When 11:00 AM - 1:00 PM Dec 09, 2016
Where 1180 Duderstadt
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Recrystallization and Grain Growth Kinetics in Binary Alpha Titanium-Aluminum Alloys

Anna Trump
Thesis Defense

Titanium alloys are used in a variety of important naval and aerospace applications and often undergo thermomechanical processing which leads to recrystallization and grain growth. Both of these processes have a significant impact on the mechanical properties of the material. Therefore, understanding the kinetics of these processes is crucial to being able to predict the final properties. Three alloys are studied with varying concentrations of aluminum which allows for the direct quantification of the effect of aluminum content on the kinetics of recrystallization and grain growth. Aluminum is the most common alpha stabilizing alloying element used in titanium alloys, however the effect of aluminum on these processes has not been previously studied. The static recrystallization kinetics are measured using an electron backscatter diffraction (EBSD) technique and a significant retardation in the kinetics is observed with increasing aluminum concentration. An analytical model is then used to capture these results and is able to successfully predict the effect of solute concentration on the time to 50% recrystallization. The model reveals that this solute effect is due to a combination of a decrease in grain boundary mobility and a decrease in driving force with increasing aluminum concentration. The effect of microstructural heterogeneities is also experimentally quantified and these results are validated with a phase field model for recrystallization. Similar to the effect seen in recrystallization, the addition of aluminum also significantly slows downs the grain growth kinetics. This is generally attributed to the solute drag effect due to segregation of solute atoms at the grain boundaries, however aluminum segregation is not observed in these alloys. The mechanism for this result is explained and is used to validate the prediction of an existing model for solute drag. This work is also part of a larger Integrated Computational Materials Engineering (ICME) effort whose goal is to combine both computational and experimental efforts to develop computationally efficient models that predict materials microstructure and properties based on processing history.



Chair: Prof. John Allison , MSE

Member: Prof. J. Wayne Jones, MSE

Member: Prof. Katsuyo Thornton, MSE

Cognate: Assoc. Prof. Veera Sundararaghavan Aerospace