud:e7-77