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First-principles investigations ofωvariant selection during athermalβ→ωtransformation of binary Ti-xMo alloy

Authors :
Shuo Cao
Qing-Miao Hu
Rui Yang
Jia-Lin Zhu
Yunzhi Wang
Source :
Computational Materials Science. 155:524-533
Publication Year :
2018
Publisher :
Elsevier BV, 2018.

Abstract

Variant selection during solid–solid phase transformation in titanium alloys affects greatly the microstructure and mechanical properties of the alloys. Theoretical investigations of the variant selection were generally performed by using phase field simulation that considers solely the elastic coherency strain energy. In the present work, we develop a model to determine the variant selection directly from first-principles calculations. The source of the variant selection is considered to be the varying free energy gains (including both bulk and interface contributions) induced by the transformation from the parent phase to different variants of the product phase. This model is applied to investigate the effects of shear stress and alloy composition on ω variant selection during athermal β → ω transformation in binary Ti-xMo ( x ≤ 25 at.%) alloys. The random distribution of the atoms in the alloy is described by using virtual crystal approximation (VCA). We show that the tendency of variant selection becomes stronger with increasing shear stress. With increasing Mo concentration, the favorable ω variant transfers from one to another, except for the ω phase with very small particle size (e.g., radius R ≤ 1 nm) where one variant is always selected. The critical Mo concentration for the transfer of the favorable ω variant approaches to 5 at.% with increasing size of the ω phase particles and remains almost unchanged against the shear stress. At the critical Mo concentration, the considered variants have equal free energy gains and there is no variant selection. This finding opens the possibility of controlling the variant selection and the associated microstructure by changing the composition of the alloys.

Details

ISSN :
09270256
Volume :
155
Database :
OpenAIRE
Journal :
Computational Materials Science
Accession number :
edsair.doi...........c515197818de827693cff4f19187380e