Conference Tools for 2026 TMS Annual Meeting & Exhibition

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Meeting

2026 TMS Annual Meeting & Exhibition

Symposium

Artificial Intelligence Applications in Integrated Computational Materials Engineering (AI-ICME)

Presentation Title

From CALPHAD to AI: High-Throughput Pathways for Functionally Graded Alloy Design and Additive Manufacturing

Author(s)

Wei Xiong

On-Site Speaker (Planned)

Wei Xiong

Abstract Scope

CALPHAD-based ICME modeling has long been a cornerstone in the composition and processing design of advanced manufacturing. By combining high-throughput modeling with targeted experiments, we establish pathways that enrich databases and enable machine learning to further enhance ICME predictive capabilities. Here, we present our recent efforts in functionally graded alloy printing, an approach that inherently generates high-throughput datasets for machine learning–assisted ICME design. Our case studies focus on designing new alloy compositions by leveraging commercially available alloys commonly used in manufacturing. This strategy supports circular metallurgical processing and significantly reduces raw material consumption. The results highlight the untapped potential of well-known composition spaces for improving mechanical and functional properties. Finally, we discuss key limitations and propose strategies to accelerate design efficiency by integrating artificial intelligence with CALPHAD-based ICME through streamlined high-throughput development pathways.

Proceedings Inclusion?

Planned:

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