Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis
Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis
High entropy alloys (HEAs), a category of highly concentrated multicomponent alloys, have become a subject of interest in the past years due to their combination of properties. The development of these single phase solid solution alloys, containing between 5% and 35% of at least five different elements, has mainly relied on trial-and-error experiments, and more recently on modelling. The latter has notably focused on criteria to guide the formation of a single solid solution: (1) Hume-Rothery rules or their modification based on elemental variations in atomic radius, electronegativity, valence or number of itinerant electrons; (2) the use of thermodynamic concepts relying on estimates of enthalpy or entropy of mixing, and/or on melting or spinodal decomposition temperatures; (3) criteria based on lattice distortion; and (4) computational thermodynamics using the CALculation of PHAse Diagrams (CALPHAD) method. However, none of these criteria or methods, taken alone, can reliably predict the formation of a single solid solution. Instead, based on a critical assessment and a Gaussian process statistical analysis, a robust strategy to predict the formation of a single solid solution is proposed, taking into account most of the previously proposed criteria simultaneously. The method can be used as a guide to design new HEAs.
Data mining, HEA, Neural network, Thermo-Calc
486-497
Tancret, Franck
63962367-3fff-4cfc-a86c-e56a9fb962d2
Toda-Caraballo, Isaac
104b4ea9-5418-46cc-a90f-db65f449a1fb
Menou, Edern
4524f561-0d13-4f79-83fc-e39e9839b138
Rivera Díaz-Del-Castillo, Pedro Eduardo Jose
6e0abc1c-2aee-4a18-badc-bac28e7831e2
1 December 2016
Tancret, Franck
63962367-3fff-4cfc-a86c-e56a9fb962d2
Toda-Caraballo, Isaac
104b4ea9-5418-46cc-a90f-db65f449a1fb
Menou, Edern
4524f561-0d13-4f79-83fc-e39e9839b138
Rivera Díaz-Del-Castillo, Pedro Eduardo Jose
6e0abc1c-2aee-4a18-badc-bac28e7831e2
Tancret, Franck, Toda-Caraballo, Isaac, Menou, Edern and Rivera Díaz-Del-Castillo, Pedro Eduardo Jose
(2016)
Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis.
Materials and Design, 115, .
(doi:10.1016/j.matdes.2016.11.049).
Abstract
High entropy alloys (HEAs), a category of highly concentrated multicomponent alloys, have become a subject of interest in the past years due to their combination of properties. The development of these single phase solid solution alloys, containing between 5% and 35% of at least five different elements, has mainly relied on trial-and-error experiments, and more recently on modelling. The latter has notably focused on criteria to guide the formation of a single solid solution: (1) Hume-Rothery rules or their modification based on elemental variations in atomic radius, electronegativity, valence or number of itinerant electrons; (2) the use of thermodynamic concepts relying on estimates of enthalpy or entropy of mixing, and/or on melting or spinodal decomposition temperatures; (3) criteria based on lattice distortion; and (4) computational thermodynamics using the CALculation of PHAse Diagrams (CALPHAD) method. However, none of these criteria or methods, taken alone, can reliably predict the formation of a single solid solution. Instead, based on a critical assessment and a Gaussian process statistical analysis, a robust strategy to predict the formation of a single solid solution is proposed, taking into account most of the previously proposed criteria simultaneously. The method can be used as a guide to design new HEAs.
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Accepted/In Press date: 14 November 2016
e-pub ahead of print date: 23 November 2016
Published date: 1 December 2016
Keywords:
Data mining, HEA, Neural network, Thermo-Calc
Identifiers
Local EPrints ID: 492267
URI: http://eprints.soton.ac.uk/id/eprint/492267
ISSN: 0264-1275
PURE UUID: db918412-14e7-433a-88b1-fad4e21b834f
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Date deposited: 23 Jul 2024 16:40
Last modified: 24 Jul 2024 02:07
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Contributors
Author:
Franck Tancret
Author:
Isaac Toda-Caraballo
Author:
Edern Menou
Author:
Pedro Eduardo Jose Rivera Díaz-Del-Castillo
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