Application Artificial Intelligence in Metallurgy & Materials – Part 3

Part 3 of the seminar focuses on leveraging AI to expedite the discovery and development of new materials. This session features presentations by leading researchers:

● Dezhen Xue: Active learning in searching for new materials, with emphasis on efficient sampling using uncertainties.
● Enzo Liotti: Study of nucleation in aluminum alloys using X-ray radiography and machine learning.
Victor Castillo: Faster prediction with AI: using process simulations and production data to develop fast-running inference models for manufacturing.

Key takeaways:

● AI can be used to strategically guide the search for novel materials with desired properties.
● AI can be used to analyze X-ray data and gain insights into the formation of new phases within materials.
● AI can utilize existing data to create efficient models for real-time predictions in manufacturing settings.

Who should attend:

○ Researchers interested in AI-powered materials discovery
○ Materials scientists working with aluminum alloys
○ Engineers involved in manufacturing process optimization