Project Description
The research project is aimed at utilizing machine learning to understand the effect of alloy compositions and processing conditions on the properties of the alloy, such as hardness, density, wettability, coefficient of friction, tensile strength, etc. Our lab has demonstrated the successful implementation of machine learning for wettability in aluminum alloys. Al-Ce alloys are widely studied due to their ability to retain their mechanical properties at high-temperatures. This project will implement machine learning in the Al-Ce alloy system and their composites.
Tasks and Responsibilites
The student will be responsible for building and implementing machine learning models for the predictive analysis of the alloy and composite properties. The student will gather databases and perform literature review of prior work on implementing machine learning in metallurgy. The student will engage in discussions with the graduate students to determine the critical factors that drive material properties and track key performance indicators.
Desired Qualifications
None listed.