Barriobero Vila, P., Requena, G., Buslaps, T., Alfeld, M., & Boesenberg, U. (2015). Role of element partitioning on the α-β phase transformation kinetics of a bi-modal Ti-6Al-6V-2Sn alloy during continuous heating. Journal of Alloys and Compounds, 626, 330–339. https://doi.org/10.1016/j.jallcom.2014.11.176
Mechanical Engineering; Mechanics of Materials; Titanium alloys; Materials Chemistry; Metals and Alloys; High-energy X-ray diffraction; Phase transformation kinetics; Micro X-ray fluorescence; Element partitioning
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Abstract:
The role of element partitioning on the phase transformation kinetics of a bi-modal α + β Ti-6Al-6V-2Sn alloy is studied experimentally as a function of heating rate combining quantitative phase analysis with elemental analysis. The evolution of phase volume fractions and lattice parameters is investigated by in situ high energy synchrotron X-ray diffraction and conventional metallographic analysis. Synchrotron micro X-ray fluorescence and energy dispersive X-ray spectroscopy are applied to trace microstructural distribution of alloying elements during heating. The linear increase of the lattice parameters observed for all conditions at the beginning of the heating is associated to lattice thermal expansion. Thereafter, at intermediate temperatures, the alloy undergoes a β to α transformation for low heating rates. Element partitioning results in an enrichment of α and β by their respective stabilizing elements and a consequent nonlinear variation of the lattice parameters. As the temperature increases, α transforms into β up to the β-transus temperature. Microstructural evidences of the role of V during phase transformation are presented. Moreover, nonlinear variations of the β lattice parameter are related to the role of alloying elements on the different stages of element partitioning. The analysis of phase transformation kinetics combining laboratory and synchrotron-based techniques provides an advance in the current knowledge of the phase transformation kinetics of the Ti-6Al-6V-2Sn alloy that can help to develop new theoretical models and, consequently, knowledge-based thermal treatment optimization.