Designing high entropy alloys employing thermodynamics and Gaussian process statistical analysis. (5th February 2017)

• Record Type: Journal Article
• Authors: Tancret, Franck; Toda-Caraballo, Isaac; Menou, Edern; Rivera Díaz-Del-Castillo, Pedro Eduardo Jose
• Is Part Of: Materials & design. Volume 115(2017)
• Page Start: 486
• Page End: 497
• Publication Date: 2017-02-05
• Subjects: HEA -- Neural network -- Thermo-Calc -- Data mining; Materials -- Periodicals; Engineering design -- Periodicals; Matériaux -- Périodiques; Conception technique -- Périodiques; Electronic journals; 620.11
• DOI: 10.1016/j.matdes.2016.11.049
• Languages: English
• ISSNs: 0264-1275

Abstract

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. Graphical abstract: Highlights: CALPHAD performance is assessed on > 320 highly concentrated multicomponent alloys using several thermodynamic databases. CALPHAD or couples of physical parameters alone cannot predict reliably the formation of High Entropy Alloys (HEAs). Gaussian processes give a probabilistic prediction of single phase formation in highly concentrated multicomponent alloys. Combining CALPHAD and Gaussian processes allows to define a robust criterion for HEA formation. The new approach can be used as a tool to design new HEAs.