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Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis

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
0264-1275
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
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, 486-497. (doi:10.1016/j.matdes.2016.11.049).

Record type: Article

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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More information

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
ORCID for Pedro Eduardo Jose Rivera Díaz-Del-Castillo: ORCID iD orcid.org/0000-0002-0419-8347

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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 ORCID iD

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