AI-Assisted Titanium Alloy Exploration
Project Description
This project introduces machine learning to explore titanium alloy compositions. Students will use existing databases to train simple AI models predicting basic mechanical properties. Lab validation involves basic microstructure analysis of pre-made samples. Focuses on understanding strength-ductility trade-offs in alloys.
Supervisor
ZHANG, Tianlong
Quota
2
Course type
UROP1100
Applicant's Roles
Input data into user-friendly ML tools (no coding)
Prepare samples for microscopy (grinding/polishing)
Analyze phase distribution in pre-tested alloys
Prepare samples for microscopy (grinding/polishing)
Analyze phase distribution in pre-tested alloys
Applicant's Learning Objectives
Apply AI tools for materials screening
Conduct basic metallographic preparation
Correlate microstructures with property trends
Deliverable: Comparative report on 3 promising alloy compositions
Conduct basic metallographic preparation
Correlate microstructures with property trends
Deliverable: Comparative report on 3 promising alloy compositions
Complexity of the project
Moderate