Modeling antiphase boundary energies of Ni3Al-based alloys using automated density functional theory and machine learning

Modeling antiphase boundary energies of Ni3Al-based alloys using automated density functional theory and machine learning

Antiphase boundaries (APBs) are planar defects that play a critical role in strengthening Ni-based superalloys, and their sensitivity to alloy composition offers a flexible tuning parameter for alloy design. Here, we report a computational workflow to enable the development of sufficient data to tra...

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Bibliographic Details
Main Authors: Asta, M. (Author), Chen, E. (Author), Epler, M.E (Author), Frolov, T. (Author), Tamm, A. (Author), Wang, T. (Author)
Format: Article
Language:English
Published: Nature Research 2022
Subjects:
Alloy compositions
Alloy designs
Antiphase boundaries
Antiphase boundary energies
Computation theory
Computational workflows
Density functional theory
Density-functional-theory
Machine learning
Machine learning models
Materials properties
Ni-based superalloys
Nickel alloys
Nickel compounds
Planar defect
Superalloys
Tuning parameter
Online Access:View Fulltext in Publisher

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