![]() ![]() The application of machine learning (ML) techniques to HEAs is also on the rise 34, 35, 36, 37, 38, 39, 40, 41. The CALPHAD (calculation of phase diagrams) method has been used to determine the phase formation of HEAs 30, 31, 32 although reliable thermodynamic databases are currently limited to a small number of elements 33. More sophisticated models additionally take into account the free energy of IM compounds 26, 27, 28, but are still oversimplified in that the IM phases are hypothetical and different definitions of the competing IM phases can lead to diverging predictions 25, 29. Early models follow the Hume-Rothery theory 20, 21 and rely on simple descriptors such as atomic radius mismatch and tabulated mixing enthalpy to induce the empirical rules for the formation of multicomponent solid solutions 22, 23, 24, 25. Numerous computational methods have been developed to predict the stability of single-phase solid solutions. Indeed, very limited regions in the compositional space have been explored and experimental screening alone would be formidable. Computational approaches are called upon to understand the driving force towards the formation of HEAs and ultimately to accelerate the discovery of new HEAs with specific properties. Yet, only a limited number of equimolar quinary single-phase HEAs have been observed experimentally over the last decade. For equimolar quinary alloys, there are 658,008 candidates resulting from the combination of 40 elements. This is happening while the concept of high entropy stabilization is extended beyond metallic alloys with the development of high-entropy oxides and ceramics 18, 19. ![]() While HEAs have first been mainly studied as structural materials, the field is now expanding to other areas such as electrocatalysis 10, thermoelectrics 11, and energy storage 12, 13, 14, 15, 16, 17. HEAs can exhibit unusual properties 3, 4 from exceptional toughness at cryogenic temperatures 5, to an outstanding combination of strength and ductility 6, 7, high damage tolerance 8 and corrosion resistance 9. The seemingly surprising stabilization of multicomponent alloys against the formation of multiple phases and intermetallics (IMs) has been associated with the high configurational entropy 2 among other important factors 3. In contrast to conventional alloys centering around one primary element with minor amounts of other elements, HEAs mix five or more elements at equal or near-equal compositions often in a single crystalline phase 1, 2. ![]() The field of metallurgy has been recently impacted by the emergence of high-entropy alloys (HEAs). the body-centered cubic AlCoMnNiV and the face-centered cubic CoFeMnNiZn, which are successfully synthesized. We demonstrate the power of our method by predicting the existence of two new high-entropy alloys, i.e. We unveil the chemistries that are likely to form high-entropy alloys, and identify the complex interplay among mixing enthalpy, intermetallics formation, and melting point that drives the formation of these solid solutions. We identify 30,201 potential single-phase equimolar alloys (5% of the possible combinations) forming mainly in body-centered cubic structures. Herein, based on high-throughput density-functional theory calculations, we construct a chemical map of single-phase equimolar high-entropy alloys by investigating over 658,000 equimolar quinary alloys through a binary regular solid-solution model. The stability of equimolar single-phase solid solution of five or more elements is supposedly rare and identifying the existence of such alloys has been challenging because of the vast chemical space of possible combinations. High-entropy alloys have exhibited unusual materials properties. ![]()
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