Ab initio phase stabilities and mechanical properties of multicomponent alloys: A comprehensive review for high entropy alloys and compositionally complex alloys

By Yuji Ikeda, Blazej Grabowski, Fritz Körmann. Materials Characterization, 2019

302 citations recorded by the source corpus.

Abstract Multicomponent alloys with multiple principal elements including high entropy alloys (HEAs) and compositionally complex alloys (CCAs) are attracting rapidly growing attention. The endless possibilities to explore new alloys and the hope for better combinations of materials properties have stimulated a remarkable number of research works in the last years. Most of these works have been based on experimental approaches, but ab initio calculations have emerged as a powerful approach that complements experiment and serves as a predictive tool for the identification and characterization of promising alloys. The theoretical ab initio modeling of phase stabilities and mechanical properties of multi-principal element alloys by means of density functional theory (DFT) is reviewed. A general thermodynamic framework is laid down that provides a bridge between the quantities accessible with DFT and the targeted thermodynamic and mechanical properties. It is shown how chemical disorder and various finite-temperature excitations can be modeled with DFT. Different concepts to study crystal and alloy phase stabilities, the impact of lattice distortions (a core effect of HEAs), magnetic transitions, and chemical short-range order are discussed along with specific examples. Strategies to study elastic properties, stacking fault energies, and their dependence on, e.g., temperature or alloy composition are illustrated. Finally, we provide an extensive compilation of multi-principal element alloys and various material properties studied with DFT so far (a set of over 500 alloy-property combinations).

Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/37ef5187cf4f853f490906599f91fe54b86938c1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. M. Ghazisaeidi
2. Zongrui Pei
3. Xianglin Liu
4. Jiaxin Zhang
5. C. Varvenne
6. M. Shih
7. Carlyn R. LaRosa

In Electrical and Electronic Engineering

1. C. Varvenne
2. M. Shih
3. Xianglin Liu
4. Zongrui Pei
5. Carlyn R. LaRosa
6. M. Ghazisaeidi
7. Jiaxin Zhang

In Mechanical Engineering

1. M. Ghazisaeidi
2. M. Shih
3. Carlyn R. LaRosa
4. Zongrui Pei
5. Xianglin Liu
6. Jiaxin Zhang
7. C. Varvenne

Citations in the corpus

• Solid solution strengthening theories of high-entropy alloys (2019, background): “and require several simulations of sufficient size and accuracy to capture the fluctuations from the average values caused by high concentrations of multiple elements [36].”
• Machine Learning for High-entropy Alloys: Progress, Challenges and Opportunities (2022, background): “Since there are a number of excellent review papers focused on HEAs [7, 8, 9, 10, 11, 12, 13], we have no intention to restate the details therein, which is also not the main focus of this work.”