| About this Abstract |
| Meeting |
2021 TMS Annual Meeting & Exhibition
|
| Symposium
|
Phase Transformations and Microstructural Evolution
|
| Presentation Title |
Exploring Non-conventional Microstructural Evolution in Titanium Alloys by Advanced Characterization and Machine Learning |
| Author(s) |
Dian Li, Xing Zhang, Yiliang Liao, Yufeng Zheng |
| On-Site Speaker (Planned) |
Dian Li |
| Abstract Scope |
Titanium alloys are important structural materials and their balanced properties can be manipulated via microstructural engineering. In order to explore the various novel non-conventional microstructural evolutions in titanium alloys, accurate materials characterization and rapid microstructure analysis are required. In the present work, the microstructural evolution in a beta titanium alloy, Ti-5Al-5Mo-5V-3Cr (wt.%, Ti5553), under different thermomechanical treatments has been characterized using scanning electron microscopy and analyzed using machine learning. The large amount of image data was quantitatively analyzed via the deep learning module in the image analysis software, MIPAR, focusing on the important features of alpha microstructure, e.g., morphology, size and areal fraction. The response of cold-rolled Ti5553 to the subsequent heat treatment was explored via advanced electron microscopy. The factor of mechanical treatment has been taken into consideration for microstructure engineering in Ti5553 and the influence of prior deformation twin on the microstructural evolution in Ti5553 will be introduced. |
| Proceedings Inclusion? |
Planned: |