Cluster-Expansion Model for Complex Quinary Alloys: Application to Alnico Permanent Magnets
Abstract
An accurate and transferable cluster-expansion model for complex quinary alloys is developed. Lattice Monte Carlo simulation enabled by this cluster-expansion model is used to investigate temperature-dependent atomic structure of alnico alloys, which are considered as promising high-performance non-rare-earth permanent-magnet materials for high-temperature applications. The results of the Monte Carlo simulations are consistent with available experimental data and provide useful insights into phase decomposition, selection, and chemical ordering in alnico. The simulations also reveal a previously unrecognized D03 alloy phase. This phase is very rich in Ni and exhibits very weak magnetization. In conclusion, manipulating the size and location of this phase provides a possible route to improve the magnetic properties of alnico, especially coercivity.
- Authors:
-
- Ames Lab. and Iowa State Univ., Ames, IA (United States)
- Publication Date:
- Research Org.:
- Ames Lab., Ames, IA (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- OSTI Identifier:
- 1461654
- Alternate Identifier(s):
- OSTI ID: 1408065
- Report Number(s):
- IS-J-9496
Journal ID: ISSN 2331-7019; PRAHB2; TRN: US1902033
- Grant/Contract Number:
- AC02-07CH11358
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Physical Review Applied
- Additional Journal Information:
- Journal Volume: 8; Journal Issue: 5; Journal ID: ISSN 2331-7019
- Publisher:
- American Physical Society (APS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE
Citation Formats
Nguyen, Manh Cuong, Zhou, Lin, Tang, Wei, Kramer, Matthew J., Anderson, Iver E., Wang, Cai -Zhuang, and Ho, Kai -Ming. Cluster-Expansion Model for Complex Quinary Alloys: Application to Alnico Permanent Magnets. United States: N. p., 2017.
Web. doi:10.1103/PhysRevApplied.8.054016.
Nguyen, Manh Cuong, Zhou, Lin, Tang, Wei, Kramer, Matthew J., Anderson, Iver E., Wang, Cai -Zhuang, & Ho, Kai -Ming. Cluster-Expansion Model for Complex Quinary Alloys: Application to Alnico Permanent Magnets. United States. https://doi.org/10.1103/PhysRevApplied.8.054016
Nguyen, Manh Cuong, Zhou, Lin, Tang, Wei, Kramer, Matthew J., Anderson, Iver E., Wang, Cai -Zhuang, and Ho, Kai -Ming. Wed .
"Cluster-Expansion Model for Complex Quinary Alloys: Application to Alnico Permanent Magnets". United States. https://doi.org/10.1103/PhysRevApplied.8.054016. https://www.osti.gov/servlets/purl/1461654.
@article{osti_1461654,
title = {Cluster-Expansion Model for Complex Quinary Alloys: Application to Alnico Permanent Magnets},
author = {Nguyen, Manh Cuong and Zhou, Lin and Tang, Wei and Kramer, Matthew J. and Anderson, Iver E. and Wang, Cai -Zhuang and Ho, Kai -Ming},
abstractNote = {An accurate and transferable cluster-expansion model for complex quinary alloys is developed. Lattice Monte Carlo simulation enabled by this cluster-expansion model is used to investigate temperature-dependent atomic structure of alnico alloys, which are considered as promising high-performance non-rare-earth permanent-magnet materials for high-temperature applications. The results of the Monte Carlo simulations are consistent with available experimental data and provide useful insights into phase decomposition, selection, and chemical ordering in alnico. The simulations also reveal a previously unrecognized D03 alloy phase. This phase is very rich in Ni and exhibits very weak magnetization. In conclusion, manipulating the size and location of this phase provides a possible route to improve the magnetic properties of alnico, especially coercivity.},
doi = {10.1103/PhysRevApplied.8.054016},
journal = {Physical Review Applied},
number = 5,
volume = 8,
place = {United States},
year = {Wed Nov 08 00:00:00 EST 2017},
month = {Wed Nov 08 00:00:00 EST 2017}
}
Web of Science
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Works referencing / citing this record:
Robust cluster expansion of multicomponent systems using structured sparsity
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Robust cluster expansion of multicomponent systems using structured sparsity
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