Abstract
Atomic ordering in bcc and hcp TiAl+Mo alloys near equiatomic TiAl composition is investigated by different ab initio tools. We show that small addition of Mo, about 5 at. %, is enough to make bcc alloys with more than 50 at. % of Ti stable with respect to the hcp alloys. Moreover, such alloying also leads to stabilizing the B2 ordered structure with respect to its B2 2 modification, which is the bcc-based ground state structure of binary TiAl. The site preference of Mo in the B2 and B19 ordered alloys is investigated by different methods: in the dilute limit, using the transfer energy formalism; in concentrated alloys, from the total energies of disordered and partially ordered alloys in the mean-field coherent potential approximation; and from Monte Carlo simulations. These methods produce consistent results for the B2 phase predicting a strong preference of Mo to Al sublattice. The site preference of Mo in the B19 phases varies from a weak preference for Al sites in the single impurity calculations to a quite strong preference for Ti sites in the mean-field approximation and finally to a strong Al preference in Monte Carlo simulations. Mo alloying dramatically increases the order–disorder transition temperatures in bcc and hcp Al-deficient Ti 0.5Al 0.5−xMo x alloys.
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 111163 |
| Seitenumfang | 11 |
| Fachzeitschrift | Computational materials science |
| Jahrgang | 205.2022 |
| Ausgabenummer | 1 April |
| DOIs | |
| Publikationsstatus | Elektronische Veröffentlichung vor Drucklegung. - 18 Jan. 2022 |
Bibliographische Notiz
Funding Information:This research was funded by the Austrian Science Fund (FWF) Project No. P29731-N36 . The computational results presented were achieved, in part, using the Vienna Scientific Cluster (VSC). Additional computational resources were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC (Stockholm) and NSC (Linköping) and through PRACE resources. AVR acknowledges a European Research Council grant, the VINNEX center Hero-m, financed by the Swedish Governmental Agency for Innovation Systems (VINNOVA), Swedish industry, and the Royal Institute of Technology (KTH). The authors also gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center “Integrated Computational Material, Process and Product Engineering (IC-MPPE)” (Project No 859480 ). This program is supported by the Austrian Federal Ministries for 718 Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and for Digital and Economic Affairs (BMDW), represented by the Austrian research funding association (FFG), and the federal states of Styria, Upper Austria, and Tyrol.
Funding Information:
This research was funded by the Austrian Science Fund (FWF) Project No. P29731-N36. The computational results presented were achieved, in part, using the Vienna Scientific Cluster (VSC). Additional computational resources were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC (Stockholm) and NSC (Link?ping) and through PRACE resources. AVR acknowledges a European Research Council grant, the VINNEX center Hero-m, financed by the Swedish Governmental Agency for Innovation Systems (VINNOVA), Swedish industry, and the Royal Institute of Technology (KTH). The authors also gratefully acknowledge the financial support under the scope of the COMET program within the K2 Center ?Integrated Computational Material, Process and Product Engineering (IC-MPPE)? (Project No 859480). This program is supported by the Austrian Federal Ministries for 718 Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK) and for Digital and Economic Affairs (BMDW), represented by the Austrian research funding association (FFG), and the federal states of Styria, Upper Austria, and Tyrol.
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