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Enabling QM-accurate simulation of dislocation motion in γ−Ni and α−Fe using a hybrid multiscale approach
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Bianchini, F., Glielmo, A., Kermode, James R. and De Vita, A. (2019) Enabling QM-accurate simulation of dislocation motion in γ−Ni and α−Fe using a hybrid multiscale approach. Physical Review Materials, 3 (4). 043605. doi:10.1103/PhysRevMaterials.3.043605 ISSN 2475-9953.
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WRAP-enabling-QM-accurate-simulation-dislocation-motion-γ−Ni-α−Fe-using-hybrid-multiscale-approach-Kermode-2019.pdf - Published Version - Requires a PDF viewer. Download (2816Kb) | Preview |
Official URL: http://dx.doi.org/10.1103/PhysRevMaterials.3.04360...
Abstract
We present an extension of the ‘learn on the fly’ method to the study of the motion of dislocations in metallic systems, developed with the aim of producing information-efficient force models that can be systematically validated against reference QM calculations. Nye tensor analysis is used to dynamically track the quantum region centered at the core of a dislocation, thus enabling quantum mechanics/molecular mechanics simulations. The technique is used to study the motion of screw dislocations in Ni-Al systems, relevant to plastic deformation in Ni-based alloys, at a variety of temperature/strain conditions. These simulations reveal only a moderate spacing ( ∼ 5 Å ) between Shockley partial dislocations, at variance with the predictions of traditional molecular dynamics (MD) simulation using interatomic potentials, which yields a much larger spacing in the high stress regime. The discrepancy can be rationalized in terms of the elastic properties of an hcp crystal, which influence the behavior of the stacking fault region between Shockley partial dislocations. The transferability of this technique to more challenging systems is addressed, focusing on the expected accuracy of such calculations. The bcc α − Fe phase is a prime example, as its magnetic properties at the open surfaces make it particularly challenging for embedding-based QM/MM techniques. Our tests reveal that high accuracy can still be obtained at the core of a dislocation, albeit at a significant computational cost for fully converged results. However, we find this cost can be reduced by using a machine learning approach to progressively reduce the rate of expensive QM calculations required during the dynamical simulations, as the size of the QM database increases.
Item Type: | Journal Article | ||||||||||||||||||||||||||||||
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Subjects: | T Technology > TN Mining engineering. Metallurgy | ||||||||||||||||||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||||||||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Dislocations in metals, Quantum theory, Molecular dynamics, Nickel, Iron | ||||||||||||||||||||||||||||||
Journal or Publication Title: | Physical Review Materials | ||||||||||||||||||||||||||||||
Publisher: | American Physical Society | ||||||||||||||||||||||||||||||
ISSN: | 2475-9953 | ||||||||||||||||||||||||||||||
Official Date: | 16 April 2019 | ||||||||||||||||||||||||||||||
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Volume: | 3 | ||||||||||||||||||||||||||||||
Number: | 4 | ||||||||||||||||||||||||||||||
Article Number: | 043605 | ||||||||||||||||||||||||||||||
DOI: | 10.1103/PhysRevMaterials.3.043605 | ||||||||||||||||||||||||||||||
Status: | Peer Reviewed | ||||||||||||||||||||||||||||||
Publication Status: | Published | ||||||||||||||||||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||||||||||||||||||||
Date of first compliant deposit: | 17 April 2019 | ||||||||||||||||||||||||||||||
Date of first compliant Open Access: | 17 April 2019 | ||||||||||||||||||||||||||||||
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