An informatics guided classification of miscible and immiscible binary alloy systems

Abstract

The classification of miscible and immiscible systems of binary alloys plays a critical role in the design of multicomponent alloys. By mining data from hundreds of experimental phase diagrams, and thousands of thermodynamic data sets from experiments and high-throughput first-principles (HTFP) calculations, we have obtained a comprehensive classification of alloying behavior for 813 binary alloy systems consisting of transition and lanthanide metals. Among several physics-based descriptors, the slightly modified Pettifor chemical scale provides a unique two-dimensional map that divides the miscible and immiscible systems into distinctly clustered regions. Based on an artificial neural network algorithm and elemental similarity, the miscibility of the unknown systems is further predicted and a complete miscibility map is thus obtained. Impressively, the classification by the miscibility map yields a robust validation on the capability of the well-known Miedema’s theory (95% agreement) and shows good agreement with the HTFP method (90% agreement). Our results demonstrate that a state-of-the-art physics-guided data mining can provide an efficient pathway for knowledge discovery in the next generation of materials design.

Learning grain boundary segregation energy spectra in polycrystals

“…segregation tendency in any given alloy, especially at low or dilute solute concentration. The choice of the Pettifor chemical scale (which preserves the Mendeleev-type features of the elements 61 ) is based on its success in pattern clustering (separation) for miscibility 62 , ordering tendency 63,64 , and crystal structures of intermetallics 61 in binary alloys. Though Fig.…”

Half-metallicity in uranium intermetallics: crystal structure prediction of a high-pressure phase of UCo

“…60 Although the absolute values of formation enthalpies predicted by the Miedema model can significantly differ from experimental values, it is able to correctly predict the alloying behavior of binary alloys with a success rate of about 95% as demonstrated by a recent study. 65 Therefore, we expect the relative enthalpy differences of uraniumcobalt alloys calculated by the PBE functional to be reliable.…”

Revealing the Phase Separation Behavior of Thermodynamically Immiscible Elements in a Nanoparticle

“…Phase-separation is a typical thermodynamic phenomenon that can be found in multimetallic materials. 1,2 Metals with a highly positive enthalpy of mixing are energetically unfavorable to be mixed with each other, which usually segregate into different domains. [2][3][4] Such phenomenon is particularly ubiquitous in nanoparticles composed of immiscible elements.…”

“…1,2 Metals with a highly positive enthalpy of mixing are energetically unfavorable to be mixed with each other, which usually segregate into different domains. [2][3][4] Such phenomenon is particularly ubiquitous in nanoparticles composed of immiscible elements. In addition, the small size and high surface-area-to-volume ratio of nanoparticles impart them high flexibility in structural transformation.…”