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Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis

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Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis. / Tancret, Franck; Toda-Caraballo, Isaac; Menou, Edern et al.
In: Materials and Design, Vol. 115, 05.02.2017, p. 486-497.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Tancret F, Toda-Caraballo I, Menou E, Rivera Díaz-Del-Castillo PEJ. Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis. Materials and Design. 2017 Feb 5;115:486-497. Epub 2016 Nov 23. doi: 10.1016/j.matdes.2016.11.049

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Tancret, Franck ; Toda-Caraballo, Isaac ; Menou, Edern et al. / Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis. In: Materials and Design. 2017 ; Vol. 115. pp. 486-497.

Bibtex

@article{eae896f2321b47dabb072771bd66d827,
title = "Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis",
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.",
keywords = "Data mining, HEA, Neural network, Thermo-Calc",
author = "Franck Tancret and Isaac Toda-Caraballo and Edern Menou and {Rivera D{\'i}az-Del-Castillo}, {Pedro Eduardo Jose}",
year = "2017",
month = feb,
day = "5",
doi = "10.1016/j.matdes.2016.11.049",
language = "English",
volume = "115",
pages = "486--497",
journal = "Materials and Design",
issn = "0264-1275",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis

AU - Tancret, Franck

AU - Toda-Caraballo, Isaac

AU - Menou, Edern

AU - Rivera Díaz-Del-Castillo, Pedro Eduardo Jose

PY - 2017/2/5

Y1 - 2017/2/5

N2 - 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.

AB - 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.

KW - Data mining

KW - HEA

KW - Neural network

KW - Thermo-Calc

U2 - 10.1016/j.matdes.2016.11.049

DO - 10.1016/j.matdes.2016.11.049

M3 - Journal article

AN - SCOPUS:85002524197

VL - 115

SP - 486

EP - 497

JO - Materials and Design

JF - Materials and Design

SN - 0264-1275

ER -