Influence of ordering behaviors on thermodynamic and mechanical properties of FCC_CoNiV multi-principal element alloys
(1. Materials Design and Manufacture Simulation Facility, School of Advance Manufacturing, Fuzhou University, Jinjiang 362200, China;
2. Multiscale Computational Materials Facility & Materials Genome Institute, School of Materials Science and Engineering, Fuzhou University, Fuzhou 350100, China;
3. Institute of High Temperature Alloy, Central Iron & Steel Research Institute Group, Beijing 100081, China)
2. Multiscale Computational Materials Facility & Materials Genome Institute, School of Materials Science and Engineering, Fuzhou University, Fuzhou 350100, China;
3. Institute of High Temperature Alloy, Central Iron & Steel Research Institute Group, Beijing 100081, China)
Abstract: In order to understand the influence of ordering behaviors on the thermodynamic and mechanical properties of multi-principal element alloys (MPEAs), the temperature-dependent thermodynamic properties and mechanical properties of FCC_CoNiV MPEAs were comparatively predicted, where the alloys were modeled as the ordered configurations based on our previously predicted site occupying fractions (SOFs), as well as disordered configuration based on traditional special quasi-random structure (SQS). The ordering behavior not only improves the thermodynamic stability of the structure, but also increases the elastic properties and Vickers hardness. For example, at 973 K, the predicted bulk modulus (B), shear modulus (G), Young’s modulus (E), and Vickers hardness (HV) of FCC_CoNiV MPEA based on SOFs configuration are 187.82, 79.03, 207.93, and 7.58 GPa, respectively, while the corresponded data are 172.58, 57.45, 155.14, and 4.64 GPa for the SQS configuration, respectively. The Vickers hardness predicted based on SOFs agrees considerably well with the available experimental data, while it is underestimated obviously based on SQS.
Key words: FCC_CoNiV; multi-principal element alloys (MPEAs); ordering behavior; temperature-dependent properties; computational materials science